python /home/admin/mtr/script_for_cron.py -j python_test3 -m 12 -a ' --short_python3 -v ' -s python_test3 -M 0 -S 0 -U 100,100,120 import MySQLdb succeeded Import error (python version) python version = 3 warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data list_job_run_as_list : ['mask_detection', 'datou', 'CacheModelData_queries', 'CachePhotoData_queries', 'test_fork', 'prepare_maskdata', 'portfolio_queries', 'sla_mensuel'] python version used : 3 liste_fichiers : [('tests/mask_test', True, 'Test mask-detection ', 'mask_detection'), ('tests/datou_test', True, 'Datou All Test', 'datou', 'all'), ('mtr/database_queries/CacheModelData_queries', True, 'Test Cache Model Data', 'CacheModelData_queries'), ('tests/cache_photo_data_test', True, 'Test local_cache_photo ', 'CachePhotoData_queries'), ('mtr/mask_rcnn/prepare_maskdata', True, 'test prepare mask data', 'prepare_maskdata', 'all'), ('mtr/database_queries/portfolio_queries', True, 'test portfolio queries', 'portfolio_queries'), ('prod/memo/memo', True, 'SLA Mensuel', 'sla_mensuel', 'all')] #&_# BEGIN OF TEST : tests/mask_test #&_# /home/admin/workarea/git/Velours/python/tests/mask_test.py Test mask-detection python version used : 3 ############################### TEST memory used ################################ free memory at begining : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10582 run mask_detect Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 0 ; length of list_pids : 0 ; length of list_args : 0 time to download the photos : 0.008612871170043945 About to test input to load empty input or other problem ret : 0 no datou_current to update free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10582 ############################### TEST detect object ################################ run mask_detect Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 0 ; length of list_pids : 0 ; length of list_args : 0 time to download the photos : 0.005994558334350586 About to test input to load empty input or other problem ret : 0 no datou_current to update ERROR : cannot unpack non-iterable NoneType object reconnect to base ! warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data #&_# TEST FAILED #&_# : tests/mask_test #&_# Error : invalid literal for int() with base 10: 'cannot unpack non-iterable NoneType object' /home/admin/workarea/git/Velours/python/tests/python_tests.py refs/heads/migration_mbp_22_09_25_51acd07c86639a4bc239bb841ffeb11177e01b4d SQL :INSERT INTO MTRAdmin.monitor_sys (name, type, server, version_code, result_str, result_bool, lien , test_group ,test_name) VALUES ('python_test3','1','marlene','refs/heads/migration_mbp_22_09_25_51acd07c86639a4bc239bb841ffeb11177e01b4d','{"mask_detection": "fail"}','0','http://marlene.fotonower-preprod.com/job/2025/September/25092025/python_test3/','mask_detection','unknown'); #&_# END OF TEST #&_# : tests/mask_test #&_# #&_# BEGIN OF TEST : tests/datou_test #&_# /home/admin/workarea/git/Velours/python/tests/datou_test.py Datou All Test python version used : 3 ############################### TEST sam ################################ TEST SAM Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4573 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4573 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4573 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4573 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : sam list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (1189321094) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 1189321094 download finish for photo 1189321094 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1731555461883545 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:sam Thu Sep 25 17:02:04 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812524_3157952_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1758812524_3157952_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png', 'extension': 'png'}} map_subphoto_mainphoto : {} Beginning of datou step sam ! pht : 4677 Inside sam : nb paths : 1 (640, 960, 3) time for calcul the mask position with numpy : 0.0020241737365722656 nb_pixel_total : 5615 time to create 1 rle with old method : 0.006319522857666016 time for calcul the mask position with numpy : 0.0014808177947998047 nb_pixel_total : 7639 time to create 1 rle with old method : 0.008287191390991211 time for calcul the mask position with numpy : 0.0013628005981445312 nb_pixel_total : 16448 time to create 1 rle with old method : 0.0175323486328125 time for calcul the mask position with numpy : 0.0023314952850341797 nb_pixel_total : 83475 time to create 1 rle with old method : 0.0918576717376709 time for calcul the mask position with numpy : 0.0014963150024414062 nb_pixel_total : 5316 time to create 1 rle with old method : 0.00590062141418457 time for calcul the mask position with numpy : 0.0014219284057617188 nb_pixel_total : 3780 time to create 1 rle with old method : 0.004025459289550781 time for calcul the mask position with numpy : 0.0015904903411865234 nb_pixel_total : 29487 time to create 1 rle with old method : 0.03247690200805664 time for calcul the mask position with numpy : 0.0015397071838378906 nb_pixel_total : 13918 time to create 1 rle with old method : 0.01544332504272461 time for calcul the mask position with numpy : 0.0013616085052490234 nb_pixel_total : 2942 time to create 1 rle with old method : 0.003441333770751953 time for calcul the mask position with numpy : 0.0013303756713867188 nb_pixel_total : 10821 time to create 1 rle with old method : 0.01191568374633789 time for calcul the mask position with numpy : 0.0014646053314208984 nb_pixel_total : 3927 time to create 1 rle with old method : 0.004492282867431641 time for calcul the mask position with numpy : 0.0013260841369628906 nb_pixel_total : 4276 time to create 1 rle with old method : 0.004832267761230469 time for calcul the mask position with numpy : 0.0014333724975585938 nb_pixel_total : 1219 time to create 1 rle with old method : 0.0014307498931884766 time for calcul the mask position with numpy : 0.0012841224670410156 nb_pixel_total : 2452 time to create 1 rle with old method : 0.0030858516693115234 time for calcul the mask position with numpy : 0.0014488697052001953 nb_pixel_total : 13116 time to create 1 rle with old method : 0.016680479049682617 time for calcul the mask position with numpy : 0.0014142990112304688 nb_pixel_total : 6635 time to create 1 rle with old method : 0.007665872573852539 time for calcul the mask position with numpy : 0.0014264583587646484 nb_pixel_total : 2081 time to create 1 rle with old method : 0.002410411834716797 time for calcul the mask position with numpy : 0.0014963150024414062 nb_pixel_total : 16325 time to create 1 rle with old method : 0.020591259002685547 time for calcul the mask position with numpy : 0.0014560222625732422 nb_pixel_total : 4272 time to create 1 rle with old method : 0.005190849304199219 time for calcul the mask position with numpy : 0.0013921260833740234 nb_pixel_total : 5474 time to create 1 rle with old method : 0.0062558650970458984 time for calcul the mask position with numpy : 0.0015978813171386719 nb_pixel_total : 39077 time to create 1 rle with old method : 0.041402578353881836 time for calcul the mask position with numpy : 0.0013337135314941406 nb_pixel_total : 8636 time to create 1 rle with old method : 0.008980274200439453 time for calcul the mask position with numpy : 0.001470327377319336 nb_pixel_total : 11997 time to create 1 rle with old method : 0.012682199478149414 time for calcul the mask position with numpy : 0.0013263225555419922 nb_pixel_total : 10565 time to create 1 rle with old method : 0.011314868927001953 time for calcul the mask position with numpy : 0.0012898445129394531 nb_pixel_total : 3525 time to create 1 rle with old method : 0.003875732421875 time for calcul the mask position with numpy : 0.0012717247009277344 nb_pixel_total : 858 time to create 1 rle with old method : 0.0010576248168945312 time for calcul the mask position with numpy : 0.0012803077697753906 nb_pixel_total : 3587 time to create 1 rle with old method : 0.0040090084075927734 time for calcul the mask position with numpy : 0.0012786388397216797 nb_pixel_total : 337 time to create 1 rle with old method : 0.0003991127014160156 time for calcul the mask position with numpy : 0.0012760162353515625 nb_pixel_total : 2781 time to create 1 rle with old method : 0.003215312957763672 time for calcul the mask position with numpy : 0.0012776851654052734 nb_pixel_total : 2448 time to create 1 rle with old method : 0.002611398696899414 time for calcul the mask position with numpy : 0.0012764930725097656 nb_pixel_total : 2773 time to create 1 rle with old method : 0.003007650375366211 time for calcul the mask position with numpy : 0.0013124942779541016 nb_pixel_total : 9879 time to create 1 rle with old method : 0.010579824447631836 time for calcul the mask position with numpy : 0.0014216899871826172 nb_pixel_total : 4121 time to create 1 rle with old method : 0.005303144454956055 time for calcul the mask position with numpy : 0.0014004707336425781 nb_pixel_total : 12972 time to create 1 rle with old method : 0.014261484146118164 time for calcul the mask position with numpy : 0.0013756752014160156 nb_pixel_total : 1643 time to create 1 rle with old method : 0.0018835067749023438 time for calcul the mask position with numpy : 0.0014944076538085938 nb_pixel_total : 14652 time to create 1 rle with old method : 0.01631927490234375 time for calcul the mask position with numpy : 0.0013608932495117188 nb_pixel_total : 3308 time to create 1 rle with old method : 0.0036814212799072266 time for calcul the mask position with numpy : 0.001476287841796875 nb_pixel_total : 8618 time to create 1 rle with old method : 0.0095367431640625 time for calcul the mask position with numpy : 0.0013287067413330078 nb_pixel_total : 1024 time to create 1 rle with old method : 0.0011756420135498047 time for calcul the mask position with numpy : 0.0017709732055664062 nb_pixel_total : 1244 time to create 1 rle with old method : 0.0018496513366699219 time for calcul the mask position with numpy : 0.0017766952514648438 nb_pixel_total : 3854 time to create 1 rle with old method : 0.005032062530517578 time for calcul the mask position with numpy : 0.0013995170593261719 nb_pixel_total : 4177 time to create 1 rle with old method : 0.004590034484863281 time for calcul the mask position with numpy : 0.0012736320495605469 nb_pixel_total : 874 time to create 1 rle with old method : 0.0010542869567871094 time for calcul the mask position with numpy : 0.0012881755828857422 nb_pixel_total : 2386 time to create 1 rle with old method : 0.0027625560760498047 time for calcul the mask position with numpy : 0.0012755393981933594 nb_pixel_total : 594 time to create 1 rle with old method : 0.0006830692291259766 time for calcul the mask position with numpy : 0.0012826919555664062 nb_pixel_total : 2318 time to create 1 rle with old method : 0.0027801990509033203 time for calcul the mask position with numpy : 0.0014255046844482422 nb_pixel_total : 2031 time to create 1 rle with old method : 0.0024542808532714844 time for calcul the mask position with numpy : 0.0014066696166992188 nb_pixel_total : 576 time to create 1 rle with old method : 0.0007483959197998047 time for calcul the mask position with numpy : 0.0014231204986572266 nb_pixel_total : 888 time to create 1 rle with old method : 0.0011246204376220703 time for calcul the mask position with numpy : 0.001432180404663086 nb_pixel_total : 8636 time to create 1 rle with old method : 0.009697914123535156 time for calcul the mask position with numpy : 0.0013263225555419922 nb_pixel_total : 1674 time to create 1 rle with old method : 0.0021398067474365234 time for calcul the mask position with numpy : 0.0014293193817138672 nb_pixel_total : 2407 time to create 1 rle with old method : 0.0030927658081054688 time for calcul the mask position with numpy : 0.0013575553894042969 nb_pixel_total : 337 time to create 1 rle with old method : 0.0004649162292480469 time for calcul the mask position with numpy : 0.0014638900756835938 nb_pixel_total : 693 time to create 1 rle with old method : 0.0009109973907470703 time for calcul the mask position with numpy : 0.0014240741729736328 nb_pixel_total : 1713 time to create 1 rle with old method : 0.0023903846740722656 time for calcul the mask position with numpy : 0.0014545917510986328 nb_pixel_total : 1070 time to create 1 rle with old method : 0.0015954971313476562 time for calcul the mask position with numpy : 0.0019047260284423828 nb_pixel_total : 2768 time to create 1 rle with old method : 0.004338741302490234 time for calcul the mask position with numpy : 0.0017876625061035156 nb_pixel_total : 3112 time to create 1 rle with old method : 0.0043239593505859375 time for calcul the mask position with numpy : 0.00130462646484375 nb_pixel_total : 1207 time to create 1 rle with old method : 0.0015256404876708984 time for calcul the mask position with numpy : 0.0013775825500488281 nb_pixel_total : 586 time to create 1 rle with old method : 0.0006911754608154297 time for calcul the mask position with numpy : 0.0014955997467041016 nb_pixel_total : 27877 time to create 1 rle with old method : 0.030448198318481445 time for calcul the mask position with numpy : 0.0014050006866455078 nb_pixel_total : 13443 time to create 1 rle with old method : 0.014083623886108398 time for calcul the mask position with numpy : 0.0012738704681396484 nb_pixel_total : 1055 time to create 1 rle with old method : 0.0012445449829101562 time for calcul the mask position with numpy : 0.001352071762084961 nb_pixel_total : 18452 time to create 1 rle with old method : 0.01960444450378418 time for calcul the mask position with numpy : 0.0013539791107177734 nb_pixel_total : 16681 time to create 1 rle with old method : 0.018714189529418945 time for calcul the mask position with numpy : 0.001277923583984375 nb_pixel_total : 1741 time to create 1 rle with old method : 0.0018780231475830078 time for calcul the mask position with numpy : 0.0012700557708740234 nb_pixel_total : 1441 time to create 1 rle with old method : 0.0016617774963378906 time for calcul the mask position with numpy : 0.0012776851654052734 nb_pixel_total : 267 time to create 1 rle with old method : 0.0003311634063720703 time for calcul the mask position with numpy : 0.0012755393981933594 nb_pixel_total : 616 time to create 1 rle with old method : 0.0007312297821044922 time for calcul the mask position with numpy : 0.0013077259063720703 nb_pixel_total : 9082 time to create 1 rle with old method : 0.009673118591308594 time for calcul the mask position with numpy : 0.0012934207916259766 nb_pixel_total : 1513 time to create 1 rle with old method : 0.0016179084777832031 time for calcul the mask position with numpy : 0.0012919902801513672 nb_pixel_total : 1332 time to create 1 rle with old method : 0.0015134811401367188 time for calcul the mask position with numpy : 0.0012655258178710938 nb_pixel_total : 965 time to create 1 rle with old method : 0.0010616779327392578 time for calcul the mask position with numpy : 0.00127410888671875 nb_pixel_total : 713 time to create 1 rle with old method : 0.0008580684661865234 time for calcul the mask position with numpy : 0.0013098716735839844 nb_pixel_total : 9489 time to create 1 rle with old method : 0.010097980499267578 time for calcul the mask position with numpy : 0.0013859272003173828 nb_pixel_total : 3166 time to create 1 rle with old method : 0.0034346580505371094 time for calcul the mask position with numpy : 0.0012874603271484375 nb_pixel_total : 4997 time to create 1 rle with old method : 0.005440950393676758 time for calcul the mask position with numpy : 0.0012636184692382812 nb_pixel_total : 248 time to create 1 rle with old method : 0.0003159046173095703 time for calcul the mask position with numpy : 0.0012676715850830078 nb_pixel_total : 887 time to create 1 rle with old method : 0.0010738372802734375 time for calcul the mask position with numpy : 0.0013108253479003906 nb_pixel_total : 973 time to create 1 rle with old method : 0.0011184215545654297 time for calcul the mask position with numpy : 0.0013113021850585938 nb_pixel_total : 221 time to create 1 rle with old method : 0.0003235340118408203 time for calcul the mask position with numpy : 0.0013165473937988281 nb_pixel_total : 1337 time to create 1 rle with old method : 0.0016052722930908203 time for calcul the mask position with numpy : 0.0012705326080322266 nb_pixel_total : 597 time to create 1 rle with old method : 0.0007109642028808594 time for calcul the mask position with numpy : 0.001268148422241211 nb_pixel_total : 1127 time to create 1 rle with old method : 0.0012485980987548828 time for calcul the mask position with numpy : 0.0012748241424560547 nb_pixel_total : 735 time to create 1 rle with old method : 0.0009260177612304688 time for calcul the mask position with numpy : 0.0012865066528320312 nb_pixel_total : 1634 time to create 1 rle with old method : 0.0019216537475585938 time for calcul the mask position with numpy : 0.0013880729675292969 nb_pixel_total : 1498 time to create 1 rle with old method : 0.0016536712646484375 time for calcul the mask position with numpy : 0.0014486312866210938 nb_pixel_total : 38920 time to create 1 rle with old method : 0.041539669036865234 time for calcul the mask position with numpy : 0.001420736312866211 nb_pixel_total : 7529 time to create 1 rle with old method : 0.00822901725769043 time for calcul the mask position with numpy : 0.0013651847839355469 nb_pixel_total : 1382 time to create 1 rle with old method : 0.0018062591552734375 time for calcul the mask position with numpy : 0.001390695571899414 nb_pixel_total : 912 time to create 1 rle with old method : 0.0011670589447021484 time for calcul the mask position with numpy : 0.0013866424560546875 nb_pixel_total : 299 time to create 1 rle with old method : 0.0004372596740722656 time for calcul the mask position with numpy : 0.0012857913970947266 nb_pixel_total : 2199 time to create 1 rle with old method : 0.002646207809448242 time for calcul the mask position with numpy : 0.0012733936309814453 nb_pixel_total : 481 time to create 1 rle with old method : 0.0005781650543212891 time for calcul the mask position with numpy : 0.0013647079467773438 nb_pixel_total : 1357 time to create 1 rle with old method : 0.0017611980438232422 time for calcul the mask position with numpy : 0.0012764930725097656 nb_pixel_total : 884 time to create 1 rle with old method : 0.0011184215545654297 time for calcul the mask position with numpy : 0.0013005733489990234 nb_pixel_total : 948 time to create 1 rle with old method : 0.0011281967163085938 time for calcul the mask position with numpy : 0.001470804214477539 nb_pixel_total : 5181 time to create 1 rle with old method : 0.005924701690673828 time for calcul the mask position with numpy : 0.001463174819946289 nb_pixel_total : 7401 time to create 1 rle with old method : 0.008716583251953125 time for calcul the mask position with numpy : 0.0013256072998046875 nb_pixel_total : 1614 time to create 1 rle with old method : 0.0020041465759277344 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 100 chid ids of type : 4677 Number RLEs to save : 9518 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975215841', '465', '201', '3') ... last line : ('3975215940', '280', '238', '18') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : sam we use saveGeneral [1189321094] map_info['map_portfolio_photo'] : {} final : True mtd_id 4573 list_pids : [1189321094] Looping around the photos to save general results len do output : 1 /1189321094Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4573', None, None, None, None, None, None, None, None) ('4573', None, '1189321094', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4573', None, '1189321094', 'None', None, None, None, None, None)] time used for this insertion : 0.012668848037719727 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.694583654403687 time spend to save output : 0.012956857681274414 total time spend for step 1 : 12.707540512084961 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1189321094': [[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], 'temp/1758812524_3157952_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png']} nb_objects detect : 100 ############################### TEST frcnn ################################ test frcnn Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4184 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4184 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4184 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4184 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : frcnn list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (917754606) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 917754606 download finish for photo 917754606 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.11708521842956543 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:frcnn Thu Sep 25 17:02:17 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812536_3157952_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1758812536_3157952_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Faster rcnn ! classes : ['background', 'plaque'] pht : 4370 caffemodel_name (should be vgg16_immat_307 but not used because net loaded outside in the fonction) : {'id': 3375, 'mtr_user_id': 31, 'name': 'detection_plaque_valcor_010622', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,plaque', 'svm_portfolios_learning': '0,0', 'photo_hashtag_type': 4370, 'photo_desc_type': 5676, 'type_classification': 'caffe_faster_rcnn', 'hashtag_id_list': '0,0'} To loadFromThcl() model_param file didn't exist model_name : detection_plaque_valcor_010622 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] local folder : /data/models_weight/detection_plaque_valcor_010622 /data/models_weight/detection_plaque_valcor_010622/caffemodel size_local : 349723073 size in s3 : 349723073 create time local : 2022-07-12 14:12:27 create time in s3 : 2022-06-01 15:05:56 caffemodel already exist and didn't need to update /data/models_weight/detection_plaque_valcor_010622/test.prototxt size_local : 7163 size in s3 : 7163 create time local : 2022-07-12 14:12:27 create time in s3 : 2022-06-01 15:05:55 test.prototxt already exist and didn't need to update prototxt : /data/models_weight/detection_plaque_valcor_010622/test.prototxt caffemodel : /data/models_weight/detection_plaque_valcor_010622/caffemodel Loaded network /data/models_weight/detection_plaque_valcor_010622/caffemodel About to compute detect_faster_rcnn : len(args) : 1 Inside frcnn step exec : nb paths : 1 image_path : temp/1758812536_3157952_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg image_size (600, 800, 3) [[[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] [[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] [[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] ... [[ 14 16 16] [ 13 15 15] [ 11 13 13] ... [198 206 205] [198 206 205] [198 206 205]] [[ 16 18 18] [ 14 16 16] [ 11 13 13] ... [206 214 213] [206 214 213] [206 214 213]] [[ 13 15 15] [ 12 14 14] [ 9 11 11] ... [210 218 217] [210 218 217] [210 218 217]]] Detection took 0.067s for 300 object proposals c : plaque list_crops.shape (72, 5) proba : 0.06384136 (374.12704, 293.91928, 430.8104, 317.80862) proba : 0.052222475 (382.17575, 297.18918, 552.3567, 344.65854) proba : 0.012272149 (345.35733, 272.42902, 468.8572, 320.7237) We are managing local photo_id len de result frcnn : 1 After datou_step_exec type output : time spend for datou_step_exec : 2.1985721588134766 time spend to save output : 0.00011420249938964844 total time spend for step 1 : 2.198686361312866 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True Inside saveFrcnn : final : True verbose : True threshold to save the result : 0.1 output flattener : [(0, 493029425, 4370, 374, 430, 293, 317, 0.06384136, None), (0, 493029425, 4370, 382, 552, 297, 344, 0.052222475, None), (0, 493029425, 4370, 345, 468, 272, 320, 0.012272149, None)] Warning : no hashtag_ids to insert in the database final : True begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4184', None, '917754606', '0', 0, '0', 493061979, '0', None)] time used for this insertion : 0.010930538177490234 [917754606] map_info['map_portfolio_photo'] : {} final : True mtd_id 4184 list_pids : [917754606] Looping around the photos to save general results len do output : 1 /0 before output type Managing all output in save final without adding information in the mtr_datou_result ('4184', None, None, None, None, None, None, None, None) ('4184', None, '917754606', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4184', None, '917754606', None, None, None, None, None, None)] time used for this insertion : 0.010944366455078125 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {0: [[(0, 493029425, 4370, 374, 430, 293, 317, 0.06384136, None), (0, 493029425, 4370, 382, 552, 297, 344, 0.052222475, None), (0, 493029425, 4370, 345, 468, 272, 320, 0.012272149, None)], 'temp/1758812536_3157952_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg']} ############################### TEST thcl ################################ TEST THCL Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 1 thcl is not linked in the step_by_step architecture ! WARNING : step 2 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : thcl, argmax list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (916235064) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 916235064 download finish for photo 916235064 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.09464788436889648 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 2 step1:thcl Thu Sep 25 17:02:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg': 916235064} map_photo_id_path_extension : {916235064: {'path': 'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Thcl ! multi_thcl or not :False multi_thcl_cond or not :False dic_thcl : {'355': 1} we are using the classfication for only one thcl 355 In convert_file_to_np l 337 : 1 l343 1 l357 after caffe.io.load_image dimension du image : (3, (66, 66, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.009735822677612305 time to convert the images to numpy array : 0.0024209022521972656 total time to convert the images to numpy array : 0.012501239776611328 list photo_ids error: [] list photo_ids correct : [916235064] number of photos to traite : 1 try to delete the photos incorrect in DB tagging for thcl : 355 To do loadFromThcl(), then load ParamDescType : thcl355 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (355) thcls : [{'id': 355, 'mtr_user_id': 31, 'name': 'car_360_1027', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 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'svm_portfolios_learning': 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'svm_portfolios_learning': '506302,506374,506399,506192,506205,506350,506052,506295,506066,506117,506065,506125,506387,506381,506349,506328,506377,506286,506124,506172,506206,506178,506371,506076,506114,506329,506122,506220,506174,506224,506232,506234,506173,506181,506323,506326,506376,506048,506400,506179,506311,506325,506402,506051,506294,506318,506303,506175,506099,506061,506337,506250,506082,506166,506133,506308,506078,506340,506310,506100,506121,506070,506218,506227,506272,506147,506160,506265,506202,506222,506093,506257,506208,506344,506077,506395,506094,506219,506298,506339,506343,506365,506200,506348,506198,506385,506239,506236,506391,506087,506342,506149,506184,506393,506203,506280,506216,506403,506355,506332,506259,506401,506357,506324,506098,506315,506335,506088,506046,506185,506171,506080,506345,506347,506067,506233,506225,506312,506278,506300,506258,506182,506226,506262,506146,506113,506108,506297,506322,506143,506363,506073,506154,506313,506189,506197,506162,506249,506139,506237,506336,506084,506109,506106,506045,506392,506247,506316,506201,506353,506305,506050,506145,506362,506101,506128,506044,506317,506074,506134,506196,506194,506285,506177,506240,506282,506396,506281,506264,506276,506144,506069,506091,506081,506168,506291,506238,506072,506085,506235,506193,506268,506148,506356,506386,506229,506256,506187,506110,506304,506115,506214,506334,506289,506361,506366,506204,506190,506188,506307,506055,506389,506364,506279,506241,506057,506063,506320,506212,506263,506394,506306,506260,506309,506221,506155,506176,506398,506360,506210,506341,506209,506170,506097,506119,506163,506092,506267,506246,506047,506296,506058,506269,506378,506123,506271,506277,506207,506141,506390,506314,506299,506075,506183,506157,506228,506255,506358,506053,506060,506382,506217,506290,506230,506186,506213,506248,506354,506245,506104,506111,506054,506068,506156,506102,506191,506158,506159,506153,506107,506056,506131,506165,506370,506161,506242,506327,506253,506330,506243,506231,506096,506331,506062,506195,506369,506384,506071,506116,506164,506090,506397,506273,506338,506140,506136,506086,506083,506275,506283,506142,506383,506380,506129,506368,506130,506367,506292,506064,506138,506167,506223,506351,506079,506132,506293,506089,506095,506120,506388,506211,506274,506321,506150,506169,506049,506379,506252,506112,506199,506287,506266,506118,506103,506301,506105,506137,506352,506333,506180,506254,506375,506270,506319,506288,506244,506284,506059,506261,506372,506127,506359,506135,506215,506151,506251,506152,506126,506373,506346', 'photo_hashtag_type': 332, 'photo_desc_type': 3390, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3390 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (3390) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3390, 'car_360_1027', 16384, 25088, 'car_360_1027', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2017, 10, 28, 12, 29, 27), datetime.datetime(2017, 10, 28, 12, 29, 27)) To loadFromThcl() : net_3390 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 6482 max_wait_temp : 1 max_wait : 0 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (3390) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3390, 'car_360_1027', 16384, 25088, 'car_360_1027', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2017, 10, 28, 12, 29, 27), datetime.datetime(2017, 10, 28, 12, 29, 27)) param : , param.caffemodel : car_360_1027 None mean_file_type : mean_file_path : prototxt_file_path : model : car_360_1027 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : car_360_1027 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : [] local folder : /data/models_weight/car_360_1027 /data/models_weight/car_360_1027/caffemodel size_local : 542944640 size in s3 : 542944640 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 caffemodel already exist and didn't need to update /data/models_weight/car_360_1027/deploy_conv_normal.prototxt size_local : 4626 size in s3 : 4626 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:42 deploy_conv_normal.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/deploy_fc.prototxt size_local : 1132 size in s3 : 1132 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 deploy_fc.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/deploy.prototxt size_local : 5654 size in s3 : 5654 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:42 deploy.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/mean.npy size_local : 1572944 size in s3 : 1572944 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:55 mean.npy already exist and didn't need to update /data/models_weight/car_360_1027/synset_words.txt size_local : 13687 size in s3 : 13687 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/caffe_cuda8_python3/python/:/home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/:/home/admin/workarea/git/apy/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/car_360_1027/deploy.prototxt caffemodel_filename : /data/models_weight/car_360_1027/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 6482 max_wait_temp : 1 max_wait : 0 dict_keys(['prob', 'pool5']) time used to do the prepocess of the images : 0.01370549201965332 time used to do the prediction : 0.10230517387390137 save descriptor for thcl : 355 (1, 512, 7, 7) Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] code_as_byte_string:b'0000000000'| time to traite the descriptors : 0.04834580421447754 Testing : ['916235064'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (916235064) result : {916235064: {'photo_id': 916235064, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2017/10/14/6293d1bb790dc6902450e7c572b7d10b.jpg', 'latitude': None, 'longitude': None, 'text': None}} list_photo_exists : [916235064] storage_type for insertDescriptorsMulti : 1 To insert : 916235064 time to insert the descriptors : 0.9625506401062012 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : False verbose : True time used to find the portfolios of the photos select button_legend_list from MTRDatou.classification_theme where id = 355 SAVE THCL, output : {'916235064': [[('916235064', 'c_elysee_1027_gao__port_506302', 0.0018815164, 332, '355'), ('916235064', 'mokka_1027_gao__port_506374', 0.0011634813, 332, '355'), ('916235064', 'captur_1027_gao__port_506399', 0.0008157271, 332, '355'), ('916235064', 'sorento_1027_gao__port_506192', 0.0011772988, 332, '355'), ('916235064', 'navara_1027_gao__port_506205', 0.0025849883, 332, '355'), ('916235064', 'xc90_1027_gao__port_506350', 0.004170529, 332, '355'), ('916235064', 'saxo_1027_gao__port_506052', 0.0034805161, 332, '355'), ('916235064', 'trafic_1027_gao__port_506295', 0.007366604, 332, '355'), ('916235064', 'punto_evo_1027_gao__port_506066', 0.0021886276, 332, '355'), ('916235064', '5_1027_gao__port_506117', 0.0005798397, 332, '355'), ('916235064', '250_1027_gao__port_506065', 0.0045915786, 332, '355'), ('916235064', 'd_max_1027_gao__port_506125', 0.0031587493, 332, '355'), ('916235064', 'panamera_1027_gao__port_506387', 0.0022509627, 332, '355'), ('916235064', 'alhambra_1027_gao__port_506381', 0.005320613, 332, '355'), ('916235064', 'x6_1027_gao__port_506349', 0.001099971, 332, '355'), ('916235064', 'vitara_1027_gao__port_506328', 0.005402275, 332, '355'), ('916235064', 'fiesta_1027_gao__port_506377', 0.00391897, 332, '355'), ('916235064', 'qashqai_1027_gao__port_506286', 0.0014786797, 332, '355'), ('916235064', '147_1027_gao__port_506124', 0.0019777594, 332, '355'), ('916235064', 'c5_1027_gao__port_506172', 0.0012442262, 332, '355'), ('916235064', 'q5_1027_gao__port_506206', 0.001505087, 332, '355'), ('916235064', 'giulia_1027_gao__port_506178', 0.0021693707, 332, '355'), ('916235064', 'karl_1027_gao__port_506371', 0.0027079678, 332, '355'), ('916235064', 'mehari_1027_gao__port_506076', 0.004703737, 332, '355'), ('916235064', '911_1027_gao__port_506114', 0.0019418272, 332, '355'), ('916235064', '508_1027_gao__port_506329', 0.0009585791, 332, '355'), ('916235064', 'idea_1027_gao__port_506122', 0.00076999166, 332, '355'), ('916235064', 'megane_1027_gao__port_506220', 0.0019469428, 332, '355'), ('916235064', 'ghibli_1027_gao__port_506174', 0.0013726088, 332, '355'), ('916235064', 'touareg_1027_gao__port_506224', 0.0016202629, 332, '355'), ('916235064', 'i10_1027_gao__port_506232', 0.0013923667, 332, '355'), ('916235064', 'jumper_1027_gao__port_506234', 0.010044211, 332, '355'), ('916235064', 'classe_clk_1027_gao__port_506173', 0.0010793429, 332, '355'), ('916235064', 'kuga_1027_gao__port_506181', 0.0008447221, 332, '355'), ('916235064', 'ct_1027_gao__port_506323', 0.0012521306, 332, '355'), ('916235064', 'leon_1027_gao__port_506326', 0.0025844458, 332, '355'), ('916235064', 'ds5_1027_gao__port_506376', 0.0012429982, 332, '355'), ('916235064', 'cordoba_1027_gao__port_506048', 0.0028649531, 332, '355'), ('916235064', 'classe_cla_1027_gao__port_506400', 0.0012949159, 332, '355'), ('916235064', 'jumpy_1027_gao__port_506179', 0.010338958, 332, '355'), ('916235064', 'avensis_1027_gao__port_506311', 0.0018767011, 332, '355'), ('916235064', 'juke_1027_gao__port_506325', 0.0011342593, 332, '355'), ('916235064', '4008_1027_gao__port_506402', 0.0015757589, 332, '355'), ('916235064', '190_series_1027_gao__port_506051', 0.0039805747, 332, '355'), ('916235064', 'serie_3_1027_gao__port_506294', 0.0028742915, 332, '355'), ('916235064', 'q7_1027_gao__port_506318', 0.002335653, 332, '355'), ('916235064', 'glc_1027_gao__port_506303', 0.0012107063, 332, '355'), ('916235064', 'grand_vitara_1027_gao__port_506175', 0.0011447765, 332, '355'), ('916235064', 's40_1027_gao__port_506099', 0.002233946, 332, '355'), ('916235064', 'toledo_1027_gao__port_506061', 0.0017464602, 332, '355'), ('916235064', '5008_1027_gao__port_506337', 0.004699432, 332, '355'), ('916235064', 'continental_1027_gao__port_506250', 0.0021914102, 332, '355'), ('916235064', 'coupe_1027_gao__port_506082', 0.0022631288, 332, '355'), ('916235064', 'iq_1027_gao__port_506166', 0.0018173356, 332, '355'), ('916235064', '407_1027_gao__port_506133', 0.0009056542, 332, '355'), ('916235064', 'touran_1027_gao__port_506308', 0.00204025, 332, '355'), ('916235064', '300c_1027_gao__port_506078', 0.0025338517, 332, '355'), ('916235064', 'classe_gl_1027_gao__port_506340', 0.0044893376, 332, '355'), ('916235064', 'vivaro_1027_gao__port_506310', 0.0034251139, 332, '355'), ('916235064', 'sl_1027_gao__port_506100', 0.0031354786, 332, '355'), ('916235064', 'elise_1027_gao__port_506121', 0.0010255439, 332, '355'), ('916235064', '1007_1027_gao__port_506070', 0.0015352418, 332, '355'), ('916235064', 'i40_1027_gao__port_506218', 0.0005915167, 332, '355'), ('916235064', 'bipper_tepee_1027_gao__port_506227', 0.00402901, 332, '355'), ('916235064', 'focus_1027_gao__port_506272', 0.0011586249, 332, '355'), ('916235064', 'primera_1027_gao__port_506147', 0.0012157593, 332, '355'), ('916235064', 'r4_1027_gao__port_506160', 0.014967937, 332, '355'), ('916235064', 'a8_1027_gao__port_506265', 0.0011321114, 332, '355'), ('916235064', 'boxer_1027_gao__port_506202', 0.01054529, 332, '355'), ('916235064', 's5_1027_gao__port_506222', 0.0011985251, 332, '355'), ('916235064', 'r21_1027_gao__port_506093', 0.0041857604, 332, '355'), ('916235064', 'c3_1027_gao__port_506257', 0.002363374, 332, '355'), ('916235064', 'santa_fe_1027_gao__port_506208', 0.0016322985, 332, '355'), ('916235064', 'm4_1027_gao__port_506344', 0.0015568744, 332, '355'), ('916235064', 'safrane_1027_gao__port_506077', 0.0013959269, 332, '355'), ('916235064', 'classe_gle_1027_gao__port_506395', 0.0021981127, 332, '355'), ('916235064', '0_1027_gao__port_506094', 0.008828065, 332, '355'), ('916235064', 'ix35_1027_gao__port_506219', 0.0014615454, 332, '355'), ('916235064', 'carens_1027_gao__port_506298', 0.00088251906, 332, '355'), ('916235064', 'classe_a_1027_gao__port_506339', 0.0024712668, 332, '355'), ('916235064', 'ix20_1027_gao__port_506343', 0.0010092319, 332, '355'), ('916235064', 'note_1027_gao__port_506365', 0.0015961863, 332, '355'), ('916235064', 'a5_1027_gao__port_506200', 0.0015330919, 332, '355'), ('916235064', 'sx4_1027_gao__port_506348', 0.001491682, 332, '355'), ('916235064', 'sandero_1027_gao__port_506198', 0.0014584345, 332, '355'), ('916235064', '3008_1027_gao__port_506385', 0.0056455615, 332, '355'), ('916235064', 'q50_1027_gao__port_506239', 0.0011164942, 332, '355'), ('916235064', 'latitude_1027_gao__port_506236', 0.00080195384, 332, '355'), ('916235064', 'v40_1027_gao__port_506391', 0.0017146395, 332, '355'), ('916235064', 'xsara_1027_gao__port_506087', 0.0009823155, 332, '355'), ('916235064', 'grand_c_max_1027_gao__port_506342', 0.0017958323, 332, '355'), ('916235064', 'swift_1027_gao__port_506149', 0.0015020453, 332, '355'), ('916235064', 'serie_1_1027_gao__port_506184', 0.0015139929, 332, '355'), ('916235064', 'xc70_1027_gao__port_506393', 0.0036194457, 332, '355'), ('916235064', 'master_1027_gao__port_506203', 0.007957198, 332, 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'200_1027_gao__port_506112', 0.004087379, 332, '355'), ('916235064', 'tts_1027_gao__port_506199', 0.0011862477, 332, '355'), ('916235064', 'zafira_1027_gao__port_506287', 0.0026953344, 332, '355'), ('916235064', 'asx_1027_gao__port_506266', 0.0011406933, 332, '355'), ('916235064', '607_1027_gao__port_506118', 0.0012529035, 332, '355'), ('916235064', '207_1027_gao__port_506103', 0.0015147844, 332, '355'), ('916235064', 'classe_s_1027_gao__port_506301', 0.0031657298, 332, '355'), ('916235064', 'c6_1027_gao__port_506105', 0.0017348807, 332, '355'), ('916235064', 'express_1027_gao__port_506137', 0.016726607, 332, '355'), ('916235064', 'classe_gla_1027_gao__port_506352', 0.0018255183, 332, '355'), ('916235064', 'v60_1027_gao__port_506333', 0.0021460282, 332, '355'), ('916235064', 'ka_1027_gao__port_506180', 0.0014151062, 332, '355'), ('916235064', 'range_rover_1027_gao__port_506254', 0.0020553332, 332, '355'), ('916235064', 'discovery_1027_gao__port_506375', 0.002296645, 332, '355'), ('916235064', 'classe_r_1027_gao__port_506270', 0.0013944855, 332, '355'), ('916235064', 'transporter_1027_gao__port_506319', 0.011968561, 332, '355'), ('916235064', 'cee_d_1027_gao__port_506288', 0.0010548317, 332, '355'), ('916235064', 'zoe_1027_gao__port_506244', 0.0020713683, 332, '355'), ('916235064', 'i20_1027_gao__port_506284', 0.001786877, 332, '355'), ('916235064', 'gtv_1027_gao__port_506059', 0.0057225223, 332, '355'), ('916235064', 's4_avant_1027_gao__port_506261', 0.0027666143, 332, '355'), ('916235064', 'x1_1027_gao__port_506372', 0.0017145388, 332, '355'), ('916235064', 'autres_1027_gao__port_506127', 0.0048256125, 332, '355'), ('916235064', '208_1027_gao__port_506359', 0.0018686805, 332, '355'), ('916235064', 'c8_1027_gao__port_506135', 0.0012580121, 332, '355'), ('916235064', 'astra_1027_gao__port_506215', 0.0012625575, 332, '355'), ('916235064', '2_1027_gao__port_506151', 0.00092446886, 332, '355'), ('916235064', 'doblo_1027_gao__port_506251', 0.0074660587, 332, '355'), ('916235064', '807_1027_gao__port_506152', 0.0007290324, 332, '355'), ('916235064', '206_1027_gao__port_506126', 0.0010384974, 332, '355'), ('916235064', 'a7_1027_gao__port_506373', 0.00069118204, 332, '355'), ('916235064', 'renegade_1027_gao__port_506346', 0.002141655, 332, '355')]]} begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 0 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 5.0067901611328125e-06 save missing photos in datou_result : time spend for datou_step_exec : 6.226062059402466 time spend to save output : 1.4580881595611572 total time spend for step 1 : 7.684150218963623 step2:argmax Thu Sep 25 17:02:27 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg': 916235064} map_photo_id_path_extension : {916235064: {'path': 'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! calculate argmax for thcl : 355 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : True verbose : True photo_id : 916235064 output[photo_id] : [('916235064', 'c15_1027_gao__port_506055', 0.017713847, 332, '355'), 'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) first line : ('916235064', '2049863950', '332') ... last line : ('916235064', '2049863950', '332') time used for this insertion : 0.008673906326293945 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 0.012003183364868164 len list_finale : 1, len picture : 1 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('2', None, '916235064', 'c15_1027_gao__port_506055', None, None, '2049863950', '0.017713847', None)] time used for this insertion : 0.010900259017944336 saving photo_ids in datou_result photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [] time used for this insertion : 3.814697265625e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.0001919269561767578 time spend to save output : 0.032000064849853516 total time spend for step 2 : 0.03219199180603027 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'916235064': [('916235064', 'c15_1027_gao__port_506055', 0.017713847, 332, '355'), 'temp/1758812539_3157952_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg']} ############################### TEST tfhub2 ################################ TEST TFHUB2 ######################## test with use_multi_inputs=0 ######################## Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4567 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4567 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4567 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4567 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 12835 tfhub_classification2 is not linked in the step_by_step architecture ! WARNING : step 12836 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (1171252784,1171252764,1171252487) Found this number of photos: 3 ##### Call download_photos : nb_thread : 5 begin to download photo : 1171252487 begin to download photo : 1171252764 begin to download photo : 1171252784 download finish for photo 1171252784 download finish for photo 1171252487 download finish for photo 1171252764 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 ##### After load_data_input time to download the photos : 0.19588208198547363 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 2 step1:tfhub_classification2 Thu Sep 25 17:02:27 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg': 1171252784, 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg': 1171252487, 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg': 1171252764} map_photo_id_path_extension : {1171252784: {'path': 'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg', 'extension': 'jpg'}, 1171252487: {'path': 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg', 'extension': 'jpg'}, 1171252764: {'path': 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step TFHub with tf2 ! multi_thcl or not :False multi_thcl_cond or not :False dic_thcl : {'3609': 1} we are using the classfication for only one thcl 3609 begin to check gpu status inside check gpu memory 2025-09-25 17:02:31.048871: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-25 17:02:31.050578: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-25 17:02:31.050771: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-25 17:02:31.050834: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-25 17:02:31.064100: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-25 17:02:31.064320: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-25 17:02:31.070891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-25 17:02:31.073283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-25 17:02:31.088143: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-25 17:02:31.089583: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-25 17:02:31.090136: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-25 17:02:31.124821: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-25 17:02:31.126534: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f5084000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-25 17:02:31.126576: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-25 17:02:31.131207: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7d0c7210 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-25 17:02:31.131240: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-25 17:02:31.132217: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-25 17:02:31.132375: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-25 17:02:31.132412: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-25 17:02:31.132526: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-25 17:02:31.132567: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-25 17:02:31.132620: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-25 17:02:31.132676: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-25 17:02:31.132732: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-25 17:02:31.134132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-25 17:02:31.134510: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-25 17:02:31.134555: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-25 17:02:31.134571: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-25 17:02:31.134583: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-25 17:02:31.136089: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3096 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) l 3637 free memory gpu now : 6482 max_wait_temp : 1 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3609 To do loadFromThcl(), then load ParamDescType : thcl3609 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (3609) thcls : [{'id': 3609, 'mtr_user_id': 31, 'name': 'tfhub_19_06_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'jrm,pcm,pcnc,pehd,tapis_vide', 'svm_portfolios_learning': '9336903,9336904,9336905,9336906,9336909', 'photo_hashtag_type': 4674, 'photo_desc_type': 5832, 'type_classification': 'tf_classification2', 'hashtag_id_list': '495916461,560181804,1284539308,628944319,2107748999'}] thcl {'id': 3609, 'mtr_user_id': 31, 'name': 'tfhub_19_06_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'jrm,pcm,pcnc,pehd,tapis_vide', 'svm_portfolios_learning': '9336903,9336904,9336905,9336906,9336909', 'photo_hashtag_type': 4674, 'photo_desc_type': 5832, 'type_classification': 'tf_classification2', 'hashtag_id_list': '495916461,560181804,1284539308,628944319,2107748999'} Update svm_hashtag_type_desc : 5832 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (5832) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5832, 'tfhub_19_06_2023', 1280, 1280, 'tfhub_19_06_2023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 6, 19, 12, 55, 22), datetime.datetime(2023, 6, 19, 12, 55, 22)) model_name : tfhub_19_06_2023 model_param file didn't exist model_name : tfhub_19_06_2023 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] /home/admin/workarea/git/Velours/python/tests/python_tests.py:11: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses import imp Traceback (most recent call last): File "/home/admin/workarea/git/Velours/python/tests/python_tests.py", line 245, in v, r = module_name.test(verbose=verbose, context=context) File "/home/admin/workarea/git/Velours/python/tests/mask_test.py", line 264, in test title2, result2, res_bool2 = test_detect_objet(context, verbose) TypeError: cannot unpack non-iterable NoneType object File "/home/admin/workarea/git/Velours/python/tests/python_tests.py", line 251, in traceback.print_stack() /home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python/../../tools/../lib/rpn/proposal_layer.py:28: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. layer_params = yaml.load(self.param_str_) local folder : /data/models_weight/tfhub_19_06_2023 /data/models_weight/tfhub_19_06_2023/Confusion_Matrix.png size_local : 57753 size in s3 : 57753 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:15 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_jrm.jpg size_local : 79724 size in s3 : 79724 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pcm.jpg size_local : 83556 size in s3 : 83556 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:15 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pcnc.jpg size_local : 74107 size in s3 : 74107 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pehd.jpg size_local : 72705 size in s3 : 72705 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_pehd.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_tapis_vide.jpg size_local : 70874 size in s3 : 70874 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:15 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Result_Summary.txt size_local : 642 size in s3 : 642 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 Result_Summary.txt already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 checkpoint already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216488 size in s3 : 216488 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279708 size in s3 : 32279708 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:21 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:22 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_weights.h5 size_local : 16499144 size in s3 : 16499144 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:15 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ tfhub_19_06_2023dense (Dense (None, 5) 6405 ================================================================= Total params: 4,055,969 Trainable params: 6,405 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 11.172670602798462 time used to load_weights : 0.17142701148986816 0it [00:00, ?it/s] 3it [00:00, 1100.67it/s]2025-09-25 17:02:45.090403: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg Found 3 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 3.2237977981567383 ['temp/image000000000_1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg', 'temp/image000000001_1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg', 'temp/image000000002_1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg'] (3,) (3, 5) (3, 1280) shape of features : (3, 1280) shape of new features : (1, 3, 1280) save descriptor for thcl : 3609 (3, 1280) Got the blobs of the net to insert : [0, 6, 0, 0, 1, 0, 0, 1, 0, 0] code_as_byte_string:b'0006000001'| Got the blobs of the net to insert : [0, 9, 0, 0, 0, 0, 1, 0, 0, 0] code_as_byte_string:b'0009000000'| Got the blobs of the net to insert : [0, 6, 0, 1, 0, 0, 0, 1, 0, 0] code_as_byte_string:b'0006000100'| time to traite the descriptors : 0.023780345916748047 Testing : ['1171252784', '1171252487', '1171252764'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (1171252784,1171252487,1171252764) result : {1171252487: {'photo_id': 1171252487, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/22/5ebdd6b0a6bb39942a3808ed114806de.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_21_55_35_005998m0.jpg 0.4259977941513062 for time 6.000020980834961, id_amount 3 this amount prod time diff : 0.006000020980834961'}, 1171252764: {'photo_id': 1171252764, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/22/29d5179a892cc50aadc9d67245534b59.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_21_55_41_005998m0.jpg 0.4319977941513062 for time 6.0, id_amount 3 this amount prod time diff : 0.006'}, 1171252784: {'photo_id': 1171252784, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/22/5a3c5d3bb155a7a116f67ded51bffb59.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_21_55_47_006033m0.jpg 0.4379978291988373 for time 6.000035047531128, id_amount 4 this amount prod time diff : 0.006000035047531128'}} list_photo_exists : [1171252487, 1171252764, 1171252784] storage_type for insertDescriptorsMulti : 3 To insert : 1171252784 To insert : 1171252487 To insert : 1171252764 time to insert the descriptors : 1.4414279460906982 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : False verbose : True saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1171252784, 1171252487, 1171252764] map_info['map_portfolio_photo'] : {} final : False mtd_id 4567 list_pids : [1171252784, 1171252487, 1171252764] Looping around the photos to save general results len do output : 3 /1171252784Didn't retrieve data . /1171252487Didn't retrieve data . /1171252764Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252784', None, None, None, None, None, None) ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252487', None, None, None, None, None, None) ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252764', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4567', None, '1171252784', 'None', None, None, None, None, None), ('4567', None, '1171252487', 'None', None, None, None, None, None), ('4567', None, '1171252764', 'None', None, None, None, None, None)] time used for this insertion : 0.011659622192382812 save_final save missing photos in datou_result : time spend for datou_step_exec : 22.36698865890503 time spend to save output : 0.011914730072021484 total time spend for step 1 : 22.37890338897705 step2:argmax Thu Sep 25 17:02:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg': 1171252784, 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg': 1171252487, 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg': 1171252764} map_photo_id_path_extension : {1171252784: {'path': 'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg', 'extension': 'jpg'}, 1171252487: {'path': 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg', 'extension': 'jpg'}, 1171252764: {'path': 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! calculate argmax for thcl : 3609 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : True verbose : True photo_id : 1171252784 output[photo_id] : [(1171252784, 'jrm', 0.9677411, 4674, '3609'), 'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg'] photo_id : 1171252487 output[photo_id] : [(1171252487, 'jrm', 0.92623633, 4674, '3609'), 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg'] photo_id : 1171252764 output[photo_id] : [(1171252764, 'jrm', 0.9853564, 4674, '3609'), 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) first line : ('1171252784', '495916461', '4674') ... last line : ('1171252764', '495916461', '4674') time used for this insertion : 0.007857322692871094 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 3 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 0.010957956314086914 len list_finale : 3, len picture : 3 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4567', None, '1171252784', 'jrm', None, None, '495916461', '0.9677411', None), ('4567', None, '1171252487', 'jrm', None, None, '495916461', '0.92623633', None), ('4567', None, '1171252764', 'jrm', None, None, '495916461', '0.9853564', None)] time used for this insertion : 0.011893510818481445 saving photo_ids in datou_result photo id not in port photo id not in port photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [] time used for this insertion : 2.6226043701171875e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.00013828277587890625 time spend to save output : 0.03474760055541992 total time spend for step 2 : 0.03488588333129883 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'1171252784': [(1171252784, 'jrm', 0.9677411, 4674, '3609'), 'temp/1758812547_3157952_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg'], '1171252487': [(1171252487, 'jrm', 0.92623633, 4674, '3609'), 'temp/1758812547_3157952_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg'], '1171252764': [(1171252764, 'jrm', 0.9853564, 4674, '3609'), 'temp/1758812547_3157952_1171252764_29d5179a892cc50aadc9d67245534b59.jpg']} --------------------- test with use_multi_inputs=0 is succeded ------------------- ######################## test with use_multi_inputs=1 ######################## Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4621 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4621 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4621 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4621 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 12927 tfhub_classification2 is not linked in the step_by_step architecture ! WARNING : step 12928 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (1171291875,1171275372,1171275314) Found this number of photos: 3 ##### Call download_photos : nb_thread : 5 begin to download photo : 1171275314 begin to download photo : 1171275372 begin to download photo : 1171291875 download finish for photo 1171291875 download finish for photo 1171275314 download finish for photo 1171275372 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 ##### After load_data_input time to download the photos : 0.24254894256591797 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 2 step1:tfhub_classification2 Thu Sep 25 17:02:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg': 1171291875, 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg': 1171275314, 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg': 1171275372} map_photo_id_path_extension : {1171291875: {'path': 'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg', 'extension': 'jpg'}, 1171275314: {'path': 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg', 'extension': 'jpg'}, 1171275372: {'path': 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step TFHub with tf2 ! multi_thcl or not :False multi_thcl_cond or not :False dic_thcl : {'3655': 1} we are using the classfication for only one thcl 3655 begin to check gpu status inside check gpu memory inside check gpu memory inside check gpu memory inside check gpu memory inside check gpu memory inside check gpu memory l 3637 free memory gpu now : 2930 max_wait_temp : 6 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3655 To do loadFromThcl(), then load ParamDescType : thcl3655 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (3655) thcls : [{'id': 3655, 'mtr_user_id': 31, 'name': 'tfhub_18_7_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'pcm,pcnc,jrm,pehd,tapis_vide', 'svm_portfolios_learning': '9336904,9336905,9336903,9336906,9336909', 'photo_hashtag_type': 4723, 'photo_desc_type': 5862, 'type_classification': 'tf_classification2', 'hashtag_id_list': '560181804,1284539308,495916461,628944319,2107748999'}] thcl {'id': 3655, 'mtr_user_id': 31, 'name': 'tfhub_18_7_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'pcm,pcnc,jrm,pehd,tapis_vide', 'svm_portfolios_learning': '9336904,9336905,9336903,9336906,9336909', 'photo_hashtag_type': 4723, 'photo_desc_type': 5862, 'type_classification': 'tf_classification2', 'hashtag_id_list': '560181804,1284539308,495916461,628944319,2107748999'} Update svm_hashtag_type_desc : 5862 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (5862) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5862, 'tfhub_18_7_2023', 1280, 1280, 'tfhub_18_7_2023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 7, 18, 22, 46, 29), datetime.datetime(2023, 7, 18, 22, 46, 29)) model_name : tfhub_18_7_2023 model_param file didn't exist model_name : tfhub_18_7_2023 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/tfhub_18_7_2023 /data/models_weight/tfhub_18_7_2023/Confusion_Matrix.png size_local : 54360 size in s3 : 54360 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:28 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_jrm.jpg size_local : 72583 size in s3 : 72583 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pcm.jpg size_local : 81681 size in s3 : 81681 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:17 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pcnc.jpg size_local : 79510 size in s3 : 79510 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pehd.jpg size_local : 59936 size in s3 : 59936 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_pehd.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_tapis_vide.jpg size_local : 78974 size in s3 : 78974 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:17 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Result_Summary.txt size_local : 642 size in s3 : 642 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 Result_Summary.txt already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 checkpoint already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216529 size in s3 : 216529 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:17 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279748 size in s3 : 32279748 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:19 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:19 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_weights.h5 size_local : 16500868 size in s3 : 16500868 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:18 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "model" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) [(None, 224, 224, 3) 0 __________________________________________________________________________________________________ input_2 (InputLayer) [(None, 1)] 0 __________________________________________________________________________________________________ module (KerasLayer) (None, 1280) 4049564 input_1[0][0] __________________________________________________________________________________________________ concatenate (Concatenate) (None, 1281) 0 input_2[0][0] module[0][0] __________________________________________________________________________________________________ tfhub_18_7_2023dense (Dense) (None, 5) 6410 concatenate[0][0] ================================================================================================== Total params: 4,055,974 Trainable params: 0 Non-trainable params: 4,055,974 __________________________________________________________________________________________________ Loading Weights... time used to create the model : 7.1503746509552 time used to load_weights : 0.14027833938598633 found 3 data found 0 labels begin to do the prediction : time used to do the prediction : 1.0367352962493896 ['temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg', 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg', 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg'] (3,) (3, 5) (3, 1280) shape of features : (3, 1280) shape of new features : (1, 3, 1280) save descriptor for thcl : 3655 (3, 1280) Got the blobs of the net to insert : [0, 1, 0, 0, 11, 0, 2, 2, 0, 0] code_as_byte_string:b'000100000b'| Got the blobs of the net to insert : [0, 0, 0, 0, 8, 0, 0, 0, 3, 0] code_as_byte_string:b'0000000008'| Got the blobs of the net to insert : [0, 0, 0, 0, 14, 0, 1, 4, 0, 0] code_as_byte_string:b'000000000e'| time to traite the descriptors : 0.03746986389160156 Testing : ['1171291875', '1171275314', '1171275372'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (1171291875,1171275314,1171275372) result : {1171275314: {'photo_id': 1171275314, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/23/6e0a72c8fa00d5e4b018bd689b547133.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_23_54_22_6187.jpg'}, 1171275372: {'photo_id': 1171275372, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/23/76d81364ff7df843bff095f45c07ba35.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_23_56_46_6098.jpg'}, 1171291875: {'photo_id': 1171291875, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2023/2/23/b62cd9e0d976b143f86fe82d072798c0.jpg', 'latitude': None, 'longitude': None, 'text': 'image_22022023_23_59_04_5803.jpg'}} list_photo_exists : [1171275314, 1171275372, 1171291875] storage_type for insertDescriptorsMulti : 3 To insert : 1171291875 To insert : 1171275314 To insert : 1171275372 time to insert the descriptors : 0.7584226131439209 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : False verbose : True saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1171291875, 1171275314, 1171275372] map_info['map_portfolio_photo'] : {} final : False mtd_id 4621 list_pids : [1171291875, 1171275314, 1171275372] Looping around the photos to save general results len do output : 3 /1171291875Didn't retrieve data . /1171275314Didn't retrieve data . /1171275372Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171291875', None, None, None, None, None, None) ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171275314', None, None, None, None, None, None) ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171275372', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4621', None, '1171291875', 'None', None, None, None, None, None), ('4621', None, '1171275314', 'None', None, None, None, None, None), ('4621', None, '1171275372', 'None', None, None, None, None, None)] time used for this insertion : 0.012648582458496094 save_final save missing photos in datou_result : time spend for datou_step_exec : 18.40082812309265 time spend to save output : 0.012990951538085938 total time spend for step 1 : 18.413819074630737 step2:argmax Thu Sep 25 17:03:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg': 1171291875, 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg': 1171275314, 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg': 1171275372} map_photo_id_path_extension : {1171291875: {'path': 'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg', 'extension': 'jpg'}, 1171275314: {'path': 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg', 'extension': 'jpg'}, 1171275372: {'path': 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! calculate argmax for thcl : 3655 After datou_step_exec type output : map_portfolio_photo : len 0 keys : dict_keys([]) Inside saveOutput : final : True verbose : True photo_id : 1171291875 output[photo_id] : [(1171291875, 'tapis_vide', 0.97062516, 4723, '3655'), 'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg'] photo_id : 1171275314 output[photo_id] : [(1171275314, 'tapis_vide', 0.9651163, 4723, '3655'), 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg'] photo_id : 1171275372 output[photo_id] : [(1171275372, 'tapis_vide', 0.96744186, 4723, '3655'), 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) first line : ('1171291875', '2107748999', '4723') ... last line : ('1171275372', '2107748999', '4723') time used for this insertion : 0.008771896362304688 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 3 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 0.01103973388671875 len list_finale : 3, len picture : 3 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4621', None, '1171291875', 'tapis_vide', None, None, '2107748999', '0.97062516', None), ('4621', None, '1171275314', 'tapis_vide', None, None, '2107748999', '0.9651163', None), ('4621', None, '1171275372', 'tapis_vide', None, None, '2107748999', '0.96744186', None)] time used for this insertion : 0.0119781494140625 saving photo_ids in datou_result photo id not in port photo id not in port photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [] time used for this insertion : 3.337860107421875e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.00014972686767578125 time spend to save output : 0.03586149215698242 total time spend for step 2 : 0.0360112190246582 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'1171291875': [(1171291875, 'tapis_vide', 0.97062516, 4723, '3655'), 'temp/1758812569_3157952_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg'], '1171275314': [(1171275314, 'tapis_vide', 0.9651163, 4723, '3655'), 'temp/1758812569_3157952_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg'], '1171275372': [(1171275372, 'tapis_vide', 0.96744186, 4723, '3655'), 'temp/1758812569_3157952_1171275372_76d81364ff7df843bff095f45c07ba35.jpg']} --------------------- test with use_multi_inputs=1 is succeded ------------------- ############################### TEST ordonner ################################ To do loadFromThcl(), then load ParamDescType : thcl358 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (358) thcls : [{'id': 358, 'mtr_user_id': 31, 'name': 'car_orientation_0111', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'FirstUploadExperveo_vignette__port_505674,CAR_EXTERIEUR_Roue__port_503398,FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486,FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485,CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465,CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198,CAR_EXTERIEUR_Face_avant_axe_droit__port_504451,CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235,FirstUploadExperveo_vin__port_505675,CAR_EXTERIEUR_cote_droite__port_504108,CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565,FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483,CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201,cartegrise_orientation__port_505064,CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217,CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531,CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218,CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214,CAR_EXTERIEUR_Angle_avant_droit__port_504087,FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484,CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563,CAR_EXTERIEUR_Angle_arriere_droit__port_504160,CAR_EXTERIEUR_arriere__port_504184,CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562,INTERIEUR_Compteur_kilometrique__port_503644,CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494,CAR_EXTERIEUR_Angle_arriere_gauche__port_504170,CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226,CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202,CAR_EXTERIEUR_moteur__port_503704,FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487,CAR_INTERIEUR_siege_arriere_class_1__port_506551,CAR_EXTERIEUR_avant__port_504146,CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215,CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225,CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564,FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482,CAR_INTERIEUR_coffre__port_503412,FirstUploadExperveo_rouetranche__port_505677,UploadPhotoImmatBest_class_1__port_505051,CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532,CAR_EXTERIEUR_angle_avant_gauche__port_504098,CAR_EXTERIEUR_face_avant_axe_gauche__port_504236,CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540,CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233,CAR_EXTERIEUR_roue_de_secour__port_503763,CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199,CAR_EXTERIEUR_cote_gauche__port_504017,CAR_INTERIEUR_avant_volant_class_1__port_506503,CAR_INTERIEUR_avant_volant_class_2__port_506504,CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234', 'svm_portfolios_learning': '505674,503398,506486,506485,504465,504198,504451,504235,505675,504108,506565,506483,504201,505064,504217,506531,504218,504214,504087,506484,506563,504160,504184,506562,503644,506494,504170,504226,504202,503704,506487,506551,504146,504215,504225,506564,506482,503412,505677,505051,506532,504098,504236,506540,504233,503763,504199,504017,506503,506504,504234', 'photo_hashtag_type': 337, 'photo_desc_type': 3392, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 358, 'mtr_user_id': 31, 'name': 'car_orientation_0111', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'FirstUploadExperveo_vignette__port_505674,CAR_EXTERIEUR_Roue__port_503398,FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486,FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485,CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465,CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198,CAR_EXTERIEUR_Face_avant_axe_droit__port_504451,CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235,FirstUploadExperveo_vin__port_505675,CAR_EXTERIEUR_cote_droite__port_504108,CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565,FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483,CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201,cartegrise_orientation__port_505064,CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217,CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531,CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218,CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214,CAR_EXTERIEUR_Angle_avant_droit__port_504087,FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484,CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563,CAR_EXTERIEUR_Angle_arriere_droit__port_504160,CAR_EXTERIEUR_arriere__port_504184,CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562,INTERIEUR_Compteur_kilometrique__port_503644,CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494,CAR_EXTERIEUR_Angle_arriere_gauche__port_504170,CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226,CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202,CAR_EXTERIEUR_moteur__port_503704,FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487,CAR_INTERIEUR_siege_arriere_class_1__port_506551,CAR_EXTERIEUR_avant__port_504146,CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215,CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225,CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564,FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482,CAR_INTERIEUR_coffre__port_503412,FirstUploadExperveo_rouetranche__port_505677,UploadPhotoImmatBest_class_1__port_505051,CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532,CAR_EXTERIEUR_angle_avant_gauche__port_504098,CAR_EXTERIEUR_face_avant_axe_gauche__port_504236,CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540,CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233,CAR_EXTERIEUR_roue_de_secour__port_503763,CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199,CAR_EXTERIEUR_cote_gauche__port_504017,CAR_INTERIEUR_avant_volant_class_1__port_506503,CAR_INTERIEUR_avant_volant_class_2__port_506504,CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234', 'svm_portfolios_learning': '505674,503398,506486,506485,504465,504198,504451,504235,505675,504108,506565,506483,504201,505064,504217,506531,504218,504214,504087,506484,506563,504160,504184,506562,503644,506494,504170,504226,504202,503704,506487,506551,504146,504215,504225,506564,506482,503412,505677,505051,506532,504098,504236,506540,504233,503763,504199,504017,506503,506504,504234', 'photo_hashtag_type': 337, 'photo_desc_type': 3392, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3392 ['FirstUploadExperveo_vignette__port_505674', 'CAR_EXTERIEUR_Roue__port_503398', 'FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486', 'FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485', 'CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465', 'CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198', 'CAR_EXTERIEUR_Face_avant_axe_droit__port_504451', 'CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235', 'FirstUploadExperveo_vin__port_505675', 'CAR_EXTERIEUR_cote_droite__port_504108', 'CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565', 'FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483', 'CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201', 'cartegrise_orientation__port_505064', 'CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217', 'CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531', 'CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218', 'CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214', 'CAR_EXTERIEUR_Angle_avant_droit__port_504087', 'FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484', 'CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563', 'CAR_EXTERIEUR_Angle_arriere_droit__port_504160', 'CAR_EXTERIEUR_arriere__port_504184', 'CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562', 'INTERIEUR_Compteur_kilometrique__port_503644', 'CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494', 'CAR_EXTERIEUR_Angle_arriere_gauche__port_504170', 'CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226', 'CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202', 'CAR_EXTERIEUR_moteur__port_503704', 'FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487', 'CAR_INTERIEUR_siege_arriere_class_1__port_506551', 'CAR_EXTERIEUR_avant__port_504146', 'CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215', 'CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225', 'CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564', 'FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482', 'CAR_INTERIEUR_coffre__port_503412', 'FirstUploadExperveo_rouetranche__port_505677', 'UploadPhotoImmatBest_class_1__port_505051', 'CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532', 'CAR_EXTERIEUR_angle_avant_gauche__port_504098', 'CAR_EXTERIEUR_face_avant_axe_gauche__port_504236', 'CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540', 'CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233', 'CAR_EXTERIEUR_roue_de_secour__port_503763', 'CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199', 'CAR_EXTERIEUR_cote_gauche__port_504017', 'CAR_INTERIEUR_avant_volant_class_1__port_506503', 'CAR_INTERIEUR_avant_volant_class_2__port_506504', 'CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234'] 51 SELECT hashtag_id,hashtag FROM MTRBack.hashtags where hashtag in ('FirstUploadExperveo_vignette__port_505674','CAR_EXTERIEUR_Roue__port_503398','FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486','FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485','CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465','CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198','CAR_EXTERIEUR_Face_avant_axe_droit__port_504451','CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235','FirstUploadExperveo_vin__port_505675','CAR_EXTERIEUR_cote_droite__port_504108','CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565','FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483','CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201','cartegrise_orientation__port_505064','CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217','CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531','CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218','CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214','CAR_EXTERIEUR_Angle_avant_droit__port_504087','FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484','CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563','CAR_EXTERIEUR_Angle_arriere_droit__port_504160','CAR_EXTERIEUR_arriere__port_504184','CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562','INTERIEUR_Compteur_kilometrique__port_503644','CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494','CAR_EXTERIEUR_Angle_arriere_gauche__port_504170','CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226','CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202','CAR_EXTERIEUR_moteur__port_503704','FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487','CAR_INTERIEUR_siege_arriere_class_1__port_506551','CAR_EXTERIEUR_avant__port_504146','CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215','CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225','CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564','FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482','CAR_INTERIEUR_coffre__port_503412','FirstUploadExperveo_rouetranche__port_505677','UploadPhotoImmatBest_class_1__port_505051','CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532','CAR_EXTERIEUR_angle_avant_gauche__port_504098','CAR_EXTERIEUR_face_avant_axe_gauche__port_504236','CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540','CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233','CAR_EXTERIEUR_roue_de_secour__port_503763','CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199','CAR_EXTERIEUR_cote_gauche__port_504017','CAR_INTERIEUR_avant_volant_class_1__port_506503','CAR_INTERIEUR_avant_volant_class_2__port_506504','CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234'); 51 dict_keys(['cartegrise_orientation__port_505064', 'car_exterieur_angle_arriere_droit_axe_arriere__port_504217', 'car_exterieur_angle_arriere_droit_axe_droit__port_504215', 'car_exterieur_angle_arriere_droit__port_504160', 'car_exterieur_angle_arriere_gauche_axe_arriere__port_504201', 'car_exterieur_angle_arriere_gauche_axe_gauche__port_504199', 'car_exterieur_angle_arriere_gauche__port_504170', 'car_exterieur_angle_avant_droit_axe_arriere__port_504226', 'car_exterieur_angle_avant_droit_axe_droit__port_504225', 'car_exterieur_angle_avant_droit__port_504087', 'car_exterieur_angle_avant_gauche_axe_avant__port_504235', 'car_exterieur_angle_avant_gauche_axe_gauche__port_504234', 'car_exterieur_angle_avant_gauche__port_504098', 'car_exterieur_arriere__port_504184', 'car_exterieur_avant__port_504146', 'car_exterieur_cote_droite__port_504108', 'car_exterieur_cote_droit_axe_arriere__port_504214', 'car_exterieur_cote_droit_axe_avant__port_504465', 'car_exterieur_cote_gauche_axe_arriere__port_504198', 'car_exterieur_cote_gauche_axe_avant__port_504233', 'car_exterieur_cote_gauche__port_504017', 'car_exterieur_face_arriere_axe_droit__port_504218', 'car_exterieur_face_arriere_axe_gauche__port_504202', 'car_exterieur_face_avant_axe_droit__port_504451', 'car_exterieur_face_avant_axe_gauche__port_504236', 'car_exterieur_moteur__port_503704', 'car_exterieur_roue_de_secour__port_503763', 'car_exterieur_roue__port_503398', 'car_interieur_avant_volant_class_1__port_506503', 'car_interieur_avant_volant_class_2__port_506504', 'car_interieur_avant_volant_class_6_boutonrond__port_506562', 'car_interieur_avant_volant_class_6_class_2__port_506563', 'car_interieur_avant_volant_class_6_ecrangrosplan__port_506564', 'car_interieur_avant_volant_class_6_levierdevitesse__port_506565', 'car_interieur_avant_vue-arriere_class_1__port_506531', 'car_interieur_avant_vue-arriere_class_2__port_506532', 'car_interieur_avant_vue_droite_habitacle_class_1__port_506540', 'car_interieur_avant_vue_gauche_habitacle_class_1__port_506494', 'car_interieur_coffre__port_503412', 'car_interieur_siege_arriere_class_1__port_506551', 'firstuploadexperveo_carrosseriegrosplan_carrosserie__port_506483', 'firstuploadexperveo_carrosseriegrosplan_class_6__port_506487', 'firstuploadexperveo_carrosseriegrosplan_morceauderoue__port_506484', 'firstuploadexperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482', 'firstuploadexperveo_carrosseriegrosplan_siegegrosplan__port_506485', 'firstuploadexperveo_carrosseriegrosplan_vindanslamoquette__port_506486', 'firstuploadexperveo_rouetranche__port_505677', 'firstuploadexperveo_vignette__port_505674', 'firstuploadexperveo_vin__port_505675', 'interieur_compteur_kilometrique__port_503644', 'uploadphotoimmatbest_class_1__port_505051']) select photo_hashtag_type from MTRDatou.classification_theme where id = 358 thcl : 358 photo_hashtag_type : 337 SELECT phi.hashtag_id , phi.photo_id FROM MTRBack.photo_hashtag_ids phi, MTRUser.mtr_portfolio_photos mp where phi.type = 337 and phi.photo_id = mp.mtr_photo_id and mp.mtr_portfolio_id =510365; {510365: [(917973295, 1), (917973297, 1), (917973302, 1), (917973293, 7), (917973296, 11), (917973300, 11), (917973286, 13), (917973289, 13), (917973301, 24), (917973285, 29), (917973290, 29), (917973299, 29), (917973304, 35), (917973287, 36), (917973298, 36), (917973305, 36), (917973292, 37), (917973291, 41), (917973303, 41), (917973294, 42), (917973288, 46)]} ############################### TEST rotate ################################ test rotate only Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=230 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=230 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 230 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=230 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : rotate list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (917849322) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 917849322 download finish for photo 917849322 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1639561653137207 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:rotate Thu Sep 25 17:03:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg': 917849322} map_photo_id_path_extension : {917849322: {'path': 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step_rotate ! We are in a linear step without datou_depend ! rotate photos of 90,180,270 degres batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 917849322) and `type` in (0) Loaded 0 chid ids of type : 0 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in () map_chi : {} photo_id in download_rotate_and_save : 917849322 list_chi_loc : 0 Use all angle ! Rotation of photo 917849322 of 90 degree temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg [] 90 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] 90 [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] shrink_image : False image_rotate : image_path : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg path_name_rotate : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c454890.jpg image_rotate.mode : RGB Rotation of photo 917849322 of 180 degree temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg [] 180 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] 180 [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] shrink_image : False image_rotate : image_path : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg path_name_rotate : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548180.jpg image_rotate.mode : RGB Rotation of photo 917849322 of 270 degree temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg [] 270 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] 270 [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] shrink_image : False image_rotate : image_path : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg path_name_rotate : temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548270.jpg image_rotate.mode : RGB About to upload 3 photos upload in portfolio : 551782 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812589_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 3 photos in the portfolio 551782 time of upload the photos Elapsed time : 1.1402316093444824 map_filename_photo_id : 3 map_filename_photo_id : {'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c454890.jpg': 1386158591, 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548180.jpg': 1386158593, 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548270.jpg': 1386158594} Len new_chis : 3 Len list_new_chi_with_photo_id : 0 of type : 0 list_new_chi_with_photo_id : [] After datou_step_exec type output : time spend for datou_step_exec : 1.3556222915649414 time spend to save output : 2.8848648071289062e-05 total time spend for step 1 : 1.3556511402130127 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [917849322] map_info['map_portfolio_photo'] : {} final : True mtd_id 230 list_pids : [917849322] Looping around the photos to save general results len do output : 3 /1386158591Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386158593Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386158594Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('230', None, None, None, None, None, None, None, None) ('230', None, '917849322', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('230', None, '1386158591', 'None', None, None, None, None, None), ('230', None, '1386158593', 'None', None, None, None, None, None), ('230', None, '1386158594', 'None', None, None, None, None, None), ('230', None, '917849322', None, None, None, None, None, None)] time used for this insertion : 0.012391090393066406 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1386158591: ['917849322', 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c454890.jpg', []], 1386158593: ['917849322', 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548180.jpg', []], 1386158594: ['917849322', 'temp/1758812588_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548270.jpg', []]} test rotate only is a success ! test rotate conditionnel Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=233 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=233 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 233 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=233 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : thcl, argmax, rotate list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (917849322) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 917849322 download finish for photo 917849322 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.15366172790527344 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 3 step1:thcl Thu Sep 25 17:03:10 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg': 917849322} map_photo_id_path_extension : {917849322: {'path': 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Thcl ! multi_thcl or not :False multi_thcl_cond or not :False dic_thcl : {'500': 1} we are using the classfication for only one thcl 500 In convert_file_to_np l 337 : 1 l343 1 l357 after caffe.io.load_image dimension du image : (3, (2448, 3264, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.00020051002502441406 time to convert the images to numpy array : 0.6957683563232422 total time to convert the images to numpy array : 0.6962687969207764 list photo_ids error: [] list photo_ids correct : [917849322] number of photos to traite : 1 try to delete the photos incorrect in DB tagging for thcl : 500 To do loadFromThcl(), then load ParamDescType : thcl500 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (500) thcls : [{'id': 500, 'mtr_user_id': 31, 'name': 'orientation_carte_grise_all_2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'carteGrisesVerticales__port_549774,cartegrise_90deg__port_550987,cartesGrisesEnvers__port_549765,portfolio_270deg__port_550988', 'svm_portfolios_learning': '549774,550987,549765,550988', 'photo_hashtag_type': 507, 'photo_desc_type': 3517, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0'}] thcl {'id': 500, 'mtr_user_id': 31, 'name': 'orientation_carte_grise_all_2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'carteGrisesVerticales__port_549774,cartegrise_90deg__port_550987,cartesGrisesEnvers__port_549765,portfolio_270deg__port_550988', 'svm_portfolios_learning': '549774,550987,549765,550988', 'photo_hashtag_type': 507, 'photo_desc_type': 3517, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0'} Update svm_hashtag_type_desc : 3517 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (3517) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3517, 'orientation_carte_grise_all_2', 16384, 25088, 'orientation_carte_grise_all_2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 4, 18, 20, 4, 34), datetime.datetime(2018, 4, 18, 20, 4, 34)) To loadFromThcl() : net_3517 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 2930 max_wait_temp : 1 max_wait : 0 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (3517) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3517, 'orientation_carte_grise_all_2', 16384, 25088, 'orientation_carte_grise_all_2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 4, 18, 20, 4, 34), datetime.datetime(2018, 4, 18, 20, 4, 34)) param : , param.caffemodel : orientation_carte_grise_all_2 None mean_file_type : mean_file_path : prototxt_file_path : model : orientation_carte_grise_all_2 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : orientation_carte_grise_all_2 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : [] local folder : /data/models_weight/orientation_carte_grise_all_2 /data/models_weight/orientation_carte_grise_all_2/caffemodel size_local : 537110520 size in s3 : 537110520 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:17 caffemodel already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy_conv_normal.prototxt size_local : 4626 size in s3 : 4626 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy_conv_normal.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy_fc.prototxt size_local : 1130 size in s3 : 1130 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy_fc.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy.prototxt size_local : 5653 size in s3 : 5653 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:31 mean.npy already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/synset_words.txt size_local : 159 size in s3 : 159 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/caffe_cuda8_python3/python/:/home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/:/home/admin/workarea/git/apy/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/orientation_carte_grise_all_2/deploy.prototxt caffemodel_filename : /data/models_weight/orientation_carte_grise_all_2/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 2930 max_wait_temp : 1 max_wait : 0 dict_keys(['prob', 'pool5']) time used to do the prepocess of the images : 2.4362425804138184 time used to do the prediction : 0.1059713363647461 save descriptor for thcl : 500 (1, 512, 7, 7) Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] code_as_byte_string:b'0000000000'| time to traite the descriptors : 0.048226118087768555 Testing : ['917849322'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (917849322) result : {917849322: {'photo_id': 917849322, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/9/13/2bd260e91e91df8378dde8bb8b8c4548.jpg', 'latitude': None, 'longitude': None, 'text': 'image_13092022_12_32_19_5566.jpg'}} list_photo_exists : [917849322] storage_type for insertDescriptorsMulti : 1 To insert : 917849322 time to insert the descriptors : 0.549962043762207 After datou_step_exec type output : time spend for datou_step_exec : 9.32585620880127 time spend to save output : 5.984306335449219e-05 total time spend for step 1 : 9.325916051864624 step2:argmax Thu Sep 25 17:03:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'917849322': [[('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), ('917849322', 'cartegrise_90deg__port_550987', 0.000503669, 507, '500'), ('917849322', 'cartesGrisesEnvers__port_549765', 0.00036618108, 507, '500'), ('917849322', 'portfolio_270deg__port_550988', 0.0014814911, 507, '500')]]} input_args_next_step : {'917849322': ()} output_args : {'917849322': [[('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), ('917849322', 'cartegrise_90deg__port_550987', 0.000503669, 507, '500'), ('917849322', 'cartesGrisesEnvers__port_549765', 0.00036618108, 507, '500'), ('917849322', 'portfolio_270deg__port_550988', 0.0014814911, 507, '500')]]} args : 917849322 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ([('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), ('917849322', 'cartegrise_90deg__port_550987', 0.000503669, 507, '500'), ('917849322', 'cartesGrisesEnvers__port_549765', 0.00036618108, 507, '500'), ('917849322', 'portfolio_270deg__port_550988', 0.0014814911, 507, '500')],) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg': 917849322} map_photo_id_path_extension : {917849322: {'path': 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! calculate argmax for thcl : 500 After datou_step_exec type output : time spend for datou_step_exec : 0.00022125244140625 time spend to save output : 4.4345855712890625e-05 total time spend for step 2 : 0.0002655982971191406 step3:rotate Thu Sep 25 17:03:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'917849322': [('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg']} input_args_next_step : {'917849322': ()} output_args : {'917849322': [('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg']} args : 917849322 depend.output_id : 1 complete output_args for input 1 : {'917849322': [('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg']} input_args_next_step : {'917849322': ('temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg',)} output_args : {'917849322': [('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500'), 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg']} args : 917849322 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ('temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg', ('917849322', 'carteGrisesVerticales__port_549774', 0.99764866, 507, '500')) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg': 917849322} map_photo_id_path_extension : {917849322: {'path': 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step_rotate ! We are in a datou with depends ! angle_condi : {'carteGrisesVerticales__port_549774': 0, 'cartegrise_90deg__port_550987': 270, 'portfolio_270deg__port_550988': 90, 'cartesGrisesEnvers__port_549765': 180} rotate photos for hashtag carteGrisesVerticales__port_549774 of 0 degres 1 photos founded : [917849322] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 917849322) and `type` in (0) Loaded 0 chid ids of type : 0 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in () map_chi : {} photo_id in download_rotate_and_save : 917849322 list_chi_loc : 0 Use all angle ! Rotation of photo 917849322 of 0 degree temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg [] 0 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[ 1. 0.] [-0. 1.]] 0 [[ 1. 0.] [-0. 1.]] shrink_image : False image_rotate : image_path : temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c4548.jpg path_name_rotate : temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c45480.jpg image_rotate.mode : RGB About to upload 1 photos upload in portfolio : 551782 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812600_3157952 we have uploaded 1 photos in the portfolio 551782 time of upload the photos Elapsed time : 0.5153977870941162 map_filename_photo_id : 1 map_filename_photo_id : {'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c45480.jpg': 1386158702} Len new_chis : 1 Len list_new_chi_with_photo_id : 0 of type : 0 list_new_chi_with_photo_id : [] rotate photos for hashtag cartegrise_90deg__port_550987 of 270 degres 0 photos founded : [] rotate photos for hashtag portfolio_270deg__port_550988 of 90 degres 0 photos founded : [] rotate photos for hashtag cartesGrisesEnvers__port_549765 of 180 degres 0 photos founded : [] After datou_step_exec type output : time spend for datou_step_exec : 0.6092061996459961 time spend to save output : 4.124641418457031e-05 total time spend for step 3 : 0.6092474460601807 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [917849322] map_info['map_portfolio_photo'] : {} final : True mtd_id 233 list_pids : [917849322] Looping around the photos to save general results len do output : 1 /1386158702Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('233', None, None, None, None, None, None, None, None) ('233', None, '917849322', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('233', None, '1386158702', 'None', None, None, None, None, None), ('233', None, '917849322', None, None, None, None, None, None)] time used for this insertion : 0.012411117553710938 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 3 output : {1386158702: ['917849322', 'temp/1758812590_3157952_917849322_2bd260e91e91df8378dde8bb8b8c45480.jpg', []]} ############################### TEST data_augmentation_ellipse_varroa_tile_rotate ################################ SELECT id FROM MTRPhoto.crop_hashtag_ids WHERE photo_id=937852786 AND `type`=520 DELETE FROM MTRPhoto.crop_hashtag_ids WHERE id IN (3975186133,3975186134,3975186135,3975186136) # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 316 crop is not linked in the step_by_step architecture ! Step 318 rotate have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 318 rotate have less outputs used (0) than in the step definition (3) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! Unexpected type seems boolean for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : DATA AUGMENTATION ELLIPSE VARROA TILE ROTATE Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=243 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=243 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 243 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=243 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 316 crop is not linked in the step_by_step architecture ! Step 318 rotate have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 318 rotate have less outputs used (0) than in the step definition (3) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : crop, tile, rotate list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (937852786) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 937852786 download finish for photo 937852786 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1319141387939453 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 3 step1:crop Thu Sep 25 17:03:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg': 937852786} map_photo_id_path_extension : {937852786: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Crop ! param_json : {'hashtag_id_ellipse': 2087736828, 'photo_hashtag_type_from_ellipse': 520, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'crop_detect_varroa', 'photo_hashtag_type': 407, 'feed_id_new_photos_not_used': 549103, 'host': 'www.fotonower.com', 'margin': 8, 'upload_type': 'python'} margin_type : margin margin_value : [8, 8, 8, 8] Loading chi in step crop with photo_hashtag_type : 407 Loading chi in step crop for list_pids : 1 ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 937852786) and `type` in (407) Loaded 4 chid ids of type : 407 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (8165075,8165076,8165077,8165078) +WARNING : Unexpected points, we should remove this data for chi_id : 8165075, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165076, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165077, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165078, for now we just ignore these empty polygon points SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (8165075,8165076,8165077,8165078) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (8165075,8165076,8165077,8165078) select photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type, id from MTRPhoto.photo_sub_photos where photo_id in ( 937852786) WARNING : margin is only used for type bib ! type of cropped photo chosen : we resize croppped photo by 1 on x axis and by 1 on y axis new_file_path_bib_crop : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg new_file_path_bib_crop : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg new_file_path_bib_crop : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg new_file_path_bib_crop : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg map_result returned by crop_photo_return_map_crop : length : 4 map_result after crop : {8165075: {'crop': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg', 'photo_id': 937852786, 'sub_photo_id': -1, 'coordonates': (426, 467, 312, 347), 'sub_photo_infos': (418, 475, 304, 355, 1, 1), 'same_chi': False}, 8165076: {'crop': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg', 'photo_id': 937852786, 'sub_photo_id': -1, 'coordonates': (411, 445, 443, 480), 'sub_photo_infos': (403, 453, 435, 480, 1, 1), 'same_chi': False}, 8165077: {'crop': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg', 'photo_id': 937852786, 'sub_photo_id': -1, 'coordonates': (103, 138, 358, 396), 'sub_photo_infos': (95, 146, 350, 404, 1, 1), 'same_chi': False}, 8165078: {'crop': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg', 'photo_id': 937852786, 'sub_photo_id': -1, 'coordonates': (104, 131, 256, 292), 'sub_photo_infos': (96, 139, 248, 300, 1, 1), 'same_chi': False}} Here we crop with rles About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 27233548 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812603_3157952 batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (51, 57, 1794, 1386158747, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 4451846, 'jpg', UNHEX('c2d4b7e9a87b733b24c212df7b55bc09')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (45, 50, 1790, 1386158750, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 77554994, 'jpg', UNHEX('73bb947187a7cccf402d3c49d52f0e04')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (54, 51, 1867, 1386158751, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 68837991, 'jpg', UNHEX('cef221ccc8163d341ac8369fab7a6492')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (52, 43, 1418, 1386158752, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 1598154, 'jpg', UNHEX('036d93e6c08ecafaae7820b02e96abeb')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `mtr_user_id`, `created_at`) VALUES (27233548, 1386158747, 0, NOW()),(27233548, 1386158750, 0, NOW()),(27233548, 1386158751, 0, NOW()),(27233548, 1386158752, 0, NOW()) 4 we have uploaded 4 photos in the portfolio 27233548 time of upload the photos Elapsed time : 4.414556503295898 {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg': 1386158747, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg': 1386158750, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg': 1386158751, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg': 1386158752} list_errors : [] map_result_insert : {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg': 1386158747, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg': 1386158750, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg': 1386158751, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg': 1386158752} Now we prepare data that will be used for ellipse search ! chi_id found to be used 8165075 path of cropped varroa found to be used to match on an ellipse temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg sub_photo_id found to be used 1386158747 chi_id found to be used 8165076 path of cropped varroa found to be used to match on an ellipse temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg sub_photo_id found to be used 1386158750 chi_id found to be used 8165077 path of cropped varroa found to be used to match on an ellipse temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg sub_photo_id found to be used 1386158751 chi_id found to be used 8165078 path of cropped varroa found to be used to match on an ellipse temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg sub_photo_id found to be used 1386158752 insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [(8165075, '1386158747', 31), (8165076, '1386158750', 31), (8165077, '1386158751', 31), (8165078, '1386158752', 31)] map of cropped photos with some data : {'1386158747': ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg', (426, 467, 312, 347)], '1386158750': ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg', (411, 445, 443, 480)], '1386158751': ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg', (103, 138, 358, 396)], '1386158752': ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg', (104, 131, 256, 292)]} About to compute ellipse and record with type : 520 (54, 57) (51, 57) [54, 57] (54, 57) score : 5120 strategy_opt : 5| strategy_opt : [('excentricity', [0.5, 2.0, 0.05]), ('angle', [-90.0, 90.0, 5.0]), ('xc', [14.25, 42.75, 1.78125]), ('yc', [12.75, 38.25, 1.59375]), ('radius', [14.25, 42.75, 1.78125])] {0.5: 18351, 0.55: 16004, 0.6000000000000001: 14127, 0.65: 12575, 0.7000000000000001: 11300, 0.75: 10158, 0.8: 9208, 0.8500000000000001: 8418, 0.9: 7642, 0.9500000000000001: 6925, 1.0: 6364, 1.05: 5843, 1.1: 5353, 1.1500000000000001: 4868, 1.2000000000000002: 4553, 1.25: 4250, 1.3: 3947, 1.35: 3698, 1.4000000000000001: 3438, 1.4500000000000002: 3230, 1.5: 3012, 1.55: 2829, 1.6: 2636, 1.6500000000000001: 2535, 1.7000000000000002: 2460, 1.75: 2388, 1.8: 2372, 1.85: 2354, 1.9000000000000001: 2332, 1.9500000000000002: 2311} [(1.9500000000000002, 2311), (1.9000000000000001, 2332), (1.85, 2354), (1.8, 2372), (1.75, 2388), (1.7000000000000002, 2460), (1.6500000000000001, 2535), (1.6, 2636), (1.55, 2829), (1.5, 3012), (1.4500000000000002, 3230), (1.4000000000000001, 3438), (1.35, 3698), (1.3, 3947), (1.25, 4250), (1.2000000000000002, 4553), (1.1500000000000001, 4868), (1.1, 5353), (1.05, 5843), (1.0, 6364), (0.9500000000000001, 6925), (0.9, 7642), (0.8500000000000001, 8418), (0.8, 9208), (0.75, 10158), (0.7000000000000001, 11300), (0.65, 12575), (0.6000000000000001, 14127), (0.55, 16004), (0.5, 18351)] arg_min reach at : 1.9500000000000002 with value = 2311 | arg_min : 1.9500000000000002 min_score : 2311{-90.0: 3359, -85.0: 3372, -80.0: 3395, -75.0: 3380, -70.0: 3304, -65.0: 3180, -60.0: 2991, -55.0: 2793, -50.0: 2601, -45.0: 2377, -40.0: 2183, -35.0: 2078, -30.0: 1968, -25.0: 1968, -20.0: 2021, -15.0: 2036, -10.0: 2102, -5.0: 2188, 0.0: 2208, 5.0: 2265, 10.0: 2311, 15.0: 2333, 20.0: 2362, 25.0: 2375, 30.0: 2375, 35.0: 2397, 40.0: 2370, 45.0: 2421, 50.0: 2491, 55.0: 2661, 60.0: 2826, 65.0: 2993, 70.0: 3106, 75.0: 3182, 80.0: 3263, 85.0: 3306} [(-30.0, 1968), (-25.0, 1968), (-20.0, 2021), (-15.0, 2036), (-35.0, 2078), (-10.0, 2102), (-40.0, 2183), (-5.0, 2188), (0.0, 2208), (5.0, 2265), (10.0, 2311), (15.0, 2333), (20.0, 2362), (40.0, 2370), (25.0, 2375), (30.0, 2375), (-45.0, 2377), (35.0, 2397), (45.0, 2421), (50.0, 2491), (-50.0, 2601), (55.0, 2661), (-55.0, 2793), (60.0, 2826), (-60.0, 2991), (65.0, 2993), (70.0, 3106), (-65.0, 3180), (75.0, 3182), (80.0, 3263), (-70.0, 3304), (85.0, 3306), (-90.0, 3359), (-85.0, 3372), (-75.0, 3380), (-80.0, 3395)] arg_min reach at : -30.0 with value = 1968 | arg_min : -30.0 min_score : 1968{14.25: 1703, 16.03125: 1654, 17.8125: 1614, 19.59375: 1679, 21.375: 1702, 23.15625: 1712, 24.9375: 1730, 26.71875: 1847, 28.5: 1968, 30.28125: 2177, 32.0625: 2456, 33.84375: 2827, 35.625: 3294, 37.40625: 3723, 39.1875: 4161, 40.96875: 4643} [(17.8125, 1614), (16.03125, 1654), (19.59375, 1679), (21.375, 1702), (14.25, 1703), (23.15625, 1712), (24.9375, 1730), (26.71875, 1847), (28.5, 1968), (30.28125, 2177), (32.0625, 2456), (33.84375, 2827), (35.625, 3294), (37.40625, 3723), (39.1875, 4161), (40.96875, 4643)] arg_min reach at : 17.8125 with value = 1614 | arg_min : 17.8125 min_score : 1614{12.75: 5534, 14.34375: 5352, 15.9375: 5116, 17.53125: 4723, 19.125: 4111, 20.71875: 3506, 22.3125: 2799, 23.90625: 2194, 25.5: 1614, 27.09375: 1339, 28.6875: 1206, 30.28125: 1137, 31.875: 1105, 33.46875: 1339, 35.0625: 1659, 36.65625: 2022} [(31.875, 1105), (30.28125, 1137), (28.6875, 1206), (27.09375, 1339), (33.46875, 1339), (25.5, 1614), (35.0625, 1659), (36.65625, 2022), (23.90625, 2194), (22.3125, 2799), (20.71875, 3506), (19.125, 4111), (17.53125, 4723), (15.9375, 5116), (14.34375, 5352), (12.75, 5534)] arg_min reach at : 31.875 with value = 1105 | arg_min : 31.875 min_score : 1105{14.25: 1942, 16.03125: 1853, 17.8125: 1756, 19.59375: 1651, 21.375: 1533, 23.15625: 1424, 24.9375: 1309, 26.71875: 1199, 28.5: 1105, 30.28125: 1219, 32.0625: 1332, 33.84375: 1547, 35.625: 1881, 37.40625: 2378, 39.1875: 3042, 40.96875: 3824} [(28.5, 1105), (26.71875, 1199), (30.28125, 1219), (24.9375, 1309), (32.0625, 1332), (23.15625, 1424), (21.375, 1533), (33.84375, 1547), (19.59375, 1651), (17.8125, 1756), (16.03125, 1853), (35.625, 1881), (14.25, 1942), (37.40625, 2378), (39.1875, 3042), (40.96875, 3824)] arg_min reach at : 28.5 with value = 1105 | arg_min : 28.5 min_score : 1105{0.5: 17397, 0.55: 15138, 0.6000000000000001: 13352, 0.65: 11859, 0.7000000000000001: 10523, 0.75: 9463, 0.8: 8469, 0.8500000000000001: 7565, 0.9: 6551, 0.9500000000000001: 5592, 1.0: 4856, 1.05: 4291, 1.1: 3654, 1.1500000000000001: 3099, 1.2000000000000002: 2647, 1.25: 2309, 1.3: 1983, 1.35: 1755, 1.4000000000000001: 1594, 1.4500000000000002: 1447, 1.5: 1358, 1.55: 1323, 1.6: 1219, 1.6500000000000001: 1215, 1.7000000000000002: 1201, 1.75: 1131, 1.8: 1134, 1.85: 1142, 1.9000000000000001: 1137, 1.9500000000000002: 1105} [(1.9500000000000002, 1105), (1.75, 1131), (1.8, 1134), (1.9000000000000001, 1137), (1.85, 1142), (1.7000000000000002, 1201), (1.6500000000000001, 1215), (1.6, 1219), (1.55, 1323), (1.5, 1358), (1.4500000000000002, 1447), (1.4000000000000001, 1594), (1.35, 1755), (1.3, 1983), (1.25, 2309), (1.2000000000000002, 2647), (1.1500000000000001, 3099), (1.1, 3654), (1.05, 4291), (1.0, 4856), (0.9500000000000001, 5592), (0.9, 6551), (0.8500000000000001, 7565), (0.8, 8469), (0.75, 9463), (0.7000000000000001, 10523), (0.65, 11859), (0.6000000000000001, 13352), (0.55, 15138), (0.5, 17397)] arg_min reach at : 1.9500000000000002 with value = 1105 arg_min : 1.9500000000000002 min_score : 1105{-90.0: 3514, -85.0: 3396, -80.0: 3238, -75.0: 3017, -70.0: 2764, -65.0: 2549, -60.0: 2339, -55.0: 2105, -50.0: 1912, -45.0: 1701, -40.0: 1467, -35.0: 1266, -30.0: 1105, -25.0: 1110, -20.0: 1114, -15.0: 1111, -10.0: 1110, -5.0: 1121, 0.0: 1120, 5.0: 1118, 10.0: 1109, 15.0: 1109, 20.0: 1099, 25.0: 1088, 30.0: 1108, 35.0: 1355, 40.0: 1649, 45.0: 1925, 50.0: 2257, 55.0: 2542, 60.0: 2845, 65.0: 3137, 70.0: 3370, 75.0: 3500, 80.0: 3578, 85.0: 3540} [(25.0, 1088), (20.0, 1099), (-30.0, 1105), (30.0, 1108), (10.0, 1109), (15.0, 1109), (-25.0, 1110), (-10.0, 1110), (-15.0, 1111), (-20.0, 1114), (5.0, 1118), (0.0, 1120), (-5.0, 1121), (-35.0, 1266), (35.0, 1355), (-40.0, 1467), (40.0, 1649), (-45.0, 1701), (-50.0, 1912), (45.0, 1925), (-55.0, 2105), (50.0, 2257), (-60.0, 2339), (55.0, 2542), (-65.0, 2549), (-70.0, 2764), (60.0, 2845), (-75.0, 3017), (65.0, 3137), (-80.0, 3238), (70.0, 3370), (-85.0, 3396), (75.0, 3500), (-90.0, 3514), (85.0, 3540), (80.0, 3578)] arg_min reach at : 25.0 with value = 1088 arg_min : 25.0 min_score : 1088{14.25: 1174, 16.03125: 1133, 17.8125: 1088, 19.59375: 1051, 21.375: 1026, 23.15625: 997, 24.9375: 979, 26.71875: 1139, 28.5: 1344, 30.28125: 1564, 32.0625: 1949, 33.84375: 2422, 35.625: 2930, 37.40625: 3453, 39.1875: 4006, 40.96875: 4592} [(24.9375, 979), (23.15625, 997), (21.375, 1026), (19.59375, 1051), (17.8125, 1088), (16.03125, 1133), (26.71875, 1139), (14.25, 1174), (28.5, 1344), (30.28125, 1564), (32.0625, 1949), (33.84375, 2422), (35.625, 2930), (37.40625, 3453), (39.1875, 4006), (40.96875, 4592)] arg_min reach at : 24.9375 with value = 979 arg_min : 24.9375 min_score : 979{12.75: 5539, 14.34375: 5239, 15.9375: 4911, 17.53125: 4425, 19.125: 3749, 20.71875: 3181, 22.3125: 2575, 23.90625: 2124, 25.5: 1808, 27.09375: 1478, 28.6875: 1290, 30.28125: 1104, 31.875: 979, 33.46875: 1070, 35.0625: 1368, 36.65625: 1872} [(31.875, 979), (33.46875, 1070), (30.28125, 1104), (28.6875, 1290), (35.0625, 1368), (27.09375, 1478), (25.5, 1808), (36.65625, 1872), (23.90625, 2124), (22.3125, 2575), (20.71875, 3181), (19.125, 3749), (17.53125, 4425), (15.9375, 4911), (14.34375, 5239), (12.75, 5539)] arg_min reach at : 31.875 with value = 979 arg_min : 31.875 min_score : 979{14.25: 1939, 16.03125: 1852, 17.8125: 1755, 19.59375: 1643, 21.375: 1531, 23.15625: 1397, 24.9375: 1264, 26.71875: 1119, 28.5: 979, 30.28125: 1023, 32.0625: 1319, 33.84375: 1771, 35.625: 2432, 37.40625: 3324, 39.1875: 4299, 40.96875: 5405} [(28.5, 979), (30.28125, 1023), (26.71875, 1119), (24.9375, 1264), (32.0625, 1319), (23.15625, 1397), (21.375, 1531), (19.59375, 1643), (17.8125, 1755), (33.84375, 1771), (16.03125, 1852), (14.25, 1939), (35.625, 2432), (37.40625, 3324), (39.1875, 4299), (40.96875, 5405)] arg_min reach at : 28.5 with value = 979 arg_min : 28.5 min_score : 979 yc : 31.875 xc : 24.9375 angle : 25.0 radius : 28.5 excentricity : 1.9500000000000002 yc : 31.875 xc : 24.9375 angle : 25.0 radius : 28.5 excentricity : 1.9500000000000002 x0 : 426 y1 : 347 width : 41, height : 35, area : 1435, score : 1.0 x0 : 432 y1 : 355 width : 35, height : 52, area : 1820, score : 1.0 Now saving polygons points : 1| batch 1 Loaded 1 chid ids of type : 520 CHI and polygons saved ! (47, 50) (45, 50) [47, 50] (47, 50) score : 5362 strategy_opt : 5| strategy_opt : [('excentricity', [0.5, 2.0, 0.05]), ('angle', [-90.0, 90.0, 5.0]), ('xc', [12.5, 37.5, 1.5625]), ('yc', [11.25, 33.75, 1.40625]), ('radius', [12.5, 37.5, 1.5625])] {0.5: 15776, 0.55: 13889, 0.6000000000000001: 12446, 0.65: 11147, 0.7000000000000001: 10181, 0.75: 9228, 0.8: 8441, 0.8500000000000001: 7765, 0.9: 7258, 0.9500000000000001: 6684, 1.0: 6195, 1.05: 5920, 1.1: 5487, 1.1500000000000001: 5099, 1.2000000000000002: 4795, 1.25: 4511, 1.3: 4245, 1.35: 4042, 1.4000000000000001: 3828, 1.4500000000000002: 3629, 1.5: 3467, 1.55: 3235, 1.6: 3126, 1.6500000000000001: 2946, 1.7000000000000002: 2826, 1.75: 2700, 1.8: 2549, 1.85: 2472, 1.9000000000000001: 2381, 1.9500000000000002: 2281} [(1.9500000000000002, 2281), (1.9000000000000001, 2381), (1.85, 2472), (1.8, 2549), (1.75, 2700), (1.7000000000000002, 2826), (1.6500000000000001, 2946), (1.6, 3126), (1.55, 3235), (1.5, 3467), (1.4500000000000002, 3629), (1.4000000000000001, 3828), (1.35, 4042), (1.3, 4245), (1.25, 4511), (1.2000000000000002, 4795), (1.1500000000000001, 5099), (1.1, 5487), (1.05, 5920), (1.0, 6195), (0.9500000000000001, 6684), (0.9, 7258), (0.8500000000000001, 7765), (0.8, 8441), (0.75, 9228), (0.7000000000000001, 10181), (0.65, 11147), (0.6000000000000001, 12446), (0.55, 13889), (0.5, 15776)] arg_min reach at : 1.9500000000000002 with value = 2281 | arg_min : 1.9500000000000002 min_score : 2281{-90.0: 3295, -85.0: 3240, -80.0: 3290, -75.0: 3269, -70.0: 3287, -65.0: 3223, -60.0: 3095, -55.0: 3043, -50.0: 2985, -45.0: 2906, -40.0: 2796, -35.0: 2724, -30.0: 2625, -25.0: 2489, -20.0: 2330, -15.0: 2220, -10.0: 2127, -5.0: 2127, 0.0: 2143, 5.0: 2182, 10.0: 2281, 15.0: 2385, 20.0: 2506, 25.0: 2665, 30.0: 2768, 35.0: 2900, 40.0: 2939, 45.0: 2994, 50.0: 3007, 55.0: 3076, 60.0: 3095, 65.0: 3201, 70.0: 3243, 75.0: 3247, 80.0: 3279, 85.0: 3240} [(-10.0, 2127), (-5.0, 2127), (0.0, 2143), (5.0, 2182), (-15.0, 2220), (10.0, 2281), (-20.0, 2330), (15.0, 2385), (-25.0, 2489), (20.0, 2506), (-30.0, 2625), (25.0, 2665), (-35.0, 2724), (30.0, 2768), (-40.0, 2796), (35.0, 2900), (-45.0, 2906), (40.0, 2939), (-50.0, 2985), (45.0, 2994), (50.0, 3007), (-55.0, 3043), (55.0, 3076), (-60.0, 3095), (60.0, 3095), (65.0, 3201), (-65.0, 3223), (-85.0, 3240), (85.0, 3240), (70.0, 3243), (75.0, 3247), (-75.0, 3269), (80.0, 3279), (-70.0, 3287), (-80.0, 3290), (-90.0, 3295)] arg_min reach at : -10.0 with value = 2127 | arg_min : -10.0 min_score : 2127{12.5: 2171, 14.0625: 2288, 15.625: 2314, 17.1875: 2360, 18.75: 2347, 20.3125: 2300, 21.875: 2249, 23.4375: 2188, 25.0: 2127, 26.5625: 2163, 28.125: 2315, 29.6875: 2476, 31.25: 2756, 32.8125: 2992, 34.375: 3319, 35.9375: 3672} [(25.0, 2127), (26.5625, 2163), (12.5, 2171), (23.4375, 2188), (21.875, 2249), (14.0625, 2288), (20.3125, 2300), (15.625, 2314), (28.125, 2315), (18.75, 2347), (17.1875, 2360), (29.6875, 2476), (31.25, 2756), (32.8125, 2992), (34.375, 3319), (35.9375, 3672)] arg_min reach at : 25.0 with value = 2127 | arg_min : 25.0 min_score : 2127{11.25: 6815, 12.65625: 6505, 14.0625: 5928, 15.46875: 5326, 16.875: 4772, 18.28125: 4095, 19.6875: 3413, 21.09375: 2728, 22.5: 2127, 23.90625: 1694, 25.3125: 1345, 26.71875: 1048, 28.125: 823, 29.53125: 728, 30.9375: 714, 32.34375: 1027} [(30.9375, 714), (29.53125, 728), (28.125, 823), (32.34375, 1027), (26.71875, 1048), (25.3125, 1345), (23.90625, 1694), (22.5, 2127), (21.09375, 2728), (19.6875, 3413), (18.28125, 4095), (16.875, 4772), (15.46875, 5326), (14.0625, 5928), (12.65625, 6505), (11.25, 6815)] arg_min reach at : 30.9375 with value = 714 | arg_min : 30.9375 min_score : 714{12.5: 1275, 14.0625: 1207, 15.625: 1132, 17.1875: 1049, 18.75: 966, 20.3125: 866, 21.875: 784, 23.4375: 729, 25.0: 714, 26.5625: 976, 28.125: 1546, 29.6875: 2147, 31.25: 2981, 32.8125: 3767, 34.375: 4761, 35.9375: 5732} [(25.0, 714), (23.4375, 729), (21.875, 784), (20.3125, 866), (18.75, 966), (26.5625, 976), (17.1875, 1049), (15.625, 1132), (14.0625, 1207), (12.5, 1275), (28.125, 1546), (29.6875, 2147), (31.25, 2981), (32.8125, 3767), (34.375, 4761), (35.9375, 5732)] arg_min reach at : 25.0 with value = 714 | arg_min : 25.0 min_score : 714{0.5: 20107, 0.55: 18155, 0.6000000000000001: 16503, 0.65: 15058, 0.7000000000000001: 13673, 0.75: 12474, 0.8: 11100, 0.8500000000000001: 9667, 0.9: 8374, 0.9500000000000001: 7344, 1.0: 6274, 1.05: 5570, 1.1: 4846, 1.1500000000000001: 4170, 1.2000000000000002: 3623, 1.25: 3211, 1.3: 2832, 1.35: 2475, 1.4000000000000001: 2182, 1.4500000000000002: 1949, 1.5: 1655, 1.55: 1513, 1.6: 1333, 1.6500000000000001: 1182, 1.7000000000000002: 1038, 1.75: 921, 1.8: 841, 1.85: 732, 1.9000000000000001: 733, 1.9500000000000002: 714} [(1.9500000000000002, 714), (1.85, 732), (1.9000000000000001, 733), (1.8, 841), (1.75, 921), (1.7000000000000002, 1038), (1.6500000000000001, 1182), (1.6, 1333), (1.55, 1513), (1.5, 1655), (1.4500000000000002, 1949), (1.4000000000000001, 2182), (1.35, 2475), (1.3, 2832), (1.25, 3211), (1.2000000000000002, 3623), (1.1500000000000001, 4170), (1.1, 4846), (1.05, 5570), (1.0, 6274), (0.9500000000000001, 7344), (0.9, 8374), (0.8500000000000001, 9667), (0.8, 11100), (0.75, 12474), (0.7000000000000001, 13673), (0.65, 15058), (0.6000000000000001, 16503), (0.55, 18155), (0.5, 20107)] arg_min reach at : 1.9500000000000002 with value = 714 arg_min : 1.9500000000000002 min_score : 714{-90.0: 2866, -85.0: 3006, -80.0: 3063, -75.0: 3168, -70.0: 3193, -65.0: 3193, -60.0: 3149, -55.0: 3022, -50.0: 2885, -45.0: 2656, -40.0: 2413, -35.0: 2119, -30.0: 1819, -25.0: 1500, -20.0: 1171, -15.0: 865, -10.0: 714, -5.0: 668, 0.0: 689, 5.0: 734, 10.0: 824, 15.0: 898, 20.0: 1116, 25.0: 1368, 30.0: 1610, 35.0: 1866, 40.0: 2105, 45.0: 2304, 50.0: 2467, 55.0: 2604, 60.0: 2731, 65.0: 2753, 70.0: 2753, 75.0: 2761, 80.0: 2722, 85.0: 2786} [(-5.0, 668), (0.0, 689), (-10.0, 714), (5.0, 734), (10.0, 824), (-15.0, 865), (15.0, 898), (20.0, 1116), (-20.0, 1171), (25.0, 1368), (-25.0, 1500), (30.0, 1610), (-30.0, 1819), (35.0, 1866), (40.0, 2105), (-35.0, 2119), (45.0, 2304), (-40.0, 2413), (50.0, 2467), (55.0, 2604), (-45.0, 2656), (80.0, 2722), (60.0, 2731), (65.0, 2753), (70.0, 2753), (75.0, 2761), (85.0, 2786), (-90.0, 2866), (-50.0, 2885), (-85.0, 3006), (-55.0, 3022), (-80.0, 3063), (-60.0, 3149), (-75.0, 3168), (-70.0, 3193), (-65.0, 3193)] arg_min reach at : -5.0 with value = 668 arg_min : -5.0 min_score : 668{12.5: 1164, 14.0625: 1082, 15.625: 1019, 17.1875: 933, 18.75: 866, 20.3125: 765, 21.875: 713, 23.4375: 655, 25.0: 668, 26.5625: 845, 28.125: 1107, 29.6875: 1374, 31.25: 1691, 32.8125: 2036, 34.375: 2375, 35.9375: 2731} [(23.4375, 655), (25.0, 668), (21.875, 713), (20.3125, 765), (26.5625, 845), (18.75, 866), (17.1875, 933), (15.625, 1019), (14.0625, 1082), (28.125, 1107), (12.5, 1164), (29.6875, 1374), (31.25, 1691), (32.8125, 2036), (34.375, 2375), (35.9375, 2731)] arg_min reach at : 23.4375 with value = 655 arg_min : 23.4375 min_score : 655{11.25: 7209, 12.65625: 6826, 14.0625: 6195, 15.46875: 5638, 16.875: 4941, 18.28125: 4177, 19.6875: 3484, 21.09375: 2750, 22.5: 2183, 23.90625: 1709, 25.3125: 1327, 26.71875: 1008, 28.125: 779, 29.53125: 631, 30.9375: 655, 32.34375: 920} [(29.53125, 631), (30.9375, 655), (28.125, 779), (32.34375, 920), (26.71875, 1008), (25.3125, 1327), (23.90625, 1709), (22.5, 2183), (21.09375, 2750), (19.6875, 3484), (18.28125, 4177), (16.875, 4941), (15.46875, 5638), (14.0625, 6195), (12.65625, 6826), (11.25, 7209)] arg_min reach at : 29.53125 with value = 631 arg_min : 29.53125 min_score : 631{12.5: 1282, 14.0625: 1211, 15.625: 1130, 17.1875: 1050, 18.75: 960, 20.3125: 871, 21.875: 772, 23.4375: 672, 25.0: 631, 26.5625: 666, 28.125: 947, 29.6875: 1472, 31.25: 2184, 32.8125: 3032, 34.375: 3932, 35.9375: 5005} [(25.0, 631), (26.5625, 666), (23.4375, 672), (21.875, 772), (20.3125, 871), (28.125, 947), (18.75, 960), (17.1875, 1050), (15.625, 1130), (14.0625, 1211), (12.5, 1282), (29.6875, 1472), (31.25, 2184), (32.8125, 3032), (34.375, 3932), (35.9375, 5005)] arg_min reach at : 25.0 with value = 631 arg_min : 25.0 min_score : 631 yc : 29.53125 xc : 23.4375 angle : -5.0 radius : 25.0 excentricity : 1.9500000000000002 yc : 29.53125 xc : 23.4375 angle : -5.0 radius : 25.0 excentricity : 1.9500000000000002 x0 : 411 y1 : 480 width : 34, height : 37, area : 1258, score : 1.0 x0 : 419 y1 : 483 width : 26, height : 49, area : 1274, score : 1.0 Now saving polygons points : 1| batch 1 Loaded 2 chid ids of type : 520 + CHI and polygons saved ! (55, 54) (54, 51) [55, 54] (55, 54) score : 4603 strategy_opt : 5| strategy_opt : [('excentricity', [0.5, 2.0, 0.05]), ('angle', [-90.0, 90.0, 5.0]), ('xc', [12.75, 38.25, 1.59375]), ('yc', [13.5, 40.5, 1.6875]), ('radius', [13.5, 40.5, 1.6875])] {0.5: 14831, 0.55: 12756, 0.6000000000000001: 10989, 0.65: 9469, 0.7000000000000001: 8158, 0.75: 7251, 0.8: 6254, 0.8500000000000001: 5559, 0.9: 5119, 0.9500000000000001: 4564, 1.0: 4072, 1.05: 3783, 1.1: 3496, 1.1500000000000001: 3342, 1.2000000000000002: 3228, 1.25: 3161, 1.3: 3127, 1.35: 3087, 1.4000000000000001: 3047, 1.4500000000000002: 3050, 1.5: 2990, 1.55: 2992, 1.6: 2992, 1.6500000000000001: 2985, 1.7000000000000002: 2988, 1.75: 2999, 1.8: 2994, 1.85: 2981, 1.9000000000000001: 3002, 1.9500000000000002: 2995} [(1.85, 2981), (1.6500000000000001, 2985), (1.7000000000000002, 2988), (1.5, 2990), (1.55, 2992), (1.6, 2992), (1.8, 2994), (1.9500000000000002, 2995), (1.75, 2999), (1.9000000000000001, 3002), (1.4000000000000001, 3047), (1.4500000000000002, 3050), (1.35, 3087), (1.3, 3127), (1.25, 3161), (1.2000000000000002, 3228), (1.1500000000000001, 3342), (1.1, 3496), (1.05, 3783), (1.0, 4072), (0.9500000000000001, 4564), (0.9, 5119), (0.8500000000000001, 5559), (0.8, 6254), (0.75, 7251), (0.7000000000000001, 8158), (0.65, 9469), (0.6000000000000001, 10989), (0.55, 12756), (0.5, 14831)] arg_min reach at : 1.85 with value = 2981 | arg_min : 1.85 min_score : 2981{-90.0: 1442, -85.0: 1411, -80.0: 1411, -75.0: 1423, -70.0: 1409, -65.0: 1428, -60.0: 1417, -55.0: 1385, -50.0: 1356, -45.0: 1374, -40.0: 1401, -35.0: 1501, -30.0: 1635, -25.0: 1772, -20.0: 1988, -15.0: 2183, -10.0: 2376, -5.0: 2552, 0.0: 2691, 5.0: 2860, 10.0: 2981, 15.0: 3063, 20.0: 3044, 25.0: 2938, 30.0: 2889, 35.0: 2865, 40.0: 2787, 45.0: 2694, 50.0: 2566, 55.0: 2452, 60.0: 2275, 65.0: 2055, 70.0: 1849, 75.0: 1731, 80.0: 1532, 85.0: 1466} [(-50.0, 1356), (-45.0, 1374), (-55.0, 1385), (-40.0, 1401), (-70.0, 1409), (-85.0, 1411), (-80.0, 1411), (-60.0, 1417), (-75.0, 1423), (-65.0, 1428), (-90.0, 1442), (85.0, 1466), (-35.0, 1501), (80.0, 1532), (-30.0, 1635), (75.0, 1731), (-25.0, 1772), (70.0, 1849), (-20.0, 1988), (65.0, 2055), (-15.0, 2183), (60.0, 2275), (-10.0, 2376), (55.0, 2452), (-5.0, 2552), (50.0, 2566), (0.0, 2691), (45.0, 2694), (40.0, 2787), (5.0, 2860), (35.0, 2865), (30.0, 2889), (25.0, 2938), (10.0, 2981), (20.0, 3044), (15.0, 3063)] arg_min reach at : -50.0 with value = 1356 | arg_min : -50.0 min_score : 1356{12.75: 3483, 14.34375: 3154, 15.9375: 2818, 17.53125: 2499, 19.125: 2212, 20.71875: 1992, 22.3125: 1750, 23.90625: 1554, 25.5: 1356, 27.09375: 1213, 28.6875: 1123, 30.28125: 1079, 31.875: 1312, 33.46875: 1586, 35.0625: 1971, 36.65625: 2464} [(30.28125, 1079), (28.6875, 1123), (27.09375, 1213), (31.875, 1312), (25.5, 1356), (23.90625, 1554), (33.46875, 1586), (22.3125, 1750), (35.0625, 1971), (20.71875, 1992), (19.125, 2212), (36.65625, 2464), (17.53125, 2499), (15.9375, 2818), (14.34375, 3154), (12.75, 3483)] arg_min reach at : 30.28125 with value = 1079 | arg_min : 30.28125 min_score : 1079{13.5: 1299, 15.1875: 1190, 16.875: 1129, 18.5625: 1073, 20.25: 1041, 21.9375: 1025, 23.625: 995, 25.3125: 1002, 27.0: 1079, 28.6875: 1280, 30.375: 1506, 32.0625: 1818, 33.75: 2218, 35.4375: 2606, 37.125: 3013, 38.8125: 3545} [(23.625, 995), (25.3125, 1002), (21.9375, 1025), (20.25, 1041), (18.5625, 1073), (27.0, 1079), (16.875, 1129), (15.1875, 1190), (28.6875, 1280), (13.5, 1299), (30.375, 1506), (32.0625, 1818), (33.75, 2218), (35.4375, 2606), (37.125, 3013), (38.8125, 3545)] arg_min reach at : 23.625 with value = 995 | arg_min : 23.625 min_score : 995{13.5: 1907, 15.1875: 1827, 16.875: 1734, 18.5625: 1635, 20.25: 1520, 21.9375: 1400, 23.625: 1268, 25.3125: 1139, 27.0: 995, 28.6875: 1081, 30.375: 1376, 32.0625: 1837, 33.75: 2365, 35.4375: 3034, 37.125: 3644, 38.8125: 4482} [(27.0, 995), (28.6875, 1081), (25.3125, 1139), (23.625, 1268), (30.375, 1376), (21.9375, 1400), (20.25, 1520), (18.5625, 1635), (16.875, 1734), (15.1875, 1827), (32.0625, 1837), (13.5, 1907), (33.75, 2365), (35.4375, 3034), (37.125, 3644), (38.8125, 4482)] arg_min reach at : 27.0 with value = 995 | arg_min : 27.0 min_score : 995{0.5: 16358, 0.55: 14291, 0.6000000000000001: 12544, 0.65: 11117, 0.7000000000000001: 9800, 0.75: 8586, 0.8: 7533, 0.8500000000000001: 6488, 0.9: 5599, 0.9500000000000001: 4779, 1.0: 4075, 1.05: 3520, 1.1: 3021, 1.1500000000000001: 2582, 1.2000000000000002: 2150, 1.25: 1820, 1.3: 1534, 1.35: 1347, 1.4000000000000001: 1219, 1.4500000000000002: 1130, 1.5: 1073, 1.55: 1037, 1.6: 998, 1.6500000000000001: 961, 1.7000000000000002: 981, 1.75: 984, 1.8: 995, 1.85: 995, 1.9000000000000001: 1023, 1.9500000000000002: 1058} [(1.6500000000000001, 961), (1.7000000000000002, 981), (1.75, 984), (1.8, 995), (1.85, 995), (1.6, 998), (1.9000000000000001, 1023), (1.55, 1037), (1.9500000000000002, 1058), (1.5, 1073), (1.4500000000000002, 1130), (1.4000000000000001, 1219), (1.35, 1347), (1.3, 1534), (1.25, 1820), (1.2000000000000002, 2150), (1.1500000000000001, 2582), (1.1, 3021), (1.05, 3520), (1.0, 4075), (0.9500000000000001, 4779), (0.9, 5599), (0.8500000000000001, 6488), (0.8, 7533), (0.75, 8586), (0.7000000000000001, 9800), (0.65, 11117), (0.6000000000000001, 12544), (0.55, 14291), (0.5, 16358)] arg_min reach at : 1.6500000000000001 with value = 961 arg_min : 1.6500000000000001 min_score : 961{-90.0: 906, -85.0: 871, -80.0: 858, -75.0: 866, -70.0: 852, -65.0: 864, -60.0: 855, -55.0: 853, -50.0: 961, -45.0: 1180, -40.0: 1412, -35.0: 1690, -30.0: 1959, -25.0: 2243, -20.0: 2484, -15.0: 2677, -10.0: 2820, -5.0: 2976, 0.0: 3039, 5.0: 3049, 10.0: 3098, 15.0: 3122, 20.0: 3061, 25.0: 2954, 30.0: 2845, 35.0: 2631, 40.0: 2417, 45.0: 2130, 50.0: 1863, 55.0: 1564, 60.0: 1439, 65.0: 1326, 70.0: 1220, 75.0: 1142, 80.0: 1056, 85.0: 986} [(-70.0, 852), (-55.0, 853), (-60.0, 855), (-80.0, 858), (-65.0, 864), (-75.0, 866), (-85.0, 871), (-90.0, 906), (-50.0, 961), (85.0, 986), (80.0, 1056), (75.0, 1142), (-45.0, 1180), (70.0, 1220), (65.0, 1326), (-40.0, 1412), (60.0, 1439), (55.0, 1564), (-35.0, 1690), (50.0, 1863), (-30.0, 1959), (45.0, 2130), (-25.0, 2243), (40.0, 2417), (-20.0, 2484), (35.0, 2631), (-15.0, 2677), (-10.0, 2820), (30.0, 2845), (25.0, 2954), (-5.0, 2976), (0.0, 3039), (5.0, 3049), (20.0, 3061), (10.0, 3098), (15.0, 3122)] arg_min reach at : -70.0 with value = 852 arg_min : -70.0 min_score : 852{12.75: 4966, 14.34375: 4695, 15.9375: 4364, 17.53125: 3945, 19.125: 3465, 20.71875: 2958, 22.3125: 2415, 23.90625: 1841, 25.5: 1295, 27.09375: 936, 28.6875: 847, 30.28125: 852, 31.875: 883, 33.46875: 997, 35.0625: 1322, 36.65625: 1859} [(28.6875, 847), (30.28125, 852), (31.875, 883), (27.09375, 936), (33.46875, 997), (25.5, 1295), (35.0625, 1322), (23.90625, 1841), (36.65625, 1859), (22.3125, 2415), (20.71875, 2958), (19.125, 3465), (17.53125, 3945), (15.9375, 4364), (14.34375, 4695), (12.75, 4966)] arg_min reach at : 28.6875 with value = 847 arg_min : 28.6875 min_score : 847{13.5: 1489, 15.1875: 1374, 16.875: 1244, 18.5625: 1126, 20.25: 996, 21.9375: 893, 23.625: 847, 25.3125: 933, 27.0: 1153, 28.6875: 1446, 30.375: 1827, 32.0625: 2217, 33.75: 2658, 35.4375: 3137, 37.125: 3653, 38.8125: 4142} [(23.625, 847), (21.9375, 893), (25.3125, 933), (20.25, 996), (18.5625, 1126), (27.0, 1153), (16.875, 1244), (15.1875, 1374), (28.6875, 1446), (13.5, 1489), (30.375, 1827), (32.0625, 2217), (33.75, 2658), (35.4375, 3137), (37.125, 3653), (38.8125, 4142)] arg_min reach at : 23.625 with value = 847 arg_min : 23.625 min_score : 847{13.5: 1870, 15.1875: 1783, 16.875: 1676, 18.5625: 1564, 20.25: 1442, 21.9375: 1302, 23.625: 1153, 25.3125: 997, 27.0: 847, 28.6875: 864, 30.375: 1163, 32.0625: 1613, 33.75: 2300, 35.4375: 3191, 37.125: 4251, 38.8125: 5356} [(27.0, 847), (28.6875, 864), (25.3125, 997), (23.625, 1153), (30.375, 1163), (21.9375, 1302), (20.25, 1442), (18.5625, 1564), (32.0625, 1613), (16.875, 1676), (15.1875, 1783), (13.5, 1870), (33.75, 2300), (35.4375, 3191), (37.125, 4251), (38.8125, 5356)] arg_min reach at : 27.0 with value = 847 arg_min : 27.0 min_score : 847 yc : 23.625 xc : 28.6875 angle : -70.0 radius : 27.0 excentricity : 1.6500000000000001 yc : 23.625 xc : 28.6875 angle : -70.0 radius : 27.0 excentricity : 1.6500000000000001 x0 : 103 y1 : 396 width : 35, height : 38, area : 1330, score : 1.0 x0 : 93 y1 : 396 width : 51, height : 36, area : 1836, score : 1.0 Now saving polygons points : 1| batch 1 Loaded 3 chid ids of type : 520 ++ CHI and polygons saved ! (57, 52) (52, 43) [57, 52] (57, 52) score : 7970 strategy_opt : 5| strategy_opt : [('excentricity', [0.5, 2.0, 0.05]), ('angle', [-90.0, 90.0, 5.0]), ('xc', [10.75, 32.25, 1.34375]), ('yc', [13.0, 39.0, 1.625]), ('radius', [13.0, 39.0, 1.625])] {0.5: 16167, 0.55: 14430, 0.6000000000000001: 12864, 0.65: 11529, 0.7000000000000001: 10346, 0.75: 9256, 0.8: 8418, 0.8500000000000001: 7609, 0.9: 6862, 0.9500000000000001: 6277, 1.0: 5482, 1.05: 4840, 1.1: 4264, 1.1500000000000001: 3773, 1.2000000000000002: 3275, 1.25: 2948, 1.3: 2727, 1.35: 2514, 1.4000000000000001: 2254, 1.4500000000000002: 2155, 1.5: 1986, 1.55: 1892, 1.6: 1846, 1.6500000000000001: 1782, 1.7000000000000002: 1717, 1.75: 1656, 1.8: 1641, 1.85: 1602, 1.9000000000000001: 1587, 1.9500000000000002: 1576} [(1.9500000000000002, 1576), (1.9000000000000001, 1587), (1.85, 1602), (1.8, 1641), (1.75, 1656), (1.7000000000000002, 1717), (1.6500000000000001, 1782), (1.6, 1846), (1.55, 1892), (1.5, 1986), (1.4500000000000002, 2155), (1.4000000000000001, 2254), (1.35, 2514), (1.3, 2727), (1.25, 2948), (1.2000000000000002, 3275), (1.1500000000000001, 3773), (1.1, 4264), (1.05, 4840), (1.0, 5482), (0.9500000000000001, 6277), (0.9, 6862), (0.8500000000000001, 7609), (0.8, 8418), (0.75, 9256), (0.7000000000000001, 10346), (0.65, 11529), (0.6000000000000001, 12864), (0.55, 14430), (0.5, 16167)] arg_min reach at : 1.9500000000000002 with value = 1576 | arg_min : 1.9500000000000002 min_score : 1576{-90.0: 2291, -85.0: 2369, -80.0: 2390, -75.0: 2401, -70.0: 2341, -65.0: 2390, -60.0: 2418, -55.0: 2445, -50.0: 2599, -45.0: 2701, -40.0: 2755, -35.0: 2787, -30.0: 2753, -25.0: 2678, -20.0: 2611, -15.0: 2478, -10.0: 2313, -5.0: 2098, 0.0: 1870, 5.0: 1702, 10.0: 1576, 15.0: 1422, 20.0: 1258, 25.0: 1061, 30.0: 872, 35.0: 752, 40.0: 632, 45.0: 677, 50.0: 872, 55.0: 1070, 60.0: 1274, 65.0: 1477, 70.0: 1637, 75.0: 1895, 80.0: 2049, 85.0: 2193} [(40.0, 632), (45.0, 677), (35.0, 752), (30.0, 872), (50.0, 872), (25.0, 1061), (55.0, 1070), (20.0, 1258), (60.0, 1274), (15.0, 1422), (65.0, 1477), (10.0, 1576), (70.0, 1637), (5.0, 1702), (0.0, 1870), (75.0, 1895), (80.0, 2049), (-5.0, 2098), (85.0, 2193), (-90.0, 2291), (-10.0, 2313), (-70.0, 2341), (-85.0, 2369), (-80.0, 2390), (-65.0, 2390), (-75.0, 2401), (-60.0, 2418), (-55.0, 2445), (-15.0, 2478), (-50.0, 2599), (-20.0, 2611), (-25.0, 2678), (-45.0, 2701), (-30.0, 2753), (-40.0, 2755), (-35.0, 2787)] arg_min reach at : 40.0 with value = 632 | arg_min : 40.0 min_score : 632{10.75: 982, 12.09375: 841, 13.4375: 751, 14.78125: 672, 16.125: 624, 17.46875: 599, 18.8125: 575, 20.15625: 561, 21.5: 632, 22.84375: 895, 24.1875: 1257, 25.53125: 1708, 26.875: 2192, 28.21875: 2686, 29.5625: 3202, 30.90625: 3701} [(20.15625, 561), (18.8125, 575), (17.46875, 599), (16.125, 624), (21.5, 632), (14.78125, 672), (13.4375, 751), (12.09375, 841), (22.84375, 895), (10.75, 982), (24.1875, 1257), (25.53125, 1708), (26.875, 2192), (28.21875, 2686), (29.5625, 3202), (30.90625, 3701)] arg_min reach at : 20.15625 with value = 561 | arg_min : 20.15625 min_score : 561{13.0: 3254, 14.625: 2871, 16.25: 2436, 17.875: 1977, 19.5: 1474, 21.125: 1071, 22.75: 835, 24.375: 629, 26.0: 561, 27.625: 716, 29.25: 937, 30.875: 1286, 32.5: 1738, 34.125: 2226, 35.75: 2782, 37.375: 3291} [(26.0, 561), (24.375, 629), (27.625, 716), (22.75, 835), (29.25, 937), (21.125, 1071), (30.875, 1286), (19.5, 1474), (32.5, 1738), (17.875, 1977), (34.125, 2226), (16.25, 2436), (35.75, 2782), (14.625, 2871), (13.0, 3254), (37.375, 3291)] arg_min reach at : 26.0 with value = 561 | arg_min : 26.0 min_score : 561{13.0: 1371, 14.625: 1301, 16.25: 1217, 17.875: 1127, 19.5: 1028, 21.125: 926, 22.75: 811, 24.375: 683, 26.0: 561, 27.625: 624, 29.25: 1026, 30.875: 1508, 32.5: 2147, 34.125: 2981, 35.75: 3949, 37.375: 5069} [(26.0, 561), (27.625, 624), (24.375, 683), (22.75, 811), (21.125, 926), (29.25, 1026), (19.5, 1028), (17.875, 1127), (16.25, 1217), (14.625, 1301), (13.0, 1371), (30.875, 1508), (32.5, 2147), (34.125, 2981), (35.75, 3949), (37.375, 5069)] arg_min reach at : 26.0 with value = 561 | arg_min : 26.0 min_score : 561{0.5: 13327, 0.55: 12420, 0.6000000000000001: 11540, 0.65: 10560, 0.7000000000000001: 9652, 0.75: 8782, 0.8: 7834, 0.8500000000000001: 7061, 0.9: 6294, 0.9500000000000001: 5633, 1.0: 4916, 1.05: 4424, 1.1: 3865, 1.1500000000000001: 3323, 1.2000000000000002: 2817, 1.25: 2401, 1.3: 1935, 1.35: 1600, 1.4000000000000001: 1218, 1.4500000000000002: 1019, 1.5: 834, 1.55: 693, 1.6: 614, 1.6500000000000001: 568, 1.7000000000000002: 549, 1.75: 529, 1.8: 520, 1.85: 521, 1.9000000000000001: 534, 1.9500000000000002: 561} [(1.8, 520), (1.85, 521), (1.75, 529), (1.9000000000000001, 534), (1.7000000000000002, 549), (1.9500000000000002, 561), (1.6500000000000001, 568), (1.6, 614), (1.55, 693), (1.5, 834), (1.4500000000000002, 1019), (1.4000000000000001, 1218), (1.35, 1600), (1.3, 1935), (1.25, 2401), (1.2000000000000002, 2817), (1.1500000000000001, 3323), (1.1, 3865), (1.05, 4424), (1.0, 4916), (0.9500000000000001, 5633), (0.9, 6294), (0.8500000000000001, 7061), (0.8, 7834), (0.75, 8782), (0.7000000000000001, 9652), (0.65, 10560), (0.6000000000000001, 11540), (0.55, 12420), (0.5, 13327)] arg_min reach at : 1.8 with value = 520 arg_min : 1.8 min_score : 520{-90.0: 2114, -85.0: 2268, -80.0: 2343, -75.0: 2405, -70.0: 2409, -65.0: 2435, -60.0: 2467, -55.0: 2514, -50.0: 2590, -45.0: 2654, -40.0: 2632, -35.0: 2610, -30.0: 2565, -25.0: 2526, -20.0: 2435, -15.0: 2330, -10.0: 2181, -5.0: 2013, 0.0: 1792, 5.0: 1584, 10.0: 1389, 15.0: 1208, 20.0: 1038, 25.0: 843, 30.0: 673, 35.0: 564, 40.0: 520, 45.0: 597, 50.0: 764, 55.0: 963, 60.0: 1158, 65.0: 1390, 70.0: 1573, 75.0: 1800, 80.0: 1969, 85.0: 2070} [(40.0, 520), (35.0, 564), (45.0, 597), (30.0, 673), (50.0, 764), (25.0, 843), (55.0, 963), (20.0, 1038), (60.0, 1158), (15.0, 1208), (10.0, 1389), (65.0, 1390), (70.0, 1573), (5.0, 1584), (0.0, 1792), (75.0, 1800), (80.0, 1969), (-5.0, 2013), (85.0, 2070), (-90.0, 2114), (-10.0, 2181), (-85.0, 2268), (-15.0, 2330), (-80.0, 2343), (-75.0, 2405), (-70.0, 2409), (-65.0, 2435), (-20.0, 2435), (-60.0, 2467), (-55.0, 2514), (-25.0, 2526), (-30.0, 2565), (-50.0, 2590), (-35.0, 2610), (-40.0, 2632), (-45.0, 2654)] arg_min reach at : 40.0 with value = 520 arg_min : 40.0 min_score : 520{10.75: 1004, 12.09375: 902, 13.4375: 775, 14.78125: 655, 16.125: 580, 17.46875: 515, 18.8125: 494, 20.15625: 520, 21.5: 692, 22.84375: 1028, 24.1875: 1466, 25.53125: 2001, 26.875: 2490, 28.21875: 3027, 29.5625: 3629, 30.90625: 4163} [(18.8125, 494), (17.46875, 515), (20.15625, 520), (16.125, 580), (14.78125, 655), (21.5, 692), (13.4375, 775), (12.09375, 902), (10.75, 1004), (22.84375, 1028), (24.1875, 1466), (25.53125, 2001), (26.875, 2490), (28.21875, 3027), (29.5625, 3629), (30.90625, 4163)] arg_min reach at : 18.8125 with value = 494 arg_min : 18.8125 min_score : 494{13.0: 3121, 14.625: 2763, 16.25: 2397, 17.875: 1962, 19.5: 1409, 21.125: 1056, 22.75: 809, 24.375: 589, 26.0: 494, 27.625: 635, 29.25: 987, 30.875: 1406, 32.5: 1937, 34.125: 2442, 35.75: 2987, 37.375: 3537} [(26.0, 494), (24.375, 589), (27.625, 635), (22.75, 809), (29.25, 987), (21.125, 1056), (30.875, 1406), (19.5, 1409), (32.5, 1937), (17.875, 1962), (16.25, 2397), (34.125, 2442), (14.625, 2763), (35.75, 2987), (13.0, 3121), (37.375, 3537)] arg_min reach at : 26.0 with value = 494 arg_min : 26.0 min_score : 494{13.0: 1347, 14.625: 1266, 16.25: 1182, 17.875: 1086, 19.5: 979, 21.125: 865, 22.75: 737, 24.375: 616, 26.0: 494, 27.625: 559, 29.25: 954, 30.875: 1524, 32.5: 2347, 34.125: 3350, 35.75: 4468, 37.375: 5635} [(26.0, 494), (27.625, 559), (24.375, 616), (22.75, 737), (21.125, 865), (29.25, 954), (19.5, 979), (17.875, 1086), (16.25, 1182), (14.625, 1266), (13.0, 1347), (30.875, 1524), (32.5, 2347), (34.125, 3350), (35.75, 4468), (37.375, 5635)] arg_min reach at : 26.0 with value = 494 arg_min : 26.0 min_score : 494 yc : 26.0 xc : 18.8125 angle : 40.0 radius : 26.0 excentricity : 1.8 yc : 26.0 xc : 18.8125 angle : 40.0 radius : 26.0 excentricity : 1.8 x0 : 104 y1 : 292 width : 27, height : 36, area : 972, score : 1.0 x0 : 102 y1 : 288 width : 39, height : 43, area : 1677, score : 1.0 Now saving polygons points : 1| batch 1 Loaded 4 chid ids of type : 520 +++ CHI and polygons saved ! ['temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0_varroa_with_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0_varroa_with_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0_varroa_with_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0_ellipsebest.jpg', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0_varroa_with_ellipsebest.jpg'] About to upload 8 photos upload in portfolio : 27233551 Result OK ! uploaded one batch 0 Elapsed time : 23.8804669380188 After datou_step_exec type output : time spend for datou_step_exec : 29.69848656654358 time spend to save output : 2.5987625122070312e-05 total time spend for step 1 : 29.6985125541687 step2:tile Thu Sep 25 17:03:50 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : ['temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg'] We expect there is only one output and this part is used while all output are not tuple or array We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : [('temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg',)] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg': 937852786, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg': 1386158747, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg': 1386158750, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg': 1386158751, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg': 1386158752} map_photo_id_path_extension : {937852786: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg', 'extension': 'jpg'}, 1386158747: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg'}, 1386158750: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg'}, 1386158751: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg'}, 1386158752: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg'}} map_subphoto_mainphoto : {1386158747: 937852786, 1386158750: 937852786, 1386158751: 937852786, 1386158752: 937852786} verbose : True param_json : {'photo_tile_type': 17, 'whiten': True, 'remove_crop_border': True, 'minimal_size_crop_border': 900, 'stride': 240, 'crop_hashtag_type_tiled': 521, 'ETA': 86400, 'new_width': 480, 'new_height': 480, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'tile_taggage_varroa', 'crop_hashtag_type': 520, 'host': 'www.fotonower.com', 'arg_aux_upload': {'type_upload': 'python'}} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {520: 521} TO DEPRECATE VR 14-6-18 map_filenames : {937852786: 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 0 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 937852786,937852786) and `type` in (520) Loaded 4 chid ids of type : 520 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975216075,3975216076,3975216077,3975216078) ++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975216075,3975216076,3975216077,3975216078) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975216075,3975216076,3975216077,3975216078) created feed_id_new_photos : 27233585 with name tile_taggage_varroa feed_id_new_photos : 27233585 filename : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg photo_id : 937852786 height_image_input : 480 width_image_input : 480 new_width : 480 new_height : 480 stride : 240 stride_relative : 0.1 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 4 list_bib_to_crops : 1 [(0, 480, 0, 480, 0)] calcul des nouveaux crops pour le tile x0:0,x1:480,y0:0,y1:480 calcul avec la methode originale calcul avec la methode originale calcul avec la methode originale calcul avec la methode originale chi selectionnes : [, , , ] new_crops_tiles : 1 crop_transformed : 4 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) [(937852786, 2090988864, 17, 0, 480, 0, 480, 1.0)] list_photo_ids_cropped : [937852786] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 937852786) and `type` in (17) Loaded 1 chid ids of type : 17 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (8165084) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (8165084) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (8165084) treat the image : temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg , 0 before upload mediasElapsed time : 0.011754989624023438 on upload les photos avec python init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812638_3157952 batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (480, 480, 50498, 1386158995, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 93921586, 'jpg', UNHEX('345879d5145933efcce16bd1d96b81a8')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `mtr_user_id`, `created_at`) VALUES (27233585, 1386158995, 0, NOW()) 1 we have uploaded 1 photos in the portfolio 27233585 Importing ! upload mediasElapsed time : 0.5831120014190674 , 0insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [(8165084, 1386158995, 0)] Saving 4 CHIs. list_chi_tile : [": {'photo_id': 1386158995, 'hashtag_id': 2087736828, 'type': 521, 'x0': 432, 'x1': 467, 'y0': 303, 'y1': 355, 'score': 1.0, 'id': 0, 'points': ['463,352,452,353,439,350,426,342,418,333,417,325,422,319,433,318,446,321,459,328,467,338,469,346', '463,352,452,353,439,350,426,342,418,333,417,325,422,319,433,318,446,321,459,328,467,338,469,346'], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', 'sum_segment': 0}", ": {'photo_id': 1386158995, 'hashtag_id': 2087736828, 'type': 521, 'x0': 419, 'x1': 445, 'y0': 434, 'y1': 480, 'score': 1.0, 'id': 0, 'points': ['451,461,449,467,441,473,429,477,416,477,406,473,402,467,403,461,411,455,423,451,435,452,446,455', '451,461,449,467,441,473,429,477,416,477,406,473,402,467,403,461,411,455,423,451,435,452,446,455'], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', 'sum_segment': 0}", ": {'photo_id': 1386158995, 'hashtag_id': 2087736828, 'type': 521, 'x0': 93, 'x1': 144, 'y0': 360, 'y1': 396, 'score': 1.0, 'id': 0, 'points': ['112,359,120,350,130,348,137,351,141,361,140,374,134,387,126,396,117,399,109,395,105,385,106,372', '112,359,120,350,130,348,137,351,141,361,140,374,134,387,126,396,117,399,109,395,105,385,106,372'], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', 'sum_segment': 0}", ": {'photo_id': 1386158995, 'hashtag_id': 2087736828, 'type': 521, 'x0': 102, 'x1': 141, 'y0': 245, 'y1': 288, 'score': 1.0, 'id': 0, 'points': ['124,293,112,290,102,281,95,271,93,262,96,255,105,254,116,257,127,266,134,276,136,285,132,292', '124,293,112,290,102,281,95,271,93,262,96,255,105,254,116,257,127,266,134,276,136,285,132,292'], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', 'sum_segment': 0}"] insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 4 chid ids of type : 521 INSERT IGNORE INTO MTRPhoto.crop_polygon_points (`crop_hashtag_id`, `points`) VALUES (%s, %s) Number RLEs to save : 0 INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! end of tileElapsed time : 0.6588654518127441 map_pid_results : {'1386158995': ['temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg']} After datou_step_exec type output : time spend for datou_step_exec : 8.64267611503601 time spend to save output : 4.935264587402344e-05 total time spend for step 2 : 8.642725467681885 step3:rotate Thu Sep 25 17:03:58 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'1386158995': ['temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg']} input_args_next_step : {'1386158995': ()} output_args : {'1386158995': ['temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg']} args : 1386158995 depend.output_id : 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ('temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg',) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg': 937852786, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg': 1386158747, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg': 1386158750, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg': 1386158751, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg': 1386158752, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg': 1386158995} map_photo_id_path_extension : {937852786: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg', 'extension': 'jpg'}, 1386158747: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0.jpg'}, 1386158750: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0.jpg'}, 1386158751: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0.jpg'}, 1386158752: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0.jpg'}, 1386158995: {'path': 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg'}} map_subphoto_mainphoto : {1386158747: 937852786, 1386158750: 937852786, 1386158751: 937852786, 1386158752: 937852786, 1386158995: 937852786} Beginning of datou_step_rotate ! Warning, new_feed_id is empty ! We are in a datou with depends ! rotate photos of 0,15,30,45,60,75,90,105,120,135,150,165,180,195,210,225,240,255,270,285,300,315,330,345 degres batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1386158995) and `type` in (521) Loaded 4 chid ids of type : 521 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975216125,3975216126,3975216124,3975216123) ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975216123. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975216124. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975216125. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975216126. Ignored now SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975216125,3975216126,3975216124,3975216123) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975216125,3975216126,3975216124,3975216123) map_chi : {1386158995: [, , , ]} feed_id_new_photos : 27233588 photo_id in download_rotate_and_save : 1386158995 list_chi_loc : 4 Use all angle ! Rotation of photo 1386158995 of 0 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 0 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 1. 0.] [-0. 1.]] 0 [[ 1. 0.] [-0. 1.]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003399848937988281 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0016665458679199219 .time for calcul the mask position with numpy : 0.00042319297790527344 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0013692378997802734 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 2 list_crops_rotate : : {'photo_id': -1, 'hashtag_id': 2087736828, 'type': 529, 'x0': 25, 'x1': 61, 'y0': 268, 'y1': 319, 'score': 1.0, 'id': None, 'points': ['32,279,40,270,50,268,57,271,61,281,60,294,54,307,46,316,37,319,29,315,25,305,26,292'], 'sub_photo_id': 0, 'rles': [(-1, 48, 268, 4), (-1, 43, 269, 11), (-1, 40, 270, 16), (-1, 39, 271, 19), (-1, 38, 272, 20), (-1, 37, 273, 22), (-1, 36, 274, 23), (-1, 36, 275, 24), (-1, 35, 276, 25), (-1, 34, 277, 26), (-1, 33, 278, 28), (-1, 32, 279, 29), (-1, 32, 280, 30), (-1, 31, 281, 31), (-1, 31, 282, 31), (-1, 30, 283, 32), (-1, 30, 284, 32), (-1, 29, 285, 33), (-1, 29, 286, 33), (-1, 28, 287, 34), (-1, 28, 288, 33), (-1, 27, 289, 34), (-1, 27, 290, 34), (-1, 26, 291, 35), (-1, 26, 292, 35), (-1, 26, 293, 35), (-1, 26, 294, 35), (-1, 26, 295, 35), (-1, 26, 296, 34), (-1, 26, 297, 34), (-1, 26, 298, 33), (-1, 25, 299, 34), (-1, 25, 300, 33), (-1, 25, 301, 33), (-1, 25, 302, 32), (-1, 25, 303, 32), (-1, 25, 304, 31), (-1, 25, 305, 31), (-1, 25, 306, 30), (-1, 26, 307, 29), (-1, 26, 308, 28), (-1, 27, 309, 26), (-1, 27, 310, 25), (-1, 27, 311, 24), (-1, 28, 312, 23), (-1, 28, 313, 22), (-1, 29, 314, 20), (-1, 29, 315, 19), (-1, 31, 316, 16), (-1, 33, 317, 12), (-1, 35, 318, 7), (-1, 37, 319, 2)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -1, 'hashtag_id': 2087736828, 'type': 529, 'x0': 13, 'x1': 56, 'y0': 174, 'y1': 213, 'score': 1.0, 'id': None, 'points': ['44,213,32,210,22,201,15,191,13,182,16,175,25,174,36,177,47,186,54,196,56,205,52,212'], 'sub_photo_id': 0, 'rles': [(-1, 21, 174, 6), (-1, 16, 175, 15), (-1, 16, 176, 19), (-1, 15, 177, 22), (-1, 15, 178, 23), (-1, 14, 179, 26), (-1, 14, 180, 27), (-1, 13, 181, 29), (-1, 13, 182, 30), (-1, 13, 183, 31), (-1, 13, 184, 33), (-1, 14, 185, 33), (-1, 14, 186, 34), (-1, 14, 187, 35), (-1, 14, 188, 35), (-1, 15, 189, 35), (-1, 15, 190, 36), (-1, 15, 191, 36), (-1, 16, 192, 36), (-1, 16, 193, 37), (-1, 17, 194, 37), (-1, 18, 195, 36), (-1, 18, 196, 37), (-1, 19, 197, 36), (-1, 20, 198, 35), (-1, 21, 199, 35), (-1, 21, 200, 35), (-1, 22, 201, 34), (-1, 23, 202, 33), (-1, 24, 203, 33), (-1, 25, 204, 32), (-1, 26, 205, 31), (-1, 28, 206, 28), (-1, 29, 207, 27), (-1, 30, 208, 25), (-1, 31, 209, 24), (-1, 32, 210, 22), (-1, 35, 211, 19), (-1, 39, 212, 14), (-1, 43, 213, 6)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 15 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 15 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.96592583 0.25881905] [-0.25881905 0.96592583]] 15 [[ 0.96592583 0.25881905] [-0.25881905 0.96592583]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00038313865661621094 nb_pixel_total : 694 time to create 1 rle with old method : 0.0011355876922607422 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003497600555419922 nb_pixel_total : 1162 time to create 1 rle with old method : 0.001996755599975586 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -2, 'hashtag_id': 2087736828, 'type': 529, 'x0': 24, 'x1': 72, 'y0': 209, 'y1': 242, 'score': 1.0, 'id': None, 'points': ['62,241,50,242,38,236,28,228,24,220,25,212,34,209,45,209,58,215,67,222,72,231,70,238'], 'sub_photo_id': 0, 'rles': [(-1, 33, 209, 3), (-1, 37, 209, 9), (-1, 30, 210, 18), (-1, 49, 210, 1), (-1, 30, 211, 21), (-1, 26, 212, 27), (-1, 26, 213, 29), (-1, 26, 214, 32), (-1, 25, 215, 35), (-1, 25, 216, 36), (-1, 25, 217, 37), (-1, 25, 218, 38), (-1, 24, 219, 40), (-1, 25, 220, 40), (-1, 25, 221, 42), (-1, 25, 222, 43), (-1, 26, 223, 43), (-1, 27, 224, 42), (-1, 27, 225, 43), (-1, 28, 226, 43), (-1, 29, 227, 42), (-1, 29, 228, 42), (-1, 30, 229, 43), (-1, 30, 230, 43), (-1, 32, 231, 41), (-1, 33, 232, 39), (-1, 34, 233, 39), (-1, 36, 234, 36), (-1, 37, 235, 35), (-1, 38, 236, 34), (-1, 40, 237, 32), (-1, 42, 238, 30), (-1, 43, 239, 28), (-1, 46, 240, 22), (-1, 48, 241, 19), (-1, 50, 242, 15)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 30 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 30 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.8660254 0.5 ] [-0.5 0.8660254]] 30 [[ 0.8660254 0.5 ] [-0.5 0.8660254]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0005528926849365234 nb_pixel_total : 221 time to create 1 rle with old method : 0.00042700767517089844 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0005307197570800781 nb_pixel_total : 1155 time to create 1 rle with old method : 0.002094745635986328 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -3, 'hashtag_id': 2087736828, 'type': 529, 'x0': 44, 'x1': 93, 'y0': 238, 'y1': 268, 'score': 1.0, 'id': None, 'points': ['86,264,74,268,61,265,50,260,44,253,43,245,50,240,61,237,75,239,87,245,93,251,93,259'], 'sub_photo_id': 0, 'rles': [(-1, 59, 238, 9), (-1, 55, 239, 17), (-1, 73, 239, 1), (-1, 51, 240, 27), (-1, 49, 241, 30), (-1, 48, 242, 34), (-1, 48, 243, 36), (-1, 46, 244, 40), (-1, 45, 245, 43), (-1, 44, 246, 45), (-1, 44, 247, 46), (-1, 44, 248, 47), (-1, 44, 249, 48), (-1, 44, 250, 49), (-1, 44, 251, 50), (-1, 44, 252, 50), (-1, 44, 253, 50), (-1, 45, 254, 49), (-1, 45, 255, 49), (-1, 47, 256, 47), (-1, 48, 257, 46), (-1, 48, 258, 46), (-1, 50, 259, 44), (-1, 51, 260, 43), (-1, 52, 261, 41), (-1, 54, 262, 37), (-1, 56, 263, 35), (-1, 59, 264, 31), (-1, 60, 265, 28), (-1, 63, 266, 21), (-1, 67, 267, 2), (-1, 70, 267, 11), (-1, 74, 268, 3)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 45 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 45 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.70710678 0.70710678] [-0.70710678 0.70710678]] 45 [[ 0.70710678 0.70710678] [-0.70710678 0.70710678]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003788471221923828 nb_pixel_total : 143 time to create 1 rle with old method : 0.0002562999725341797 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00035643577575683594 nb_pixel_total : 1161 time to create 1 rle with old method : 0.001500844955444336 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -4, 'hashtag_id': 2087736828, 'type': 529, 'x0': 69, 'x1': 121, 'y0': 258, 'y1': 286, 'score': 1.0, 'id': None, 'points': ['115,279,105,285,91,286,79,284,72,279,69,272,74,265,84,259,98,258,110,260,118,265,120,273'], 'sub_photo_id': 0, 'rles': [(-1, 96, 258, 5), (-1, 88, 259, 17), (-1, 84, 260, 26), (-1, 111, 260, 1), (-1, 82, 261, 31), (-1, 81, 262, 34), (-1, 78, 263, 38), (-1, 77, 264, 42), (-1, 75, 265, 45), (-1, 74, 266, 46), (-1, 73, 267, 47), (-1, 72, 268, 48), (-1, 72, 269, 49), (-1, 71, 270, 50), (-1, 70, 271, 51), (-1, 69, 272, 53), (-1, 70, 273, 52), (-1, 70, 274, 51), (-1, 70, 275, 50), (-1, 71, 276, 48), (-1, 71, 277, 49), (-1, 72, 278, 47), (-1, 71, 279, 47), (-1, 72, 280, 45), (-1, 73, 281, 41), (-1, 76, 282, 37), (-1, 77, 283, 34), (-1, 79, 284, 31), (-1, 82, 285, 25), (-1, 85, 286, 21)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 60 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 60 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.5 0.8660254] [-0.8660254 0.5 ]] 60 [[ 0.5 0.8660254] [-0.8660254 0.5 ]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003848075866699219 nb_pixel_total : 414 time to create 1 rle with old method : 0.0005686283111572266 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003571510314941406 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0014564990997314453 . crop are not in the shrunk photo ! On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -5, 'hashtag_id': 2087736828, 'type': 529, 'x0': 102, 'x1': 152, 'y0': 269, 'y1': 300, 'score': 1.0, 'id': None, 'points': ['148,286,140,295,127,299,115,300,106,297,101,291,105,283,113,275,126,270,139,268,147,271,151,278'], 'sub_photo_id': 0, 'rles': [(-1, 132, 269, 1), (-1, 135, 269, 6), (-1, 126, 270, 18), (-1, 124, 271, 24), (-1, 121, 272, 28), (-1, 118, 273, 32), (-1, 116, 274, 34), (-1, 113, 275, 38), (-1, 112, 276, 39), (-1, 111, 277, 41), (-1, 111, 278, 42), (-1, 109, 279, 44), (-1, 108, 280, 44), (-1, 108, 281, 44), (-1, 106, 282, 45), (-1, 105, 283, 47), (-1, 105, 284, 46), (-1, 104, 285, 46), (-1, 104, 286, 46), (-1, 104, 287, 45), (-1, 104, 288, 44), (-1, 103, 289, 44), (-1, 103, 290, 43), (-1, 102, 291, 43), (-1, 102, 292, 42), (-1, 103, 293, 41), (-1, 104, 294, 38), (-1, 104, 295, 37), (-1, 105, 296, 33), (-1, 106, 297, 28), (-1, 107, 298, 27), (-1, 111, 299, 19), (-1, 112, 300, 1), (-1, 114, 300, 9)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 75 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 75 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.25881905 0.96592583] [-0.96592583 0.25881905]] 75 [[ 0.25881905 0.96592583] [-0.96592583 0.25881905]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0004382133483886719 nb_pixel_total : 1204 time to create 1 rle with old method : 0.0014345645904541016 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00033926963806152344 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0014629364013671875 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003256797790527344 nb_pixel_total : 264 time to create 1 rle with old method : 0.00043272972106933594 On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -6, 'hashtag_id': 2087736828, 'type': 529, 'x0': 138, 'x1': 183, 'y0': 271, 'y1': 308, 'score': 1.0, 'id': None, 'points': ['182,285,176,295,164,303,153,307,144,306,138,302,139,293,145,283,156,275,168,270,177,271,183,277'], 'sub_photo_id': 0, 'rles': [(-1, 168, 271, 10), (-1, 165, 272, 14), (-1, 162, 273, 18), (-1, 160, 274, 22), (-1, 157, 275, 25), (-1, 155, 276, 28), (-1, 154, 277, 30), (-1, 153, 278, 31), (-1, 152, 279, 32), (-1, 150, 280, 33), (-1, 148, 281, 36), (-1, 148, 282, 36), (-1, 146, 283, 38), (-1, 145, 284, 38), (-1, 144, 285, 39), (-1, 144, 286, 39), (-1, 143, 287, 39), (-1, 143, 288, 38), (-1, 142, 289, 39), (-1, 141, 290, 40), (-1, 141, 291, 38), (-1, 140, 292, 39), (-1, 140, 293, 39), (-1, 139, 294, 39), (-1, 139, 295, 38), (-1, 139, 296, 38), (-1, 139, 297, 36), (-1, 139, 298, 35), (-1, 139, 299, 33), (-1, 139, 300, 32), (-1, 138, 301, 32), (-1, 138, 302, 30), (-1, 139, 303, 27), (-1, 140, 304, 25), (-1, 142, 305, 19), (-1, 143, 306, 17), (-1, 143, 307, 14), (-1, 150, 308, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 90 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 90 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] 90 [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003962516784667969 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0017616748809814453 .time for calcul the mask position with numpy : 0.00034737586975097656 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0014376640319824219 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 2 list_crops_rotate : : {'photo_id': -7, 'hashtag_id': 2087736828, 'type': 529, 'x0': 268, 'x1': 319, 'y0': 258, 'y1': 294, 'score': 1.0, 'id': None, 'points': ['279,287,270,279,268,269,271,262,281,258,294,259,307,265,316,273,319,282,315,290,305,294,292,293'], 'sub_photo_id': 0, 'rles': [(-1, 280, 258, 8), (-1, 278, 259, 18), (-1, 275, 260, 23), (-1, 273, 261, 27), (-1, 271, 262, 31), (-1, 271, 263, 33), (-1, 270, 264, 36), (-1, 270, 265, 38), (-1, 269, 266, 40), (-1, 269, 267, 41), (-1, 268, 268, 43), (-1, 268, 269, 45), (-1, 268, 270, 46), (-1, 268, 271, 47), (-1, 269, 272, 47), (-1, 269, 273, 48), (-1, 269, 274, 48), (-1, 269, 275, 49), (-1, 269, 276, 49), (-1, 270, 277, 48), (-1, 270, 278, 49), (-1, 270, 279, 49), (-1, 271, 280, 48), (-1, 272, 281, 48), (-1, 273, 282, 47), (-1, 274, 283, 45), (-1, 276, 284, 43), (-1, 277, 285, 41), (-1, 278, 286, 40), (-1, 279, 287, 38), (-1, 281, 288, 36), (-1, 283, 289, 33), (-1, 285, 290, 31), (-1, 287, 291, 27), (-1, 289, 292, 23), (-1, 291, 293, 18), (-1, 299, 294, 8)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -7, 'hashtag_id': 2087736828, 'type': 529, 'x0': 174, 'x1': 213, 'y0': 263, 'y1': 306, 'score': 1.0, 'id': None, 'points': ['213,275,210,287,201,297,191,304,182,306,175,303,174,294,177,283,186,272,196,265,205,263,212,267'], 'sub_photo_id': 0, 'rles': [(-1, 203, 263, 3), (-1, 199, 264, 9), (-1, 196, 265, 14), (-1, 194, 266, 18), (-1, 193, 267, 20), (-1, 192, 268, 21), (-1, 190, 269, 23), (-1, 189, 270, 24), (-1, 187, 271, 27), (-1, 186, 272, 28), (-1, 185, 273, 29), (-1, 184, 274, 30), (-1, 184, 275, 30), (-1, 183, 276, 31), (-1, 182, 277, 31), (-1, 181, 278, 32), (-1, 180, 279, 33), (-1, 179, 280, 34), (-1, 179, 281, 33), (-1, 178, 282, 34), (-1, 177, 283, 35), (-1, 177, 284, 35), (-1, 176, 285, 35), (-1, 176, 286, 35), (-1, 176, 287, 35), (-1, 176, 288, 34), (-1, 175, 289, 34), (-1, 175, 290, 33), (-1, 175, 291, 32), (-1, 175, 292, 31), (-1, 174, 293, 32), (-1, 174, 294, 31), (-1, 174, 295, 30), (-1, 174, 296, 29), (-1, 174, 297, 28), (-1, 174, 298, 27), (-1, 175, 299, 24), (-1, 175, 300, 23), (-1, 175, 301, 22), (-1, 175, 302, 20), (-1, 175, 303, 19), (-1, 177, 304, 15), (-1, 179, 305, 10), (-1, 181, 306, 4)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 105 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 105 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.25881905 0.96592583] [-0.96592583 -0.25881905]] 105 [[-0.25881905 0.96592583] [-0.96592583 -0.25881905]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00041365623474121094 nb_pixel_total : 694 time to create 1 rle with old method : 0.0010190010070800781 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0004425048828125 nb_pixel_total : 1162 time to create 1 rle with old method : 0.0015370845794677734 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -8, 'hashtag_id': 2087736828, 'type': 529, 'x0': 209, 'x1': 242, 'y0': 248, 'y1': 296, 'score': 1.0, 'id': None, 'points': ['241,257,242,269,236,281,228,291,220,295,212,294,209,285,209,274,215,261,222,252,231,247,238,249'], 'sub_photo_id': 0, 'rles': [(-1, 229, 248, 3), (-1, 233, 248, 1), (-1, 229, 249, 10), (-1, 226, 250, 14), (-1, 225, 251, 15), (-1, 223, 252, 17), (-1, 222, 253, 19), (-1, 221, 254, 21), (-1, 221, 255, 21), (-1, 220, 256, 23), (-1, 219, 257, 24), (-1, 218, 258, 25), (-1, 217, 259, 26), (-1, 216, 260, 27), (-1, 215, 261, 28), (-1, 215, 262, 28), (-1, 214, 263, 29), (-1, 214, 264, 29), (-1, 214, 265, 29), (-1, 213, 266, 30), (-1, 213, 267, 30), (-1, 212, 268, 31), (-1, 212, 269, 31), (-1, 211, 270, 32), (-1, 210, 271, 32), (-1, 211, 272, 31), (-1, 210, 273, 31), (-1, 210, 274, 31), (-1, 209, 275, 31), (-1, 209, 276, 31), (-1, 209, 277, 31), (-1, 209, 278, 30), (-1, 209, 279, 29), (-1, 209, 280, 29), (-1, 209, 281, 28), (-1, 209, 282, 28), (-1, 209, 283, 27), (-1, 210, 284, 25), (-1, 209, 285, 25), (-1, 209, 286, 25), (-1, 209, 287, 24), (-1, 210, 288, 22), (-1, 210, 289, 21), (-1, 210, 290, 21), (-1, 212, 291, 17), (-1, 212, 292, 15), (-1, 212, 293, 14), (-1, 212, 294, 12), (-1, 215, 295, 8), (-1, 219, 296, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 120 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 120 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.5 0.8660254] [-0.8660254 -0.5 ]] 120 [[-0.5 0.8660254] [-0.8660254 -0.5 ]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00044226646423339844 nb_pixel_total : 221 time to create 1 rle with old method : 0.0005936622619628906 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00045680999755859375 nb_pixel_total : 1155 time to create 1 rle with old method : 0.0023670196533203125 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -9, 'hashtag_id': 2087736828, 'type': 529, 'x0': 238, 'x1': 268, 'y0': 227, 'y1': 276, 'score': 1.0, 'id': None, 'points': ['264,233,268,245,265,258,260,269,253,275,245,276,240,269,237,258,239,244,245,232,251,226,259,226'], 'sub_photo_id': 0, 'rles': [(-1, 251, 227, 10), (-1, 250, 228, 12), (-1, 249, 229, 13), (-1, 248, 230, 16), (-1, 247, 231, 18), (-1, 246, 232, 19), (-1, 245, 233, 21), (-1, 245, 234, 21), (-1, 244, 235, 22), (-1, 244, 236, 22), (-1, 243, 237, 24), (-1, 243, 238, 24), (-1, 242, 239, 25), (-1, 242, 240, 26), (-1, 242, 241, 26), (-1, 241, 242, 27), (-1, 240, 243, 28), (-1, 240, 244, 29), (-1, 240, 245, 29), (-1, 240, 246, 29), (-1, 239, 247, 29), (-1, 240, 248, 28), (-1, 239, 249, 29), (-1, 239, 250, 29), (-1, 239, 251, 28), (-1, 239, 252, 29), (-1, 238, 253, 30), (-1, 238, 254, 29), (-1, 238, 255, 29), (-1, 238, 256, 29), (-1, 238, 257, 29), (-1, 238, 258, 28), (-1, 238, 259, 28), (-1, 238, 260, 28), (-1, 238, 261, 27), (-1, 239, 262, 25), (-1, 239, 263, 25), (-1, 239, 264, 25), (-1, 239, 265, 24), (-1, 240, 266, 23), (-1, 240, 267, 22), (-1, 240, 268, 22), (-1, 240, 269, 21), (-1, 241, 270, 19), (-1, 241, 271, 18), (-1, 242, 272, 17), (-1, 244, 273, 13), (-1, 244, 274, 12), (-1, 245, 275, 11), (-1, 246, 276, 8)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 135 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 135 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.70710678 0.70710678] [-0.70710678 -0.70710678]] 135 [[-0.70710678 0.70710678] [-0.70710678 -0.70710678]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003857612609863281 nb_pixel_total : 143 time to create 1 rle with old method : 0.0003211498260498047 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003559589385986328 nb_pixel_total : 1160 time to create 1 rle with old method : 0.0019404888153076172 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -10, 'hashtag_id': 2087736828, 'type': 529, 'x0': 258, 'x1': 286, 'y0': 199, 'y1': 251, 'score': 1.0, 'id': None, 'points': ['279,204,285,214,286,228,284,240,279,247,272,250,265,245,259,235,258,221,260,209,265,201,273,199'], 'sub_photo_id': 0, 'rles': [(-1, 272, 199, 2), (-1, 269, 200, 6), (-1, 265, 201, 1), (-1, 267, 201, 9), (-1, 277, 201, 1), (-1, 264, 202, 15), (-1, 264, 203, 16), (-1, 264, 204, 17), (-1, 263, 205, 18), (-1, 262, 206, 19), (-1, 262, 207, 20), (-1, 261, 208, 22), (-1, 260, 209, 23), (-1, 261, 210, 23), (-1, 260, 211, 25), (-1, 260, 212, 25), (-1, 260, 213, 25), (-1, 260, 214, 26), (-1, 260, 215, 27), (-1, 259, 216, 28), (-1, 259, 217, 28), (-1, 259, 218, 28), (-1, 259, 219, 28), (-1, 258, 220, 29), (-1, 258, 221, 29), (-1, 258, 222, 29), (-1, 258, 223, 29), (-1, 258, 224, 29), (-1, 259, 225, 28), (-1, 259, 226, 28), (-1, 259, 227, 28), (-1, 259, 228, 28), (-1, 259, 229, 28), (-1, 259, 230, 28), (-1, 259, 231, 28), (-1, 259, 232, 28), (-1, 260, 233, 27), (-1, 260, 234, 27), (-1, 260, 235, 27), (-1, 260, 236, 26), (-1, 261, 237, 25), (-1, 261, 238, 25), (-1, 262, 239, 23), (-1, 263, 240, 22), (-1, 263, 241, 22), (-1, 263, 242, 21), (-1, 264, 243, 20), (-1, 265, 244, 18), (-1, 265, 245, 17), (-1, 266, 246, 16), (-1, 267, 247, 15), (-1, 268, 248, 13), (-1, 270, 249, 8), (-1, 279, 249, 1), (-1, 271, 250, 5), (-1, 272, 251, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 150 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 150 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.8660254 0.5 ] [-0.5 -0.8660254]] 150 [[-0.8660254 0.5 ] [-0.5 -0.8660254]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00036644935607910156 nb_pixel_total : 414 time to create 1 rle with old method : 0.0007386207580566406 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003666877746582031 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0019474029541015625 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.00032782554626464844 nb_pixel_total : 1 time to create 1 rle with old method : 1.9550323486328125e-05 len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -11, 'hashtag_id': 2087736828, 'type': 529, 'x0': 269, 'x1': 300, 'y0': 168, 'y1': 218, 'score': 1.0, 'id': None, 'points': ['286,171,295,179,299,192,300,204,297,213,291,218,283,214,275,206,270,193,268,180,271,172,278,168'], 'sub_photo_id': 0, 'rles': [(-1, 278, 168, 2), (-1, 277, 169, 5), (-1, 283, 169, 1), (-1, 275, 170, 10), (-1, 273, 171, 14), (-1, 272, 172, 16), (-1, 271, 173, 18), (-1, 271, 174, 19), (-1, 271, 175, 20), (-1, 271, 176, 21), (-1, 270, 177, 24), (-1, 270, 178, 24), (-1, 270, 179, 25), (-1, 269, 180, 27), (-1, 269, 181, 27), (-1, 269, 182, 27), (-1, 269, 183, 28), (-1, 269, 184, 28), (-1, 269, 185, 28), (-1, 270, 186, 27), (-1, 270, 187, 29), (-1, 269, 188, 30), (-1, 270, 189, 29), (-1, 270, 190, 29), (-1, 270, 191, 30), (-1, 270, 192, 30), (-1, 270, 193, 30), (-1, 270, 194, 30), (-1, 271, 195, 29), (-1, 271, 196, 29), (-1, 272, 197, 28), (-1, 272, 198, 29), (-1, 272, 199, 29), (-1, 273, 200, 28), (-1, 273, 201, 28), (-1, 273, 202, 28), (-1, 274, 203, 27), (-1, 274, 204, 27), (-1, 275, 205, 26), (-1, 275, 206, 26), (-1, 275, 207, 25), (-1, 276, 208, 25), (-1, 277, 209, 23), (-1, 279, 210, 20), (-1, 279, 211, 20), (-1, 280, 212, 19), (-1, 282, 213, 17), (-1, 282, 214, 16), (-1, 283, 215, 14), (-1, 285, 216, 11), (-1, 289, 217, 5), (-1, 291, 218, 2)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 165 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 165 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.96592583 0.25881905] [-0.25881905 -0.96592583]] 165 [[-0.96592583 0.25881905] [-0.25881905 -0.96592583]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0004057884216308594 nb_pixel_total : 1204 time to create 1 rle with old method : 0.0021545886993408203 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.000347137451171875 nb_pixel_total : 1158 time to create 1 rle with old method : 0.001961946487426758 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003294944763183594 nb_pixel_total : 264 time to create 1 rle with old method : 0.0004661083221435547 On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -12, 'hashtag_id': 2087736828, 'type': 529, 'x0': 271, 'x1': 308, 'y0': 137, 'y1': 182, 'score': 1.0, 'id': None, 'points': ['285,137,295,143,303,155,307,166,306,175,302,181,293,180,283,174,275,163,270,151,271,142,277,136'], 'sub_photo_id': 0, 'rles': [(-1, 276, 137, 4), (-1, 281, 137, 3), (-1, 276, 138, 11), (-1, 274, 139, 14), (-1, 274, 140, 17), (-1, 273, 141, 18), (-1, 272, 142, 22), (-1, 271, 143, 24), (-1, 271, 144, 26), (-1, 271, 145, 26), (-1, 271, 146, 27), (-1, 271, 147, 28), (-1, 271, 148, 28), (-1, 271, 149, 29), (-1, 271, 150, 30), (-1, 271, 151, 31), (-1, 271, 152, 31), (-1, 272, 153, 31), (-1, 272, 154, 31), (-1, 272, 155, 32), (-1, 273, 156, 32), (-1, 273, 157, 32), (-1, 273, 158, 32), (-1, 274, 159, 31), (-1, 274, 160, 32), (-1, 275, 161, 32), (-1, 275, 162, 32), (-1, 275, 163, 32), (-1, 276, 164, 32), (-1, 276, 165, 32), (-1, 277, 166, 31), (-1, 278, 167, 30), (-1, 279, 168, 29), (-1, 280, 169, 28), (-1, 280, 170, 29), (-1, 281, 171, 27), (-1, 281, 172, 27), (-1, 283, 173, 25), (-1, 283, 174, 25), (-1, 284, 175, 24), (-1, 285, 176, 23), (-1, 287, 177, 21), (-1, 289, 178, 17), (-1, 290, 179, 15), (-1, 292, 180, 13), (-1, 294, 181, 10), (-1, 301, 182, 2)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 180 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 180 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] 180 [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00039696693420410156 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0023598670959472656 .time for calcul the mask position with numpy : 0.0003170967102050781 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0013852119445800781 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 2 list_crops_rotate : : {'photo_id': -13, 'hashtag_id': 2087736828, 'type': 529, 'x0': 258, 'x1': 294, 'y0': 1, 'y1': 52, 'score': 1.0, 'id': None, 'points': ['287,41,279,50,269,52,262,49,258,39,259,26,265,13,273,4,282,1,290,5,294,15,293,28'], 'sub_photo_id': 0, 'rles': [(-1, 281, 1, 2), (-1, 278, 2, 7), (-1, 275, 3, 12), (-1, 273, 4, 16), (-1, 272, 5, 19), (-1, 271, 6, 20), (-1, 270, 7, 22), (-1, 269, 8, 23), (-1, 269, 9, 24), (-1, 268, 10, 25), (-1, 267, 11, 26), (-1, 266, 12, 28), (-1, 265, 13, 29), (-1, 265, 14, 30), (-1, 264, 15, 31), (-1, 264, 16, 31), (-1, 263, 17, 32), (-1, 263, 18, 32), (-1, 262, 19, 33), (-1, 262, 20, 33), (-1, 261, 21, 34), (-1, 261, 22, 33), (-1, 260, 23, 34), (-1, 260, 24, 34), (-1, 259, 25, 35), (-1, 259, 26, 35), (-1, 259, 27, 35), (-1, 259, 28, 35), (-1, 259, 29, 35), (-1, 259, 30, 34), (-1, 259, 31, 34), (-1, 259, 32, 33), (-1, 258, 33, 34), (-1, 258, 34, 33), (-1, 258, 35, 33), (-1, 258, 36, 32), (-1, 258, 37, 32), (-1, 258, 38, 31), (-1, 258, 39, 31), (-1, 258, 40, 30), (-1, 259, 41, 29), (-1, 259, 42, 28), (-1, 260, 43, 26), (-1, 260, 44, 25), (-1, 260, 45, 24), (-1, 261, 46, 23), (-1, 261, 47, 22), (-1, 262, 48, 20), (-1, 262, 49, 19), (-1, 264, 50, 16), (-1, 266, 51, 11), (-1, 268, 52, 4)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -13, 'hashtag_id': 2087736828, 'type': 529, 'x0': 263, 'x1': 306, 'y0': 107, 'y1': 146, 'score': 1.0, 'id': None, 'points': ['275,107,287,110,297,119,304,129,306,138,303,145,294,146,283,143,272,134,265,124,263,115,267,108'], 'sub_photo_id': 0, 'rles': [(-1, 271, 107, 6), (-1, 267, 108, 14), (-1, 266, 109, 19), (-1, 266, 110, 22), (-1, 265, 111, 24), (-1, 265, 112, 25), (-1, 264, 113, 27), (-1, 264, 114, 28), (-1, 263, 115, 31), (-1, 263, 116, 32), (-1, 263, 117, 33), (-1, 264, 118, 33), (-1, 264, 119, 34), (-1, 264, 120, 35), (-1, 264, 121, 35), (-1, 265, 122, 35), (-1, 265, 123, 36), (-1, 265, 124, 37), (-1, 266, 125, 36), (-1, 266, 126, 37), (-1, 267, 127, 37), (-1, 268, 128, 36), (-1, 269, 129, 36), (-1, 269, 130, 36), (-1, 270, 131, 35), (-1, 271, 132, 35), (-1, 271, 133, 35), (-1, 272, 134, 34), (-1, 273, 135, 33), (-1, 274, 136, 33), (-1, 276, 137, 31), (-1, 277, 138, 30), (-1, 278, 139, 29), (-1, 279, 140, 27), (-1, 280, 141, 26), (-1, 282, 142, 23), (-1, 283, 143, 22), (-1, 285, 144, 19), (-1, 289, 145, 15), (-1, 293, 146, 6)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 195 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 195 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.96592583 -0.25881905] [ 0.25881905 -0.96592583]] 195 [[-0.96592583 -0.25881905] [ 0.25881905 -0.96592583]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00036406517028808594 nb_pixel_total : 727 time to create 1 rle with old method : 0.0008563995361328125 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.000339508056640625 nb_pixel_total : 1162 time to create 1 rle with old method : 0.0017199516296386719 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -14, 'hashtag_id': 2087736828, 'type': 529, 'x0': 248, 'x1': 296, 'y0': 78, 'y1': 111, 'score': 1.0, 'id': None, 'points': ['257,78,269,77,281,83,291,91,295,99,294,107,285,110,274,110,261,104,252,97,247,88,249,81'], 'sub_photo_id': 0, 'rles': [(-1, 256, 78, 15), (-1, 254, 79, 19), (-1, 253, 80, 22), (-1, 250, 81, 28), (-1, 249, 82, 30), (-1, 249, 83, 32), (-1, 249, 84, 34), (-1, 249, 85, 35), (-1, 249, 86, 36), (-1, 248, 87, 39), (-1, 249, 88, 39), (-1, 248, 89, 41), (-1, 248, 90, 43), (-1, 248, 91, 43), (-1, 250, 92, 42), (-1, 250, 93, 42), (-1, 250, 94, 43), (-1, 251, 95, 43), (-1, 252, 96, 42), (-1, 252, 97, 43), (-1, 253, 98, 43), (-1, 254, 99, 42), (-1, 256, 100, 40), (-1, 257, 101, 40), (-1, 258, 102, 38), (-1, 259, 103, 37), (-1, 260, 104, 36), (-1, 261, 105, 35), (-1, 263, 106, 32), (-1, 266, 107, 29), (-1, 268, 108, 27), (-1, 270, 109, 21), (-1, 271, 110, 1), (-1, 273, 110, 18), (-1, 275, 111, 9), (-1, 285, 111, 3)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 210 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 210 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.8660254 -0.5 ] [ 0.5 -0.8660254]] 210 [[-0.8660254 -0.5 ] [ 0.5 -0.8660254]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003750324249267578 nb_pixel_total : 250 time to create 1 rle with old method : 0.0003974437713623047 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.000339508056640625 nb_pixel_total : 1155 time to create 1 rle with old method : 0.0014743804931640625 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -15, 'hashtag_id': 2087736828, 'type': 529, 'x0': 227, 'x1': 276, 'y0': 52, 'y1': 82, 'score': 1.0, 'id': None, 'points': ['233,55,245,51,258,54,269,59,275,66,276,74,269,79,258,82,244,80,232,74,226,68,226,60'], 'sub_photo_id': 0, 'rles': [(-1, 244, 52, 3), (-1, 240, 53, 11), (-1, 252, 53, 2), (-1, 237, 54, 21), (-1, 233, 55, 28), (-1, 231, 56, 31), (-1, 230, 57, 35), (-1, 230, 58, 37), (-1, 228, 59, 41), (-1, 227, 60, 43), (-1, 227, 61, 44), (-1, 227, 62, 46), (-1, 227, 63, 46), (-1, 227, 64, 47), (-1, 227, 65, 49), (-1, 227, 66, 49), (-1, 227, 67, 50), (-1, 227, 68, 50), (-1, 227, 69, 50), (-1, 228, 70, 49), (-1, 229, 71, 48), (-1, 230, 72, 47), (-1, 231, 73, 46), (-1, 232, 74, 45), (-1, 233, 75, 43), (-1, 235, 76, 40), (-1, 237, 77, 36), (-1, 239, 78, 34), (-1, 242, 79, 30), (-1, 243, 80, 27), (-1, 247, 81, 1), (-1, 249, 81, 17), (-1, 253, 82, 9)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 225 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 225 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.70710678 -0.70710678] [ 0.70710678 -0.70710678]] 225 [[-0.70710678 -0.70710678] [ 0.70710678 -0.70710678]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00037479400634765625 nb_pixel_total : 169 time to create 1 rle with old method : 0.00031256675720214844 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00032067298889160156 nb_pixel_total : 1161 time to create 1 rle with old method : 0.0013432502746582031 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -16, 'hashtag_id': 2087736828, 'type': 529, 'x0': 199, 'x1': 251, 'y0': 34, 'y1': 62, 'score': 1.0, 'id': None, 'points': ['204,40,214,34,228,33,240,35,247,40,250,47,245,54,235,60,221,61,209,59,201,54,199,46'], 'sub_photo_id': 0, 'rles': [(-1, 215, 34, 21), (-1, 214, 35, 25), (-1, 211, 36, 31), (-1, 210, 37, 34), (-1, 208, 38, 37), (-1, 207, 39, 41), (-1, 204, 40, 45), (-1, 203, 41, 47), (-1, 202, 42, 47), (-1, 201, 43, 49), (-1, 202, 44, 48), (-1, 201, 45, 50), (-1, 200, 46, 51), (-1, 199, 47, 52), (-1, 199, 48, 53), (-1, 200, 49, 51), (-1, 200, 50, 50), (-1, 200, 51, 49), (-1, 201, 52, 48), (-1, 201, 53, 47), (-1, 201, 54, 46), (-1, 201, 55, 45), (-1, 202, 56, 42), (-1, 205, 57, 38), (-1, 206, 58, 34), (-1, 208, 59, 31), (-1, 209, 60, 1), (-1, 211, 60, 26), (-1, 216, 61, 17), (-1, 220, 62, 5)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 240 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 240 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.5 -0.8660254] [ 0.8660254 -0.5 ]] 240 [[-0.5 -0.8660254] [ 0.8660254 -0.5 ]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0004341602325439453 nb_pixel_total : 450 time to create 1 rle with old method : 0.0008502006530761719 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00041365623474121094 nb_pixel_total : 1159 time to create 1 rle with old method : 0.002040863037109375 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.00037407875061035156 nb_pixel_total : 1 time to create 1 rle with old method : 2.2649765014648438e-05 len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -17, 'hashtag_id': 2087736828, 'type': 529, 'x0': 168, 'x1': 218, 'y0': 20, 'y1': 51, 'score': 1.0, 'id': None, 'points': ['171,33,179,24,192,20,204,19,213,22,218,28,214,36,206,44,193,49,180,51,172,48,168,41'], 'sub_photo_id': 0, 'rles': [(-1, 198, 20, 9), (-1, 208, 20, 1), (-1, 191, 21, 19), (-1, 187, 22, 27), (-1, 187, 23, 28), (-1, 183, 24, 33), (-1, 180, 25, 37), (-1, 179, 26, 38), (-1, 177, 27, 41), (-1, 177, 28, 42), (-1, 176, 29, 43), (-1, 175, 30, 43), (-1, 174, 31, 44), (-1, 173, 32, 44), (-1, 172, 33, 45), (-1, 171, 34, 46), (-1, 171, 35, 46), (-1, 170, 36, 46), (-1, 169, 37, 47), (-1, 170, 38, 45), (-1, 169, 39, 44), (-1, 169, 40, 44), (-1, 168, 41, 44), (-1, 168, 42, 42), (-1, 169, 43, 41), (-1, 170, 44, 39), (-1, 170, 45, 38), (-1, 171, 46, 34), (-1, 171, 47, 32), (-1, 172, 48, 28), (-1, 173, 49, 24), (-1, 177, 50, 18), (-1, 180, 51, 6), (-1, 188, 51, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 255 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 255 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-0.25881905 -0.96592583] [ 0.96592583 -0.25881905]] 255 [[-0.25881905 -0.96592583] [ 0.96592583 -0.25881905]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003688335418701172 nb_pixel_total : 1237 time to create 1 rle with old method : 0.0014574527740478516 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00032258033752441406 nb_pixel_total : 1158 time to create 1 rle with old method : 0.001355886459350586 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003075599670410156 nb_pixel_total : 234 time to create 1 rle with old method : 0.00030684471130371094 On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -18, 'hashtag_id': 2087736828, 'type': 529, 'x0': 137, 'x1': 182, 'y0': 12, 'y1': 49, 'score': 1.0, 'id': None, 'points': ['137,34,143,24,155,16,166,12,175,13,181,17,180,26,174,36,163,44,151,49,142,48,136,42'], 'sub_photo_id': 0, 'rles': [(-1, 170, 12, 1), (-1, 164, 13, 14), (-1, 161, 14, 17), (-1, 160, 15, 19), (-1, 156, 16, 25), (-1, 155, 17, 27), (-1, 153, 18, 30), (-1, 151, 19, 32), (-1, 150, 20, 32), (-1, 149, 21, 33), (-1, 147, 22, 35), (-1, 146, 23, 36), (-1, 144, 24, 38), (-1, 144, 25, 38), (-1, 143, 26, 39), (-1, 142, 27, 39), (-1, 142, 28, 39), (-1, 142, 29, 38), (-1, 140, 30, 40), (-1, 140, 31, 39), (-1, 140, 32, 38), (-1, 139, 33, 39), (-1, 138, 34, 39), (-1, 138, 35, 39), (-1, 138, 36, 38), (-1, 137, 37, 38), (-1, 137, 38, 36), (-1, 137, 39, 36), (-1, 138, 40, 33), (-1, 137, 41, 32), (-1, 137, 42, 31), (-1, 137, 43, 30), (-1, 137, 44, 29), (-1, 139, 45, 25), (-1, 139, 46, 22), (-1, 141, 47, 18), (-1, 142, 48, 14), (-1, 143, 49, 10)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 270 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 270 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] 270 [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003724098205566406 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0016207695007324219 .time for calcul the mask position with numpy : 0.00034165382385253906 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0013654232025146484 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 2 list_crops_rotate : : {'photo_id': -19, 'hashtag_id': 2087736828, 'type': 529, 'x0': 1, 'x1': 52, 'y0': 26, 'y1': 62, 'score': 1.0, 'id': None, 'points': ['41,32,50,40,52,50,49,57,39,61,26,60,13,54,4,46,1,37,5,29,15,25,28,26'], 'sub_photo_id': 0, 'rles': [(-1, 14, 26, 8), (-1, 12, 27, 18), (-1, 9, 28, 23), (-1, 7, 29, 27), (-1, 5, 30, 31), (-1, 5, 31, 33), (-1, 4, 32, 36), (-1, 4, 33, 38), (-1, 3, 34, 40), (-1, 3, 35, 41), (-1, 2, 36, 43), (-1, 2, 37, 45), (-1, 1, 38, 47), (-1, 1, 39, 48), (-1, 2, 40, 48), (-1, 2, 41, 49), (-1, 2, 42, 49), (-1, 3, 43, 48), (-1, 3, 44, 49), (-1, 3, 45, 49), (-1, 4, 46, 48), (-1, 4, 47, 48), (-1, 5, 48, 47), (-1, 6, 49, 47), (-1, 7, 50, 46), (-1, 8, 51, 45), (-1, 10, 52, 43), (-1, 11, 53, 41), (-1, 12, 54, 40), (-1, 13, 55, 38), (-1, 15, 56, 36), (-1, 17, 57, 33), (-1, 19, 58, 31), (-1, 21, 59, 27), (-1, 23, 60, 23), (-1, 25, 61, 18), (-1, 33, 62, 8)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -19, 'hashtag_id': 2087736828, 'type': 529, 'x0': 107, 'x1': 146, 'y0': 14, 'y1': 57, 'score': 1.0, 'id': None, 'points': ['107,44,110,32,119,22,129,15,138,13,144,16,145,25,143,36,134,47,124,54,115,56,108,52'], 'sub_photo_id': 0, 'rles': [(-1, 136, 14, 4), (-1, 132, 15, 10), (-1, 129, 16, 15), (-1, 127, 17, 19), (-1, 126, 18, 20), (-1, 124, 19, 22), (-1, 123, 20, 23), (-1, 122, 21, 24), (-1, 120, 22, 27), (-1, 119, 23, 28), (-1, 118, 24, 29), (-1, 117, 25, 30), (-1, 116, 26, 31), (-1, 115, 27, 32), (-1, 115, 28, 31), (-1, 114, 29, 32), (-1, 113, 30, 33), (-1, 112, 31, 34), (-1, 111, 32, 34), (-1, 110, 33, 35), (-1, 110, 34, 35), (-1, 110, 35, 35), (-1, 109, 36, 35), (-1, 109, 37, 35), (-1, 109, 38, 34), (-1, 109, 39, 33), (-1, 108, 40, 34), (-1, 108, 41, 33), (-1, 108, 42, 32), (-1, 108, 43, 31), (-1, 107, 44, 31), (-1, 107, 45, 30), (-1, 107, 46, 30), (-1, 107, 47, 29), (-1, 107, 48, 28), (-1, 107, 49, 27), (-1, 108, 50, 24), (-1, 108, 51, 23), (-1, 108, 52, 21), (-1, 108, 53, 20), (-1, 109, 54, 18), (-1, 111, 55, 14), (-1, 113, 56, 9), (-1, 115, 57, 3)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 285 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 285 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.25881905 -0.96592583] [ 0.96592583 0.25881905]] 285 [[ 0.25881905 -0.96592583] [ 0.96592583 0.25881905]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003426074981689453 nb_pixel_total : 727 time to create 1 rle with old method : 0.0008769035339355469 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00034356117248535156 nb_pixel_total : 1162 time to create 1 rle with old method : 0.0013797283172607422 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -20, 'hashtag_id': 2087736828, 'type': 529, 'x0': 78, 'x1': 111, 'y0': 24, 'y1': 72, 'score': 1.0, 'id': None, 'points': ['78,62,77,50,83,38,91,28,99,24,107,25,110,34,110,45,104,58,97,67,88,72,81,70'], 'sub_photo_id': 0, 'rles': [(-1, 101, 24, 1), (-1, 98, 25, 8), (-1, 97, 26, 12), (-1, 95, 27, 14), (-1, 94, 28, 15), (-1, 92, 29, 17), (-1, 90, 30, 21), (-1, 90, 31, 21), (-1, 89, 32, 22), (-1, 88, 33, 24), (-1, 87, 34, 25), (-1, 87, 35, 25), (-1, 86, 36, 25), (-1, 85, 37, 27), (-1, 84, 38, 28), (-1, 84, 39, 28), (-1, 83, 40, 29), (-1, 83, 41, 29), (-1, 82, 42, 30), (-1, 81, 43, 31), (-1, 81, 44, 31), (-1, 81, 45, 31), (-1, 80, 46, 31), (-1, 80, 47, 31), (-1, 79, 48, 31), (-1, 79, 49, 32), (-1, 78, 50, 32), (-1, 78, 51, 31), (-1, 78, 52, 31), (-1, 78, 53, 30), (-1, 78, 54, 30), (-1, 78, 55, 29), (-1, 78, 56, 29), (-1, 78, 57, 29), (-1, 78, 58, 28), (-1, 78, 59, 28), (-1, 78, 60, 27), (-1, 78, 61, 26), (-1, 78, 62, 25), (-1, 78, 63, 24), (-1, 78, 64, 23), (-1, 79, 65, 21), (-1, 79, 66, 21), (-1, 80, 67, 19), (-1, 81, 68, 17), (-1, 81, 69, 15), (-1, 81, 70, 14), (-1, 82, 71, 10), (-1, 87, 72, 1), (-1, 89, 72, 3)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 300 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 300 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.5 -0.8660254] [ 0.8660254 0.5 ]] 300 [[ 0.5 -0.8660254] [ 0.8660254 0.5 ]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0004222393035888672 nb_pixel_total : 250 time to create 1 rle with old method : 0.00038242340087890625 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003771781921386719 nb_pixel_total : 1155 time to create 1 rle with old method : 0.0014255046844482422 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -21, 'hashtag_id': 2087736828, 'type': 529, 'x0': 52, 'x1': 82, 'y0': 44, 'y1': 93, 'score': 1.0, 'id': None, 'points': ['55,86,51,74,54,61,59,50,66,44,74,43,79,50,82,61,80,75,74,87,68,93,60,93'], 'sub_photo_id': 0, 'rles': [(-1, 67, 44, 8), (-1, 65, 45, 11), (-1, 65, 46, 12), (-1, 64, 47, 13), (-1, 62, 48, 17), (-1, 62, 49, 18), (-1, 61, 50, 19), (-1, 60, 51, 21), (-1, 59, 52, 22), (-1, 59, 53, 22), (-1, 58, 54, 23), (-1, 58, 55, 24), (-1, 57, 56, 25), (-1, 57, 57, 25), (-1, 57, 58, 25), (-1, 56, 59, 27), (-1, 55, 60, 28), (-1, 55, 61, 28), (-1, 55, 62, 28), (-1, 54, 63, 29), (-1, 54, 64, 29), (-1, 54, 65, 29), (-1, 54, 66, 29), (-1, 53, 67, 30), (-1, 53, 68, 29), (-1, 54, 69, 28), (-1, 53, 70, 29), (-1, 53, 71, 29), (-1, 53, 72, 28), (-1, 53, 73, 29), (-1, 52, 74, 29), (-1, 52, 75, 29), (-1, 52, 76, 29), (-1, 53, 77, 28), (-1, 53, 78, 27), (-1, 53, 79, 26), (-1, 53, 80, 26), (-1, 54, 81, 25), (-1, 54, 82, 24), (-1, 54, 83, 24), (-1, 55, 84, 22), (-1, 55, 85, 22), (-1, 55, 86, 21), (-1, 55, 87, 21), (-1, 56, 88, 19), (-1, 56, 89, 18), (-1, 57, 90, 16), (-1, 59, 91, 13), (-1, 59, 92, 12), (-1, 60, 93, 10)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 315 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 315 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.70710678 -0.70710678] [ 0.70710678 0.70710678]] 315 [[ 0.70710678 -0.70710678] [ 0.70710678 0.70710678]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0003952980041503906 nb_pixel_total : 169 time to create 1 rle with old method : 0.0002865791320800781 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003681182861328125 nb_pixel_total : 1161 time to create 1 rle with old method : 0.002270936965942383 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -22, 'hashtag_id': 2087736828, 'type': 529, 'x0': 34, 'x1': 62, 'y0': 69, 'y1': 121, 'score': 1.0, 'id': None, 'points': ['40,115,34,105,33,91,35,79,40,72,47,69,54,74,60,84,61,98,59,110,54,118,46,120'], 'sub_photo_id': 0, 'rles': [(-1, 48, 69, 1), (-1, 45, 70, 5), (-1, 41, 71, 1), (-1, 43, 71, 8), (-1, 40, 72, 13), (-1, 39, 73, 15), (-1, 39, 74, 16), (-1, 39, 75, 17), (-1, 38, 76, 18), (-1, 37, 77, 20), (-1, 37, 78, 21), (-1, 36, 79, 22), (-1, 36, 80, 22), (-1, 36, 81, 23), (-1, 35, 82, 25), (-1, 35, 83, 25), (-1, 35, 84, 26), (-1, 34, 85, 27), (-1, 34, 86, 27), (-1, 34, 87, 27), (-1, 34, 88, 28), (-1, 34, 89, 28), (-1, 34, 90, 28), (-1, 34, 91, 28), (-1, 34, 92, 28), (-1, 34, 93, 28), (-1, 34, 94, 28), (-1, 34, 95, 28), (-1, 34, 96, 29), (-1, 34, 97, 29), (-1, 34, 98, 29), (-1, 34, 99, 29), (-1, 34, 100, 29), (-1, 34, 101, 28), (-1, 34, 102, 28), (-1, 34, 103, 28), (-1, 34, 104, 28), (-1, 34, 105, 27), (-1, 35, 106, 26), (-1, 36, 107, 25), (-1, 36, 108, 25), (-1, 36, 109, 25), (-1, 37, 110, 23), (-1, 38, 111, 23), (-1, 38, 112, 22), (-1, 39, 113, 20), (-1, 40, 114, 19), (-1, 40, 115, 18), (-1, 40, 116, 17), (-1, 41, 117, 16), (-1, 42, 118, 15), (-1, 43, 119, 1), (-1, 45, 119, 11), (-1, 46, 120, 6), (-1, 47, 121, 2)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 330 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 330 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.8660254 -0.5 ] [ 0.5 0.8660254]] 330 [[ 0.8660254 -0.5 ] [ 0.5 0.8660254]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.0004062652587890625 nb_pixel_total : 450 time to create 1 rle with old method : 0.0006227493286132812 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003771781921386719 nb_pixel_total : 1159 time to create 1 rle with old method : 0.001432180404663086 . crop are not in the shrunk photo ! On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -23, 'hashtag_id': 2087736828, 'type': 529, 'x0': 20, 'x1': 51, 'y0': 102, 'y1': 152, 'score': 1.0, 'id': None, 'points': ['33,148,24,140,20,127,19,115,22,106,28,101,36,105,44,113,49,126,51,139,48,147,41,151'], 'sub_photo_id': 0, 'rles': [(-1, 28, 102, 2), (-1, 27, 103, 5), (-1, 25, 104, 11), (-1, 24, 105, 14), (-1, 23, 106, 16), (-1, 22, 107, 17), (-1, 22, 108, 19), (-1, 22, 109, 20), (-1, 22, 110, 20), (-1, 21, 111, 23), (-1, 20, 112, 25), (-1, 21, 113, 25), (-1, 20, 114, 26), (-1, 20, 115, 26), (-1, 20, 116, 27), (-1, 20, 117, 27), (-1, 20, 118, 28), (-1, 20, 119, 28), (-1, 20, 120, 28), (-1, 20, 121, 29), (-1, 20, 122, 29), (-1, 21, 123, 28), (-1, 21, 124, 29), (-1, 21, 125, 29), (-1, 21, 126, 30), (-1, 21, 127, 30), (-1, 21, 128, 30), (-1, 21, 129, 30), (-1, 22, 130, 29), (-1, 22, 131, 29), (-1, 22, 132, 30), (-1, 22, 133, 29), (-1, 24, 134, 27), (-1, 24, 135, 28), (-1, 24, 136, 28), (-1, 24, 137, 28), (-1, 25, 138, 27), (-1, 25, 139, 27), (-1, 25, 140, 27), (-1, 26, 141, 25), (-1, 27, 142, 24), (-1, 27, 143, 24), (-1, 29, 144, 21), (-1, 30, 145, 20), (-1, 31, 146, 19), (-1, 32, 147, 18), (-1, 33, 148, 16), (-1, 34, 149, 14), (-1, 36, 150, 10), (-1, 37, 151, 1), (-1, 39, 151, 5), (-1, 41, 152, 2)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1386158995 of 345 degree temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0.jpg [, , , ] 345 remove_crop_border : True version de PIL : 9.5.0 Needs to change image size ! [[ 0.96592583 -0.25881905] [ 0.25881905 0.96592583]] 345 [[ 0.96592583 -0.25881905] [ 0.25881905 0.96592583]] shrink_image : True len(list_crops) : 4 time for calcul the mask position with numpy : 0.00048279762268066406 nb_pixel_total : 1237 time to create 1 rle with old method : 0.001598358154296875 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003364086151123047 nb_pixel_total : 1157 time to create 1 rle with old method : 0.013916492462158203 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.00033402442932128906 nb_pixel_total : 234 time to create 1 rle with old method : 0.00038909912109375 On the border Smaller than minimal size ! len(list_crops_rotate) : 1 list_crops_rotate : : {'photo_id': -24, 'hashtag_id': 2087736828, 'type': 529, 'x0': 12, 'x1': 49, 'y0': 138, 'y1': 183, 'score': 1.0, 'id': None, 'points': ['34,182,24,176,16,164,12,153,13,144,17,138,26,139,36,145,44,156,49,168,48,177,42,183'], 'sub_photo_id': 0, 'rles': [(-1, 18, 138, 2), (-1, 17, 139, 10), (-1, 16, 140, 13), (-1, 16, 141, 15), (-1, 15, 142, 17), (-1, 13, 143, 21), (-1, 13, 144, 23), (-1, 13, 145, 24), (-1, 13, 146, 25), (-1, 13, 147, 25), (-1, 13, 148, 27), (-1, 13, 149, 27), (-1, 12, 150, 29), (-1, 13, 151, 28), (-1, 13, 152, 29), (-1, 13, 153, 30), (-1, 13, 154, 31), (-1, 13, 155, 32), (-1, 13, 156, 32), (-1, 14, 157, 32), (-1, 14, 158, 32), (-1, 14, 159, 32), (-1, 15, 160, 32), (-1, 16, 161, 31), (-1, 16, 162, 32), (-1, 16, 163, 32), (-1, 16, 164, 32), (-1, 17, 165, 32), (-1, 18, 166, 31), (-1, 18, 167, 31), (-1, 19, 168, 31), (-1, 19, 169, 31), (-1, 20, 170, 30), (-1, 21, 171, 29), (-1, 22, 172, 28), (-1, 22, 173, 28), (-1, 23, 174, 27), (-1, 24, 175, 26), (-1, 24, 176, 26), (-1, 26, 177, 24), (-1, 27, 178, 22), (-1, 30, 179, 18), (-1, 30, 180, 17), (-1, 33, 181, 14), (-1, 34, 182, 11), (-1, 37, 183, 3), (-1, 41, 183, 3)], 'hashtag': '', 'sum_segment': 0} About to upload 24 photos upload in portfolio : 27233588 init cache_photo without model_param we have 24 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812642_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 24 photos in the portfolio 27233588 time of upload the photos Elapsed time : 8.966575622558594 map_filename_photo_id : 24 map_filename_photo_id : {'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_00.jpg': 1386159075, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_015.jpg': 1386159076, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_030.jpg': 1386159078, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_045.jpg': 1386159079, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_060.jpg': 1386159080, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_075.jpg': 1386159081, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_090.jpg': 1386159083, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0105.jpg': 1386159084, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0120.jpg': 1386159085, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0135.jpg': 1386159087, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0150.jpg': 1386159088, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0165.jpg': 1386159089, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0180.jpg': 1386159091, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0195.jpg': 1386159092, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0210.jpg': 1386159093, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0225.jpg': 1386159095, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0240.jpg': 1386159096, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0255.jpg': 1386159097, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0270.jpg': 1386159099, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0285.jpg': 1386159100, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0300.jpg': 1386159101, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0315.jpg': 1386159102, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0330.jpg': 1386159104, 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0345.jpg': 1386159105} Len new_chis : 24 Len list_new_chi_with_photo_id : 28 of type : 529 list_new_chi_with_photo_id : [, , , , , , , , , , , , , , , , , , , , , , , , , , , ] batch 1 Loaded 28 chid ids of type : 529 Number RLEs to save : 1197 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 13.622756004333496 time spend to save output : 0.00010418891906738281 total time spend for step 3 : 13.622860193252563 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [937852786, 937852786, '1386158995'] map_info['map_portfolio_photo'] : {} final : True mtd_id 243 list_pids : [937852786, 937852786, '1386158995'] Looping around the photos to save general results len do output : 24 /1386159075Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159076Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159078Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159079Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159080Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159081Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159083Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159084Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159085Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159087Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159088Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159089Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159091Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159092Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159093Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159095Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159096Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159097Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159099Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159100Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159101Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159102Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159104Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159105Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('243', None, None, None, None, None, None, None, None) ('243', None, '937852786', None, None, None, None, None, None) ('243', None, None, None, None, None, None, None, None) ('243', None, '937852786', None, None, None, None, None, None) ('243', None, None, None, None, None, None, None, None) ('243', None, '1386158995', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 75 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('243', None, '1386159075', 'None', None, None, None, None, None), ('243', None, '1386159076', 'None', None, None, None, None, None), ('243', None, '1386159078', 'None', None, None, None, None, None), ('243', None, '1386159079', 'None', None, None, None, None, None), ('243', None, '1386159080', 'None', None, None, None, None, None), ('243', None, '1386159081', 'None', None, None, None, None, None), ('243', None, '1386159083', 'None', None, None, None, None, None), ('243', None, '1386159084', 'None', None, None, None, None, None), ('243', None, '1386159085', 'None', None, None, None, None, None), ('243', None, '1386159087', 'None', None, None, None, None, None), ('243', None, '1386159088', 'None', None, None, None, None, None), ('243', None, '1386159089', 'None', None, None, None, None, None), ('243', None, '1386159091', 'None', None, None, None, None, None), ('243', None, '1386159092', 'None', None, None, None, None, None), ('243', None, '1386159093', 'None', None, None, None, None, None), ('243', None, '1386159095', 'None', None, None, None, None, None), ('243', None, '1386159096', 'None', None, None, None, None, None), ('243', None, '1386159097', 'None', None, None, None, None, None), ('243', None, '1386159099', 'None', None, None, None, None, None), ('243', None, '1386159100', 'None', None, None, None, None, None), ('243', None, '1386159101', 'None', None, None, None, None, None), ('243', None, '1386159102', 'None', None, None, None, None, None), ('243', None, '1386159104', 'None', None, None, None, None, None), ('243', None, '1386159105', 'None', None, None, None, None, None), ('243', None, '937852786', None, None, None, None, None, None), ('243', None, '1386158995', None, None, None, None, None, None)] time used for this insertion : 0.016652345657348633 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 3 output : {1386159075: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_00.jpg', [, ]], 1386159076: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_015.jpg', []], 1386159078: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_030.jpg', []], 1386159079: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_045.jpg', []], 1386159080: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_060.jpg', []], 1386159081: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_075.jpg', []], 1386159083: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_090.jpg', [, ]], 1386159084: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0105.jpg', []], 1386159085: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0120.jpg', []], 1386159087: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0135.jpg', []], 1386159088: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0150.jpg', []], 1386159089: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0165.jpg', []], 1386159091: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0180.jpg', [, ]], 1386159092: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0195.jpg', []], 1386159093: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0210.jpg', []], 1386159095: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0225.jpg', []], 1386159096: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0240.jpg', []], 1386159097: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0255.jpg', []], 1386159099: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0270.jpg', [, ]], 1386159100: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0285.jpg', []], 1386159101: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0300.jpg', []], 1386159102: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0315.jpg', []], 1386159104: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0330.jpg', []], 1386159105: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0345.jpg', []]} ret_da : {1386159075: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_00.jpg', [, ]], 1386159076: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_015.jpg', []], 1386159078: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_030.jpg', []], 1386159079: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_045.jpg', []], 1386159080: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_060.jpg', []], 1386159081: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_075.jpg', []], 1386159083: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_090.jpg', [, ]], 1386159084: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0105.jpg', []], 1386159085: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0120.jpg', []], 1386159087: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0135.jpg', []], 1386159088: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0150.jpg', []], 1386159089: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0165.jpg', []], 1386159091: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0180.jpg', [, ]], 1386159092: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0195.jpg', []], 1386159093: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0210.jpg', []], 1386159095: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0225.jpg', []], 1386159096: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0240.jpg', []], 1386159097: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0255.jpg', []], 1386159099: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0270.jpg', [, ]], 1386159100: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0285.jpg', []], 1386159101: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0300.jpg', []], 1386159102: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0315.jpg', []], 1386159104: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0330.jpg', []], 1386159105: ['937852786', 'temp/1758812600_3157952_937852786_7d9a231a08a1c63d0868e56a5361bf67_0345.jpg', []]} list chi : [[, ], [], [], [], [], [], [, ], [], [], [], [], [], [, ], [], [], [], [], [], [, ], [], [], [], [], []] ############################### TEST flip ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=571 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=571 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 571 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=571 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : flip list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (911785586) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 911785586 download finish for photo 911785586 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.165724515914917 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:flip Thu Sep 25 17:04:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big.jpg': 911785586} map_photo_id_path_extension : {911785586: {'path': 'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step_flip ! We are in a linear step without datou_depend ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 911785586) and `type` in (741) Loaded 6 chid ids of type : 741 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (18344206,18344211,18344210,18344209,18344208,18344207) +++++WARNING : Unexpected points, we should remove this data for chi_id : 18344210, for now we just ignore these empty polygon points +SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (18344206,18344211,18344210,18344209,18344208,18344207) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (18344206,18344211,18344210,18344209,18344208,18344207) map_chi_objs : {911785586: [, , , , , ]} photo_id in download_rotate_and_save : 911785586 list_chi_loc : 6 Vertical flip of photo 911785586 version de PIL : 9.5.0 vertically flipped image is saved in temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_vert.jpg Horizontal flip of photo 911785586 version de PIL : 9.5.0 horizontally flipped image is saved in temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_hori.jpg About to upload 2 photos upload in portfolio : 1090565 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812653_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 2 photos in the portfolio 1090565 time of upload the photos Elapsed time : 0.8838896751403809 map_filename_photo_id : 2 map_filename_photo_id : {'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_vert.jpg': 1386159122, 'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_hori.jpg': 1386159123} Len new_chis : 12 Len list_new_chi_with_photo_id : 12 of type : 741 list_new_chi_with_photo_id : [, , , , , , , , , , , ] insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 12 chid ids of type : 741 INSERT IGNORE INTO MTRPhoto.crop_polygon_points (`crop_hashtag_id`, `points`) VALUES (%s, %s) Number RLEs to save : 0 INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 0.9883711338043213 time spend to save output : 3.5762786865234375e-05 total time spend for step 1 : 0.9884068965911865 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : flip we use saveGeneral [911785586] map_info['map_portfolio_photo'] : {} final : True mtd_id 571 list_pids : [911785586] Looping around the photos to save general results len do output : 2 /1386159122 /1386159123 before output type Managing all output in save final without adding information in the mtr_datou_result ('571', None, None, None, None, None, None, None, None) ('571', None, '911785586', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('571', None, '911785586', None, None, None, None, None, None)] time used for this insertion : 0.014166831970214844 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1386159122': ['911785586', 'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_vert.jpg', [, , , , , ]], '1386159123': ['911785586', 'temp/1758812652_3157952_911785586_d8582feabcd359151ff718b5832248c7-big_flip_hori.jpg', [, , , , , ]]} ############################### TEST crop_rles ################################ # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! Unexpected type seems boolean for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : TEST CROP RLES Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=686 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=686 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 686 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=686 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : crop list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (950103132) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 950103132 download finish for photo 950103132 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.10719847679138184 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:crop Thu Sep 25 17:04:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00.jpg': 950103132} map_photo_id_path_extension : {950103132: {'path': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Crop ! param_json : {'photo_hashtag_type': 755, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'feed_id_new_photos': 0, 'host': 'www.fotonower.com', 'crop_type': 'rle', 'margin_relative': 0.1, 'min_score': 0.3, 'upload,type': 'python'} margin_type : margin_relative margin_value : [0.1, 0.1, 0.1, 0.1] Loading chi in step crop with photo_hashtag_type : 755 Loading chi in step crop for list_pids : 1 ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 950103132) and `type` in (755) and score>0.3 Loaded 8 chid ids of type : 755 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1947670931,1947670932,1947670933,1947670934,1947670935,1947670936,1947670937,1947670938) ++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947670931,1947670932,1947670933,1947670934,1947670935,1947670936,1947670937,1947670938) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1947670931,1947670932,1947670933,1947670934,1947670935,1947670936,1947670937,1947670938) select photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type, id from MTRPhoto.photo_sub_photos where photo_id in ( 950103132) WARNING : margin is only used for type bib ! type of cropped photo chosen : rle we resize croppped photo by 1 on x axis and by 1 on y axis we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! we have both polygon and rles Here we manage rles ! map_result returned by crop_photo_return_map_crop : length : 8 map_result after crop : {1947670931: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670931_0.jpg', 'coordonates': (183, 199, 15, 41), 'sub_photo_id': -1, 'same_chi': False}, 1947670932: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670932_0.jpg', 'coordonates': (38, 85, 113, 140), 'sub_photo_id': -1, 'same_chi': False}, 1947670933: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670933_0.jpg', 'coordonates': (168, 194, 141, 151), 'sub_photo_id': -1, 'same_chi': False}, 1947670934: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670934_0.jpg', 'coordonates': (47, 101, 16, 110), 'sub_photo_id': -1, 'same_chi': False}, 1947670935: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670935_0.jpg', 'coordonates': (175, 199, 104, 111), 'sub_photo_id': -1, 'same_chi': False}, 1947670936: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670936_0.jpg', 'coordonates': (86, 130, 184, 196), 'sub_photo_id': -1, 'same_chi': False}, 1947670937: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670937_0.jpg', 'coordonates': (79, 195, 0, 61), 'sub_photo_id': -1, 'same_chi': False}, 1947670938: {'crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg', 'photo_id': 950103132, 'bib_crop': 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_bib_crop_1947670938_0.jpg', 'coordonates': (131, 155, 181, 195), 'sub_photo_id': -1, 'same_chi': False}} Here we crop with rles About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos upload in portfolio : 27233592 in upload media Upload medias : ['temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg'] : url : https://www.fotonower.com/api/v1/secured/photo/upload?token=78d09a0790ec6ecbf119343125a81fdc&datou=0 temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg after data_to_send, before sending request after request b'{"photo_ids":["1386159259","1386159232","1386159160","1386159189","1386159174","1386159246","1386159219","1386159204"],"photo_ids_order":["1386159160","1386159174","1386159189","1386159204","1386159219","1386159232","1386159246","1386159259"],"photo_detail":[{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/62a9f4922c9daa9d64f81185f7e26e28.jpg","text":"TemporaryFile(/tmp/multipartBody1639617236574215313asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/af7a1203ba5465ad8d53abbc53632f08.jpg","text":"TemporaryFile(/tmp/multipartBody9056176453911603777asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/ce8f4a13ce85a300687fbfb65d2559e7.jpg","text":"TemporaryFile(/tmp/multipartBody7633513586188180386asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/48103fe5cf279e338084f3aac6d89f0b.jpg","text":"TemporaryFile(/tmp/multipartBody1032826506738520570asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/eb49e015a574e4c43e25d13c6b730818.jpg","text":"TemporaryFile(/tmp/multipartBody3683568161931280441asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/b9c8c6ae3bbe86c02162f76b6dc3d47b.jpg","text":"TemporaryFile(/tmp/multipartBody4216047369148453044asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/5249b7ddbb153e25712b6c5e3128103a.jpg","text":"TemporaryFile(/tmp/multipartBody4333119623743911397asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg","height":0,"width":0},{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/005291634ab3d4b032fd8286cff5e3f3.jpg","text":"TemporaryFile(/tmp/multipartBody142979575925501776asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812657142,"filename":"1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg","height":0,"width":0}],"map_files_photo_id":{"file2":"1386159189","file6":"1386159246","file1":"1386159174","file7":"1386159259","file0":"1386159160","file4":"1386159219","file5":"1386159232","file3":"1386159204"},"map_files_photo_id_array":[{"photo_id":"1386159232","filename":"file5"},{"photo_id":"1386159189","filename":"file2"},{"photo_id":"1386159219","filename":"file4"},{"photo_id":"1386159259","filename":"file7"},{"photo_id":"1386159174","filename":"file1"},{"photo_id":"1386159160","filename":"file0"},{"photo_id":"1386159204","filename":"file3"},{"photo_id":"1386159246","filename":"file6"}],"portfolio_id":27233592,"hashtag_by_photo_ids":[{"1386159259":["hashtag1","hashtag2"]},{"1386159232":["hashtag1","hashtag2"]},{"1386159160":["hashtag1","hashtag2"]},{"1386159189":["hashtag1","hashtag2"]},{"1386159174":["hashtag1","hashtag2"]},{"1386159246":["hashtag1","hashtag2"]},{"1386159219":["hashtag1","hashtag2"]},{"1386159204":["hashtag1","hashtag2"]}],"comms":"Portfolio 27233592 used, photo_id : ArrayBuffer(1386159259, 1386159232, 1386159160, 1386159189, 1386159174, 1386159246, 1386159219, 1386159204)","result":[],"list_datou_current":[]}' Result OK ! uploaded one batch 0 Elapsed time : 23.93488836288452 map_result_insert : {'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg': 1386159189, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg': 1386159246, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg': 1386159174, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg': 1386159259, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg': 1386159160, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg': 1386159219, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg': 1386159232, 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg': 1386159204} Now we prepare data that will be used for ellipse search ! chi_id found to be used 1947670931 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg sub_photo_id found to be used 1386159160 chi_id found to be used 1947670932 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg sub_photo_id found to be used 1386159174 chi_id found to be used 1947670933 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg sub_photo_id found to be used 1386159189 chi_id found to be used 1947670934 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg sub_photo_id found to be used 1386159204 chi_id found to be used 1947670935 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg sub_photo_id found to be used 1386159219 chi_id found to be used 1947670936 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg sub_photo_id found to be used 1386159232 chi_id found to be used 1947670937 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg sub_photo_id found to be used 1386159246 chi_id found to be used 1947670938 path of cropped varroa found to be used to match on an ellipse temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg sub_photo_id found to be used 1386159259 insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [(1947670931, '1386159160', 31), (1947670932, '1386159174', 31), (1947670933, '1386159189', 31), (1947670934, '1386159204', 31), (1947670935, '1386159219', 31), (1947670936, '1386159232', 31), (1947670937, '1386159246', 31), (1947670938, '1386159259', 31)] map of cropped photos with some data : {'1386159160': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', (183, 199, 15, 41)], '1386159174': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', (38, 85, 113, 140)], '1386159189': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', (168, 194, 141, 151)], '1386159204': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', (47, 101, 16, 110)], '1386159219': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', (175, 199, 104, 111)], '1386159232': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', (86, 130, 184, 196)], '1386159246': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', (79, 195, 0, 61)], '1386159259': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg', (131, 155, 181, 195)]} After datou_step_exec type output : time spend for datou_step_exec : 23.98632788658142 time spend to save output : 5.3882598876953125e-05 total time spend for step 1 : 23.986381769180298 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : crop we use saveGeneral [950103132] map_info['map_portfolio_photo'] : {} final : True mtd_id 686 list_pids : [950103132] Looping around the photos to save general results len do output : 8 /1386159160Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159174Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159189Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159204Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159219Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159232Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159246Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386159259Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('686', None, None, None, None, None, None, None, None) ('686', None, '950103132', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 25 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('686', None, '1386159160', 'None', None, None, None, None, None), ('686', None, '1386159174', 'None', None, None, None, None, None), ('686', None, '1386159189', 'None', None, None, None, None, None), ('686', None, '1386159204', 'None', None, None, None, None, None), ('686', None, '1386159219', 'None', None, None, None, None, None), ('686', None, '1386159232', 'None', None, None, None, None, None), ('686', None, '1386159246', 'None', None, None, None, None, None), ('686', None, '1386159259', 'None', None, None, None, None, None), ('686', None, '950103132', None, None, None, None, None, None)] time used for this insertion : 0.014324665069580078 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1386159160': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', (183, 199, 15, 41)], '1386159174': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', (38, 85, 113, 140)], '1386159189': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', (168, 194, 141, 151)], '1386159204': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', (47, 101, 16, 110)], '1386159219': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', (175, 199, 104, 111)], '1386159232': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', (86, 130, 184, 196)], '1386159246': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', (79, 195, 0, 61)], '1386159259': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg', (131, 155, 181, 195)]} ret_da : {'1386159160': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', (183, 199, 15, 41)], '1386159174': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', (38, 85, 113, 140)], '1386159189': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', (168, 194, 141, 151)], '1386159204': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', (47, 101, 16, 110)], '1386159219': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', (175, 199, 104, 111)], '1386159232': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', (86, 130, 184, 196)], '1386159246': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', (79, 195, 0, 61)], '1386159259': ['950103132', 'temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg', (131, 155, 181, 195)]} 8 Found filename_to_hash : temp/1758812653_3157952_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg ############################### TEST angular_coeff ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=852 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=852 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 852 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=852 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : angular_coeff list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (932296368) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 932296368 download finish for photo 932296368 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.14068865776062012 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:angular_coeff Thu Sep 25 17:04:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812677_3157952_932296368_97c5e7b0f2830e550e2d6eeb248d8006.jpg': 932296368} map_photo_id_path_extension : {932296368: {'path': 'temp/1758812677_3157952_932296368_97c5e7b0f2830e550e2d6eeb248d8006.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of step detection filter param_json : {'input_type': 846, 'output_type': -1, 'orientation_type': 872, 'ref_crop_type': 846, 'condition_crop': 'car', 'criteria_crop': 'center_rect', 'crops_coeffs': {'CAR_EXTERIEUR_angle_avant_droit.*': {'aile-avant': [[15, 0.0], [240, 0.0], [285, 1.0], [345, 1.0]], 'capot': [[45, 1.0], [60, 0.5], [270, 0.0], [315, 1.0], [360, 1.0]]}}} angular_coefficients_to_crops batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 932296368) and `type` in (846) Loaded 19 chid ids of type : 846 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (769189713,769189714,769189715,769189716,769189717,769189718,769189721,769189723,769189724,769189725,769189727,769189729,769189730,769189732,769189733,769189734,769189737,769189738,769189739) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (769189713,769189714,769189715,769189716,769189717,769189718,769189721,769189723,769189724,769189725,769189727,769189729,769189730,769189732,769189733,769189734,769189737,769189738,769189739) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (769189713,769189714,769189715,769189716,769189717,769189718,769189721,769189723,769189724,769189725,769189727,769189729,769189730,769189732,769189733,769189734,769189737,769189738,769189739) select distinct hashtag_id from MTRBack.photo_hashtag_ids where photo_id in (932296368) and type=872 treating photo 932296368 select distinct hashtag_id from MTRBack.photo_hashtag_ids where photo_id in (932296368) and type=872 After datou_step_exec type output : time spend for datou_step_exec : 0.06409502029418945 time spend to save output : 0.0012149810791015625 total time spend for step 1 : 0.06531000137329102 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {932296368: ([(932296368, 2106233860, 846, 1066, 1277, 93, 340, 0.31964028378983567, 0, []), (932296368, 2106233860, 846, 434, 690, 218, 498, 0.7170410105787726, 0, []), (932296368, 503548896, 846, 902, 1111, 466, 576, 0.31724966, 769189715, []), (932296368, 599722655, 846, 523, 1100, 152, 337, 0.98039776, 0, []), (932296368, 492601069, 846, 143, 1190, 90, 695, 0.9696157, 769189717, []), (932296368, 492601069, 846, 0, 408, 246, 719, 0.9431181, 769189718, []), (932296368, 2096875722, 846, 567, 964, 162, 215, 0.55490255, 769189721, []), (932296368, 2096875709, 846, 437, 939, 24, 198, 0.9983077, 769189723, []), (932296368, 2096875709, 846, 1004, 1263, 28, 144, 0.9485744, 769189724, []), (932296368, 624624117, 846, 595, 1122, 331, 640, 0.99100167, 769189725, []), (932296368, 492624020, 846, 585, 874, 308, 393, 0.78697366, 769189727, []), (932296368, 2096875719, 846, 943, 1100, 428, 547, 0.96733797, 769189729, []), (932296368, 492654799, 846, 253, 467, 35, 441, 0.99621326, 769189730, []), (932296368, 492689227, 846, 1118, 1264, 270, 438, 0.9901647, 769189732, []), (932296368, 492689227, 846, 486, 671, 378, 690, 0.98789483, 769189733, []), (932296368, 492689227, 846, 161, 255, 229, 409, 0.70801014, 769189734, []), (932296368, 492925064, 846, 261, 421, 27, 193, 0.92215157, 769189737, []), (932296368, 492925064, 846, 873, 1045, 46, 156, 0.7535122, 769189738, []), (932296368, 492925064, 846, 1090, 1279, 20, 107, 0.45259848, 769189739, [])],)} test angular coeff is a success ! ############################### TEST detection_filter_by_crop ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=708 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=708 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 708 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=708 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : detection_filter_by_crop list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (946711423) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 946711423 download finish for photo 946711423 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.12396740913391113 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:detection_filter_by_crop Thu Sep 25 17:04:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812678_3157952_946711423_b4bef6b5c6c4b6ffae23f8718c42183c.jpg': 946711423} map_photo_id_path_extension : {946711423: {'path': 'temp/1758812678_3157952_946711423_b4bef6b5c6c4b6ffae23f8718c42183c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of step detection filter param_json : {'input_type': 631, 'output_type': -1, 'condition_type': 445, 'condition_crop': 'car', 'criteria_crop': 'center_rect', 'min_surface_ratio': 0.7} conditional_crop_copy batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 946711423) and `type` in (445) Loaded 3 chid ids of type : 445 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1947734477,18345275,18345276) +++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947734477,18345275,18345276) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1947734477,18345275,18345276) batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 946711423) and `type` in (631) Loaded 35 chid ids of type : 631 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 946711423) and `type` in (445) Loaded 3 chid ids of type : 445 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1947734477,18345275,18345276) +++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947734477,18345275,18345276) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1947734477,18345275,18345276) treating photo 946711423 SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 624624117, 'type': 631, 'x0': 226, 'x1': 569, 'y0': 252, 'y1': 425, 'score': 0.99812776, 'id': 1947740368, 'points': ['395,419,341,419,340,418,316,418,315,417,306,417, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 162, 'x1': 245, 'y0': 233, 'y1': 396, 'score': 0.99702626, 'id': 1947740369, 'points': ['215,393,206,393,202,390,200,390,192,383,191,380, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 96, 'x1': 172, 'y0': 39, 'y1': 261, 'score': 0.9928518, 'id': 1947740370, 'points': ['143,252,143,249,141,246,140,246,138,248,138,251,137 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 545, 'x1': 612, 'y0': 186, 'y1': 276, 'score': 0.9876676, 'id': 1947740371, 'points': ['584,267,583,266,578,266,574,262,574,259,573,258,5 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875719, 'type': 631, 'x0': 468, 'x1': 555, 'y0': 292, 'y1': 365, 'score': 0.9830025, 'id': 1947740372, 'points': ['491,350,489,350,488,349,487,350,483,350,480,348, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 599722655, 'type': 631, 'x0': 176, 'x1': 535, 'y0': 138, 'y1': 264, 'score': 0.9818268, 'id': 1947740373, 'points': ['453,253,413,253,412,252,387,252,386,250,386,248,3 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 53, 'x1': 87, 'y0': 127, 'y1': 212, 'score': 0.9786105, 'id': 1947740374, 'points': ['74,201,69,201,67,199,66,199,65,198,62,192,62,190,61 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492844413, 'type': 631, 'x0': 89, 'x1': 163, 'y0': 93, 'y1': 144, 'score': 0.9772748, 'id': 1947740375, 'points': ['159,142,153,141,151,139,148,138,145,135,141,133,139 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 418, 'x1': 522, 'y0': 69, 'y1': 136, 'score': 0.97407305, 'id': 1947740376, 'points': ['510,121,507,121,505,119,501,120,500,119,500,113,4 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875709, 'type': 631, 'x0': 185, 'x1': 431, 'y0': 39, 'y1': 136, 'score': 0.97171515, 'id': 1947740377, 'points': ['331,134,287,134,286,133,284,133,283,134,272,134, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875722, 'type': 631, 'x0': 198, 'x1': 395, 'y0': 118, 'y1': 142, 'score': 0.9699756, 'id': 1947740378, 'points': ['328,137,251,137,250,136,249,137,241,137,240,136, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 499500794, 'type': 631, 'x0': 93, 'x1': 107, 'y0': 127, 'y1': 146, 'score': 0.9574813, 'id': 1947740379, 'points': ['101,143,98,143,95,139,95,131,97,129,100,129,101,13 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 71, 'x1': 125, 'y0': 36, 'y1': 95, 'score': 0.95296955, 'id': 1947740380, 'points': ['104,92,96,92,93,90,91,90,86,86,83,85,83,84,81,82,80 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 101, 'x1': 167, 'y0': 38, 'y1': 127, 'score': 0.9508439, 'id': 1947740381, 'points': ['154,117,152,115,152,112,150,110,148,106,148,104,14 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492624020, 'type': 631, 'x0': 249, 'x1': 400, 'y0': 219, 'y1': 316, 'score': 0.8792459, 'id': 1947740382, 'points': ['395,313,390,313,386,311,384,312,381,312,376,309,3 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 540, 'x1': 625, 'y0': 78, 'y1': 221, 'score': 0.87864035, 'id': 1947740383, 'points': ['567,127,566,127,565,126,564,109,562,106,560,106,5 surface aoutside conditional crop crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 547, 'x1': 640, 'y0': 79, 'y1': 129, 'score': 0.8165246, 'id': 1947740384, 'points': ['630,96,627,96,627,94,628,92,629,92,631,94,631,95', surface aoutside conditional crop crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 360, 'x1': 434, 'y0': 62, 'y1': 116, 'score': 0.74684095, 'id': 1947740385, 'points': ['415,103,413,103,411,101,408,101,405,99,403,99,401 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 503548896, 'type': 631, 'x0': 302, 'x1': 540, 'y0': 339, 'y1': 403, 'score': 0.7406652, 'id': 1947740386, 'points': ['442,401,372,401,372,397,370,395,369,392,366,390,3 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 53, 'x1': 85, 'y0': 75, 'y1': 182, 'score': 0.73015845, 'id': 1947740387, 'points': ['70,147,68,145,65,139,65,137,62,132,61,128,57,126,5 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875717, 'type': 631, 'x0': 477, 'x1': 510, 'y0': 220, 'y1': 243, 'score': 0.69028217, 'id': 1947740388, 'points': ['501,241,493,241,489,239,488,237,487,237,480,232 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 61, 'x1': 115, 'y0': 42, 'y1': 188, 'score': 0.6900027, 'id': 1947740389, 'points': ['92,47,91,45,92,44,96,45,94,45', '73,141,73,136,72,1 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875712, 'type': 631, 'x0': 309, 'x1': 326, 'y0': 382, 'y1': 404, 'score': 0.6633776, 'id': 1947740390, 'points': ['309,383,309,382,311,382', '325,385,324,383,319,3 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875719, 'type': 631, 'x0': 427, 'x1': 553, 'y0': 258, 'y1': 315, 'score': 0.6446218, 'id': 1947740391, 'points': ['531,284,526,284,525,283,525,281,523,279,522,280, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233861, 'type': 631, 'x0': 144, 'x1': 267, 'y0': 181, 'y1': 307, 'score': 0.63958377, 'id': 1947740392, 'points': ['212,251,209,251,208,250,203,251,201,250,201,249 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875712, 'type': 631, 'x0': 285, 'x1': 433, 'y0': 343, 'y1': 377, 'score': 0.61493844, 'id': 1947740393, 'points': ['431,376,286,376,285,375,285,368,286,367,286,362 crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 146, 'x1': 287, 'y0': 140, 'y1': 311, 'score': 0.54784286, 'id': 1947740394, 'points': ['234,254,227,254,221,251,219,248,215,253,212,253 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 496, 'x1': 624, 'y0': 141, 'y1': 245, 'score': 0.46262404, 'id': 1947740395, 'points': ['603,176,599,173,595,176,593,176,590,174,589,174 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 495920967, 'type': 631, 'x0': 202, 'x1': 524, 'y0': 112, 'y1': 333, 'score': 0.45109355, 'id': 1947740396, 'points': ['483,289,483,286,482,285,482,283,480,279,480,274, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 2096875722, 'type': 631, 'x0': 433, 'x1': 558, 'y0': 248, 'y1': 286, 'score': 0.44133398, 'id': 1947740397, 'points': ['492,272,474,272,473,271,468,271,465,269,460,269 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233861, 'type': 631, 'x0': 535, 'x1': 630, 'y0': 138, 'y1': 231, 'score': 0.42747068, 'id': 1947740398, 'points': ['590,171,589,170,585,170,584,171,581,169,579,169 surface aoutside conditional crop crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 399, 'x1': 569, 'y0': 68, 'y1': 251, 'score': 0.41876298, 'id': 1947740399, 'points': [], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', ' crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 492624020, 'type': 631, 'x0': 420, 'x1': 552, 'y0': 244, 'y1': 293, 'score': 0.35962066, 'id': 1947740400, 'points': ['474,289,453,289,452,288,439,288,437,286,431,286, crop duplicated : : {'photo_id': 946711423, 'hashtag_id': 503548896, 'type': 631, 'x0': 301, 'x1': 540, 'y0': 339, 'y1': 403, 'score': 0.740756, 'id': 3140491551, 'points': ['442,401,371,401,371,397,366,390,365,386,356,386,35 crop not duplicated : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 496, 'x1': 624, 'y0': 140, 'y1': 245, 'score': 0.4627206, 'id': 3140491552, 'points': ['595,176,593,176,589,173,586,176,583,176,580,174, surface aoutside conditional crop After datou_step_exec type output : time spend for datou_step_exec : 0.10864472389221191 time spend to save output : 2.7894973754882812e-05 total time spend for step 1 : 0.1086726188659668 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {946711423: ([(946711423, 624624117, 631, 226, 569, 252, 425, 0.99812776, 1947740368, 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(946711423, 492689227, 631, 162, 245, 233, 396, 0.99702626, 1947740369, ['215,393,206,393,202,390,200,390,192,383,191,380,187,375,184,369,184,367,180,360,180,358,179,357,177,349,175,347,174,339,172,336,171,330,170,329,169,324,168,323,168,313,167,312,167,304,166,303,166,298,165,297,165,288,164,287,165,286,165,272,166,271,166,268,167,267,167,263,168,262,169,254,173,249,177,247,178,247,181,251,184,251,184,252,187,255,189,255,193,259,193,261,195,263,195,264,201,270,203,278,207,282,208,289,211,293,211,296,213,299,214,304,215,305,216,312,219,316,219,319,220,320,220,325,222,329,222,335,223,336,223,338,225,342,225,349,226,350,226,359,227,360,227,366,228,367,228,371,231,375,231,382,227,385,226,388,225,389,223,388,219,392,216,392']), (946711423, 492654799, 631, 96, 172, 39, 261, 0.9928518, 1947740370, ['143,252,143,249,141,246,140,246,138,248,138,251,137,250,137,248,135,246,134,246,132,248,127,244,124,244,122,241,122,236,121,235,121,232,118,229,117,225,116,224,116,212,113,209,115,207,116,201,111,194,110,184,106,178,107,154,108,152,112,148,113,144,112,143,112,138,110,136,108,136,107,135,103,128,103,124,102,123,102,121,103,120,103,118,106,115,106,106,107,105,110,104,113,101,117,93,117,71,114,65,116,61,116,59,117,58,117,55,118,54,119,49,122,45,122,44,124,42,150,42,151,43,153,43,153,47,152,48,152,50,154,52,155,56,156,57,156,85,155,86,155,95,154,96,154,98,155,99,155,105,156,106,155,107,155,116,157,120,159,121,159,123,156,127,156,134,157,135,157,138,156,139,156,141,154,145,152,147,150,151,149,159,148,160,148,164,149,165,149,174,148,175,148,197,149,198,149,215,150,216,150,241,149,242,149,245,148,247,146,245,144,247', '122,147,121,138,120,141,119,142,119,144,118,145,121,148']), (946711423, 2096875719, 631, 468, 555, 292, 365, 0.9830025, 1947740372, 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['453,253,413,253,412,252,387,252,386,250,386,248,383,246,379,245,376,243,361,243,361,240,362,239,359,238,358,237,356,237,355,236,352,236,351,235,333,235,332,234,329,234,329,233,331,231,331,229,329,228,328,224,330,222,330,221,324,218,308,219,307,218,302,218,298,216,288,217,287,218,285,218,283,220,283,221,287,224,295,225,295,225,294,226,289,226,288,227,283,227,282,228,273,228,272,229,271,228,259,228,258,227,254,227,253,226,247,225,247,225,251,221,248,218,243,216,247,213,248,213,249,212,248,211,246,211,245,210,241,210,240,209,237,209,236,208,231,207,230,206,228,202,224,201,223,200,221,200,220,199,214,198,213,195,211,193,208,193,203,189,203,184,201,181,201,176,198,171,199,170,199,158,203,154,205,153,205,151,206,149,209,149,210,148,225,148,226,147,283,147,284,148,287,148,288,147,305,147,306,148,312,148,313,147,354,147,355,146,428,146,429,147,433,147,434,148,437,148,438,149,451,149,457,156,459,162,462,165,464,166,471,166,472,165,477,165,480,167,480,171,486,175,488,175,489,176,502,176,503,178,503,180,509,185,509,189,512,193,512,199,513,200,513,203,514,204,514,210,513,211,514,217,512,221,513,222,513,225,510,229,510,235,507,237,504,238,502,243,490,243,489,244,485,244,484,245,480,245,479,246,463,246,462,247,460,247,458,249,457,252,454,252', '528,212,528,207,526,206,524,203,526,203,527,202,528,202', '299,215,302,212,299,211,298,210,291,210,290,211,281,212,286,215,290,215,291,216', '375,242,376,240,375,238,363,239,368,242,371,242,372,243']), (946711423, 492844413, 631, 89, 163, 93, 144, 0.9772748, 1947740375, ['159,142,153,141,151,139,148,138,145,135,141,133,139,133,138,132,131,132,130,131,125,131,124,130,121,130,120,129,116,129,115,128,112,128,108,126,106,126,100,123,98,121,94,113,94,104,97,101,103,98,105,98,106,97,110,97,111,96,116,96,117,95,132,95,133,96,139,97,141,99,144,100,149,105,150,107,154,108,155,113,157,115,158,115,160,118,160,120,161,121,161,133,160,134,160,140']), (946711423, 2096875709, 631, 185, 431, 39, 136, 0.97171515, 1947740377, 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['442,401,372,401,372,397,370,395,369,392,366,390,367,389,366,386,357,386,354,384,350,384,349,383,320,383,319,382,320,378,318,376,318,374,314,370,309,370,308,369,306,369,305,363,305,357,306,356,306,353,307,353,308,354,313,354,314,355,315,354,320,354,321,353,331,353,332,354,335,354,336,355,339,355,340,356,379,356,380,357,406,357,407,356,409,356,410,357,474,357,475,356,482,356,484,357,485,356,488,356,493,353,501,354,502,353,506,353,507,352,517,352,518,351,522,351,525,347,527,346,530,347,530,349,533,351,530,355,528,355,527,356,515,356,509,359,508,361,505,362,503,365,497,368,494,372,490,373,489,374,492,376,495,376,493,377,488,378,490,380,495,380,497,381,497,381,487,382,485,385,476,387,469,392,466,392,465,393,460,393,456,396,453,397,451,399,443,400', '519,353,518,352,517,353,518,354']), (946711423, 2106233860, 631, 53, 85, 75, 182, 0.73015845, 1947740387, ['70,147,68,145,65,139,65,137,62,132,61,128,57,126,56,124,56,121,54,119,54,110,56,108,56,103,59,100,60,101,61,100,61,96,63,93,63,89,66,84,65,83,65,80,66,78,68,78,68,79,70,80,70,83,74,87,74,90,75,91,75,100,77,102,77,105,75,106,75,125,76,126,77,125,77,125,77,128,76,129,77,131,77,136,75,139,75,143,78,145,76,146,71,146', '61,107,60,106,59,107,60,108', '77,134,76,131,75,134,76,135']), (946711423, 2096875717, 631, 477, 510, 220, 243, 0.69028217, 1947740388, ['501,241,493,241,489,239,488,237,487,237,480,232,479,230,479,226,484,222,487,222,488,223,492,224,496,228,497,228,497,229,502,234,502,235,504,236,504,240,502,240']), (946711423, 2096875712, 631, 309, 326, 382, 404, 0.6633776, 1947740390, ['309,383,309,382,311,382', '325,385,324,383,319,383,318,382,325,382', '320,400,311,400,309,398,309,385,310,386,311,385,315,385,316,384,318,384,319,385,322,385,325,387,325,398,323,398']), (946711423, 2096875719, 631, 427, 553, 258, 315, 0.6446218, 1947740391, 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['431,376,286,376,285,375,285,368,286,367,286,362,287,361,287,359,291,359,297,362,306,363,307,364,312,364,313,365,322,366,323,367,331,366,332,368,334,368,335,369,338,368,337,366,336,366,337,365,336,364,327,364,325,361,319,361,317,357,317,356,318,355,325,355,326,353,331,353,333,351,332,350,330,350,328,348,326,348,325,347,319,347,315,345,306,345,305,344,297,344,299,344,300,343,431,343,432,344,432,353,431,354,431,358,430,359,430,365,427,365,425,363,424,363,422,364,421,366,418,366,413,369,404,370,409,371,409,371,399,371,398,372,395,373,419,374,420,373,426,372,428,370,428,367,429,367,430,368,429,369,430,370,430,373,431,374', '381,373,378,372,377,371,356,371,356,371,359,370,347,369,345,367,343,367,342,368,343,369,341,370,354,371,354,371,352,372,353,373,359,373,360,374']), (946711423, 2106233860, 631, 146, 287, 140, 311, 0.54784286, 1947740394, ['234,254,227,254,221,251,219,248,215,253,212,253,210,252,206,247,203,247,198,243,197,243,194,239,189,238,186,236,182,236,181,235,167,235,164,233,164,228,159,227,158,226,158,219,159,218,159,213,162,207,162,205,169,192,169,186,170,185,172,185,177,179,175,175,173,173,177,171,181,171,182,170,184,170,187,167,187,164,188,163,188,161,199,161,202,164,205,165,207,167,209,167,212,165,215,165,216,168,218,170,219,170,221,168,221,164,220,163,220,161,222,161,223,160,230,160,231,159,242,159,244,158,247,161,248,161,247,162,246,168,248,172,248,174,253,176,254,180,253,182,249,182,247,185,249,188,253,188,254,189,254,194,249,194,247,196,247,198,249,200,252,200,253,199,255,202,255,205,254,206,254,208,250,207,249,206,246,209,246,210,249,214,252,212,254,212,254,214,255,215,255,217,254,218,254,221,252,221,249,219,247,221,247,225,249,228,250,228,252,226,253,224,253,224,253,229,252,229,251,228,249,228,247,230,247,233,246,234,246,237,245,238,245,240,243,244,243,247,239,251,237,251', '230,167,229,166,227,167,228,168']), (946711423, 495920967, 631, 202, 524, 112, 333, 0.45109355, 1947740396, 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'312,179,311,178,308,179,309,180', '268,269,264,269,259,266,259,262,261,258,261,250,265,245,269,250,270,257,274,260,278,265,275,267,269,268', '414,281,401,281,414,281']), (946711423, 2096875722, 631, 433, 558, 248, 286, 0.44133398, 1947740397, ['492,272,474,272,473,271,468,271,465,269,460,269,460,268,465,266,467,266,468,265,470,265,471,264,475,264,476,263,479,263,480,262,486,262,487,261,491,261,492,260,495,260,496,259,502,259,506,257,510,257,514,255,517,255,518,254,530,253,531,252,535,252,536,251,538,251,539,252,543,252,544,253,547,253,549,251,553,251,555,253,555,267,552,270,550,270,550,269,548,267,547,267,547,267,548,266,547,265,545,266,540,266,539,264,530,264,529,263,524,263,519,266,513,266,510,268,507,268,506,269,499,270,498,271,493,271', '438,279,435,279,435,273,436,272,448,271,449,272,448,274,443,274,440,277,440,278']), (946711423, 492654799, 631, 399, 569, 68, 251, 0.41876298, 1947740399, []), (946711423, 492624020, 631, 420, 552, 244, 293, 0.35962066, 1947740400, ['474,289,453,289,452,288,439,288,437,286,431,286,427,284,423,284,422,283,422,275,427,275,428,273,430,272,435,272,436,271,438,271,442,269,447,269,450,267,454,267,460,264,464,264,467,262,483,261,484,260,488,260,489,259,494,259,495,258,502,258,503,257,505,257,509,255,512,255,516,252,520,252,521,251,526,250,530,248,534,248,535,247,546,247,547,248,549,248,549,250,550,251,550,266,551,267,551,275,550,276,550,278,549,279,549,281,537,282,535,284,528,284,527,285,504,285,503,286,495,286,492,288,488,287,487,288,475,288']), (946711423, 503548896, 631, 301, 540, 339, 403, 0.740756, 3140491551, ['442,401,371,401,371,397,366,390,365,386,356,386,353,384,348,383,319,383,319,378,314,370,310,370,305,368,304,357,305,353,330,353,339,356,378,356,379,357,474,357,475,356,488,356,493,353,501,354,507,352,517,352,522,351,527,346,530,347,533,351,530,355,527,356,515,356,505,362,503,365,497,368,494,372,489,374,492,376,488,378,490,380,495,380,487,382,485,385,476,387,469,392,461,393,456,395,451,399,447,399', '519,353,518,352,517,353,518,354'])],)} test detection filter by crop is a success ! ############################### TEST detection_filter_by_classif ################################ t SELECT id FROM MTRPhoto.crop_hashtag_ids WHERE photo_id=946711423 AND `type`=816 DELETE FROM MTRPhoto.crop_hashtag_ids WHERE id IN (3975187147,3975187146,3975187145,3975187154,3975187153,3975187152,3975187151,3975187150,3975187159,3975187162,3975187148,3975187149,3975187158,3975187157,3975187163,3975187164,3975187165,3975187167,3975187155,3975187161,3975187160,3975187166,3975187156) Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=672 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=672 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 672 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=672 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : detection_filter_by_classif list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (946711423) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.004750728607177734 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:detection_filter_by_classif Thu Sep 25 17:04:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} beginning of step detection filter with classification results param_json : {'input_type': 631, 'output_type': 816, 'condition_type': 872, 'crops_ok': {'CAR_DOCUMENT.*': {}, 'CAR_INTERIEUR.*': {}, 'CAR_EXTERIEUR_angle_avant_droit.*': {'Retroviseur': 2, 'Roue': 2, 'Capot': 1, 'Pare-brise': 1, 'vitre': 10, 'phare': 2, 'Feu-antibrouillard': 2, 'poignee': 2, 'porte': 2, 'calandre': 1, 'logo-marque': 1, 'Plaque-immatriculation': 1, 'Essuie-glace': 1, 'pare-choc': 1, 'toit': 1, 'logo-roue': 1, 'aile-avant': 1}}, 'separation': {'CAR_EXTERIEUR_avant.*': {'pare-choc': ['pare-chocs-avant'], 'phare': ['phare-gauche', 'a-droite-de', 'phare-droit']}, 'CAR_EXTERIEUR_angle_avant_droit.*': {'pare-choc': ['pare-chocs-avant'], 'phare': ['phare-droite', 'a-gauche-de', 'phare-gauche'], 'porte': ['porte-avant', 'a-droite-de', 'porte-arriere']}}} conditional_crop_by_classif_copy select distinct hashtag_id from MTRBack.photo_hashtag_ids where photo_id in (946711423) and type=872 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 946711423) and `type` in (631) Loaded 35 chid ids of type : 631 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1947740368,1947740369,1947740370,1947740371,1947740372,1947740373,1947740374,1947740375,1947740376,1947740377,1947740378,1947740379,1947740380,1947740381,1947740382,1947740383,1947740384,1947740385,1947740386,1947740387,1947740388,1947740389,1947740390,1947740391,1947740392,1947740393,1947740394,1947740395,1947740396,1947740397,1947740398,1947740399,1947740400,3140491551,3140491552) treating photo 946711423 select distinct hashtag_id from MTRBack.photo_hashtag_ids where photo_id in (946711423) and type=872 list of crops kept {'retroviseur': 2, 'roue': 2, 'capot': 1, 'pare-brise': 1, 'vitre': 10, 'phare': 2, 'feu-antibrouillard': 2, 'poignee': 2, 'porte': 2, 'calandre': 1, 'logo-marque': 1, 'plaque-immatriculation': 1, 'essuie-glace': 1, 'pare-choc': 1, 'toit': 1, 'logo-roue': 1, 'aile-avant': 1} for hahstag car_exterieur_angle_avant_droit_merge__port_551052 crop not duplicated for hashtag aile-arriere : : {'photo_id': 946711423, 'hashtag_id': 2106233861, 'type': 631, 'x0': 144, 'x1': 267, 'y0': 181, 'y1': 307, 'score': 0.63958377, 'id': 1947740392, 'points': ['212,251,209,251,208,250,203,251,201,250,201,249 crop not duplicated for hashtag coffre : : {'photo_id': 946711423, 'hashtag_id': 495920967, 'type': 631, 'x0': 202, 'x1': 524, 'y0': 112, 'y1': 333, 'score': 0.45109355, 'id': 1947740396, 'points': ['483,289,483,286,482,285,482,283,480,279,480,274, crop not duplicated for hashtag aile-arriere : : {'photo_id': 946711423, 'hashtag_id': 2106233861, 'type': 631, 'x0': 535, 'x1': 630, 'y0': 138, 'y1': 231, 'score': 0.42747068, 'id': 1947740398, 'points': ['590,171,589,170,585,170,584,171,581,169,579,169 crop duplicated for hashtag retroviseur : : {'photo_id': 946711423, 'hashtag_id': 492844413, 'type': 631, 'x0': 89, 'x1': 163, 'y0': 93, 'y1': 144, 'score': 0.9772748, 'id': 1947740375, 'points': ['159,142,153,141,151,139,148,138,145,135,141,133,139 crop duplicated for hashtag roue : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 162, 'x1': 245, 'y0': 233, 'y1': 396, 'score': 0.99702626, 'id': 1947740369, 'points': ['215,393,206,393,202,390,200,390,192,383,191,380, crop duplicated for hashtag roue : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 545, 'x1': 612, 'y0': 186, 'y1': 276, 'score': 0.9876676, 'id': 1947740371, 'points': ['584,267,583,266,578,266,574,262,574,259,573,258,5 crop not duplicated for hashtag roue : : {'photo_id': 946711423, 'hashtag_id': 492689227, 'type': 631, 'x0': 53, 'x1': 87, 'y0': 127, 'y1': 212, 'score': 0.9786105, 'id': 1947740374, 'points': ['74,201,69,201,67,199,66,199,65,198,62,192,62,190,61 crop duplicated for hashtag capot : : {'photo_id': 946711423, 'hashtag_id': 599722655, 'type': 631, 'x0': 176, 'x1': 535, 'y0': 138, 'y1': 264, 'score': 0.9818268, 'id': 1947740373, 'points': ['453,253,413,253,412,252,387,252,386,250,386,248,3 crop duplicated for hashtag pare-brise : : {'photo_id': 946711423, 'hashtag_id': 2096875709, 'type': 631, 'x0': 185, 'x1': 431, 'y0': 39, 'y1': 136, 'score': 0.97171515, 'id': 1947740377, 'points': ['331,134,287,134,286,133,284,133,283,134,272,134, crop duplicated for hashtag vitre : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 418, 'x1': 522, 'y0': 69, 'y1': 136, 'score': 0.97407305, 'id': 1947740376, 'points': ['510,121,507,121,505,119,501,120,500,119,500,113,4 crop duplicated for hashtag vitre : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 71, 'x1': 125, 'y0': 36, 'y1': 95, 'score': 0.95296955, 'id': 1947740380, 'points': ['104,92,96,92,93,90,91,90,86,86,83,85,83,84,81,82,80 crop duplicated for hashtag vitre : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 101, 'x1': 167, 'y0': 38, 'y1': 127, 'score': 0.9508439, 'id': 1947740381, 'points': ['154,117,152,115,152,112,150,110,148,106,148,104,14 crop duplicated for hashtag vitre : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 547, 'x1': 640, 'y0': 79, 'y1': 129, 'score': 0.8165246, 'id': 1947740384, 'points': ['630,96,627,96,627,94,628,92,629,92,631,94,631,95', crop duplicated for hashtag vitre : : {'photo_id': 946711423, 'hashtag_id': 492925064, 'type': 631, 'x0': 360, 'x1': 434, 'y0': 62, 'y1': 116, 'score': 0.74684095, 'id': 1947740385, 'points': ['415,103,413,103,411,101,408,101,405,99,403,99,401 crop duplicated for hashtag phare : : {'photo_id': 946711423, 'hashtag_id': 492624020, 'type': 631, 'x0': 249, 'x1': 400, 'y0': 219, 'y1': 316, 'score': 0.8792459, 'id': 1947740382, 'points': ['395,313,390,313,386,311,384,312,381,312,376,309,3 crop duplicated for hashtag phare : : {'photo_id': 946711423, 'hashtag_id': 492624020, 'type': 631, 'x0': 420, 'x1': 552, 'y0': 244, 'y1': 293, 'score': 0.35962066, 'id': 1947740400, 'points': ['474,289,453,289,452,288,439,288,437,286,431,286, crop duplicated for hashtag feu-antibrouillard : : {'photo_id': 946711423, 'hashtag_id': 2096875712, 'type': 631, 'x0': 309, 'x1': 326, 'y0': 382, 'y1': 404, 'score': 0.6633776, 'id': 1947740390, 'points': ['309,383,309,382,311,382', '325,385,324,383,319,3 crop duplicated for hashtag feu-antibrouillard : : {'photo_id': 946711423, 'hashtag_id': 2096875712, 'type': 631, 'x0': 285, 'x1': 433, 'y0': 343, 'y1': 377, 'score': 0.61493844, 'id': 1947740393, 'points': ['431,376,286,376,285,375,285,368,286,367,286,362 crop duplicated for hashtag poignee : : {'photo_id': 946711423, 'hashtag_id': 499500794, 'type': 631, 'x0': 93, 'x1': 107, 'y0': 127, 'y1': 146, 'score': 0.9574813, 'id': 1947740379, 'points': ['101,143,98,143,95,139,95,131,97,129,100,129,101,13 crop duplicated for hashtag porte : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 96, 'x1': 172, 'y0': 39, 'y1': 261, 'score': 0.9928518, 'id': 1947740370, 'points': ['143,252,143,249,141,246,140,246,138,248,138,251,137 crop duplicated for hashtag porte : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 540, 'x1': 625, 'y0': 78, 'y1': 221, 'score': 0.87864035, 'id': 1947740383, 'points': ['567,127,566,127,565,126,564,109,562,106,560,106,5 crop not duplicated for hashtag porte : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 61, 'x1': 115, 'y0': 42, 'y1': 188, 'score': 0.6900027, 'id': 1947740389, 'points': ['92,47,91,45,92,44,96,45,94,45', '73,141,73,136,72,1 crop not duplicated for hashtag porte : : {'photo_id': 946711423, 'hashtag_id': 492654799, 'type': 631, 'x0': 399, 'x1': 569, 'y0': 68, 'y1': 251, 'score': 0.41876298, 'id': 1947740399, 'points': [], 'sub_photo_id': 0, 'rles': [], 'hashtag': '', ' crop duplicated for hashtag calandre : : {'photo_id': 946711423, 'hashtag_id': 503548896, 'type': 631, 'x0': 301, 'x1': 540, 'y0': 339, 'y1': 403, 'score': 0.740756, 'id': 3140491551, 'points': ['442,401,371,401,371,397,366,390,365,386,356,386,35 crop not duplicated for hashtag calandre : : {'photo_id': 946711423, 'hashtag_id': 503548896, 'type': 631, 'x0': 302, 'x1': 540, 'y0': 339, 'y1': 403, 'score': 0.7406652, 'id': 1947740386, 'points': ['442,401,372,401,372,397,370,395,369,392,366,390,3 crop duplicated for hashtag logo-marque : : {'photo_id': 946711423, 'hashtag_id': 2096875717, 'type': 631, 'x0': 477, 'x1': 510, 'y0': 220, 'y1': 243, 'score': 0.69028217, 'id': 1947740388, 'points': ['501,241,493,241,489,239,488,237,487,237,480,232 crop duplicated for hashtag plaque-immatriculation : : {'photo_id': 946711423, 'hashtag_id': 2096875719, 'type': 631, 'x0': 468, 'x1': 555, 'y0': 292, 'y1': 365, 'score': 0.9830025, 'id': 1947740372, 'points': ['491,350,489,350,488,349,487,350,483,350,480,348, crop not duplicated for hashtag plaque-immatriculation : : {'photo_id': 946711423, 'hashtag_id': 2096875719, 'type': 631, 'x0': 427, 'x1': 553, 'y0': 258, 'y1': 315, 'score': 0.6446218, 'id': 1947740391, 'points': ['531,284,526,284,525,283,525,281,523,279,522,280, crop duplicated for hashtag essuie-glace : : {'photo_id': 946711423, 'hashtag_id': 2096875722, 'type': 631, 'x0': 198, 'x1': 395, 'y0': 118, 'y1': 142, 'score': 0.9699756, 'id': 1947740378, 'points': ['328,137,251,137,250,136,249,137,241,137,240,136, crop not duplicated for hashtag essuie-glace : : {'photo_id': 946711423, 'hashtag_id': 2096875722, 'type': 631, 'x0': 433, 'x1': 558, 'y0': 248, 'y1': 286, 'score': 0.44133398, 'id': 1947740397, 'points': ['492,272,474,272,473,271,468,271,465,269,460,269 crop duplicated for hashtag pare-choc : : {'photo_id': 946711423, 'hashtag_id': 624624117, 'type': 631, 'x0': 226, 'x1': 569, 'y0': 252, 'y1': 425, 'score': 0.99812776, 'id': 1947740368, 'points': ['395,419,341,419,340,418,316,418,315,417,306,417, crop duplicated for hashtag aile-avant : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 53, 'x1': 85, 'y0': 75, 'y1': 182, 'score': 0.73015845, 'id': 1947740387, 'points': ['70,147,68,145,65,139,65,137,62,132,61,128,57,126,5 crop not duplicated for hashtag aile-avant : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 146, 'x1': 287, 'y0': 140, 'y1': 311, 'score': 0.54784286, 'id': 1947740394, 'points': ['234,254,227,254,221,251,219,248,215,253,212,253 crop not duplicated for hashtag aile-avant : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 496, 'x1': 624, 'y0': 140, 'y1': 245, 'score': 0.4627206, 'id': 3140491552, 'points': ['595,176,593,176,589,173,586,176,583,176,580,174, crop not duplicated for hashtag aile-avant : : {'photo_id': 946711423, 'hashtag_id': 2106233860, 'type': 631, 'x0': 496, 'x1': 624, 'y0': 141, 'y1': 245, 'score': 0.46262404, 'id': 1947740395, 'points': ['603,176,599,173,595,176,593,176,590,174,589,174 list of crops kept {'pare-choc': ('pare-chocs-avant',), 'phare': ('phare-droite', 'a-gauche-de', 'phare-gauche'), 'porte': ('porte-avant', 'a-droite-de', 'porte-arriere')} for hahstag car_exterieur_angle_avant_droit_merge__port_551052 batch 1 Loaded 0 chid ids of type : 0 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 23 chid ids of type : 816 INSERT IGNORE INTO MTRPhoto.crop_polygon_points (`crop_hashtag_id`, `points`) VALUES (%s, %s) Number RLEs to save : 1600 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975218855', '117', '95', '16') ... last line : ('3975218877', '70', '147', '1') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 0.29154300689697266 time spend to save output : 8.416175842285156e-05 total time spend for step 1 : 0.2916271686553955 caffe_path_current : About to save ! 0 After save, about to update current ! test detection filter by classif is a success ! ############################### TEST blur_detection ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1243 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1243 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1243 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1243 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : blur_detection list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (930729675) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 930729675 download finish for photo 930729675 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.12365174293518066 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:blur_detection Thu Sep 25 17:04:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812678_3157952_930729675_b2d2beaaee733d521cbb0c9800a29073.jpg': 930729675} map_photo_id_path_extension : {930729675: {'path': 'temp/1758812678_3157952_930729675_b2d2beaaee733d521cbb0c9800a29073.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} inside step blur_detection methode: ratio et variance treat image : temp/1758812678_3157952_930729675_b2d2beaaee733d521cbb0c9800a29073.jpg resize: (600, 800) 930729675 12.961859636534896 score_blur_detection : {930729675: [(930729675, 12.961859636534896, 492688767)]} After datou_step_exec type output : time spend for datou_step_exec : 0.2018754482269287 time spend to save output : 3.814697265625e-05 total time spend for step 1 : 0.20191359519958496 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {930729675: [(930729675, 12.961859636534896, 492688767)]} {930729675: [(930729675, 12.961859636534896, 492688767)]} ############################### TEST detect_point_224x224 ################################ test_detect_point_224x224 Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1908 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1908 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1908 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1908 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 4589 thcl is not linked in the step_by_step architecture ! WARNING : step 4590 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : thcl, argmax list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (987515175,987515176,987515177,987515178,987515179,987515180,987515181,987515182,987515183,987515184,987515185,987515186,987515187,987515188,987515189,987515190,987515192,987515193,987515195,987515196,987515198,987515200,987515201,987515202,987515204,987515205,987515207,987515208,987515209,987515211,987515212,987515213,987515215,987515216,987515217,987515219,987515220,987515222,987515223,987515224,987515226,987515227,987515228,987515230,987515231,987515232,987515233,987515234,987515235,987515236,987515237,987515238,987515239,987515240,987515241,987515242,987515243,987515244,987515245,987515246,987515247,987515248,987515249,987515250) Found this number of photos: 64 ##### Call download_photos : nb_thread : 5 maybe url didn't existe for photo_id 987515175 , please check it begin to download photo : 987515176 begin to download photo : 987515188 begin to download photo : 987515207 begin to download photo : 987515224 begin to download photo : 987515239 download finish for photo 987515224 begin to download photo : 987515226 download finish for photo 987515207 begin to download photo : 987515208 download finish for photo 987515176 begin to download photo : 987515177 download finish for photo 987515188 begin to download photo : 987515189 download finish for photo 987515239 begin to download photo : 987515240 download finish for photo 987515226 begin to download photo : 987515227 download finish for photo 987515189 begin to download photo : 987515190 download finish for photo 987515177 begin to download photo : 987515178 download finish for photo 987515208 begin to download photo : 987515209 download finish for photo 987515240 begin to download photo : 987515241 download finish for photo 987515178 begin to download photo : 987515179 download finish for photo 987515209 begin to download photo : 987515211 download finish for photo 987515227 begin to download photo : 987515228 download finish for photo 987515190 begin to download photo : 987515192 download finish for photo 987515241 begin to download photo : 987515242 download finish for photo 987515228 begin to download photo : 987515230 download finish for photo 987515179 begin to download photo : 987515180 download finish for photo 987515211 maybe url didn't existe for photo_id 987515212 , please check it begin to download photo : 987515213 download finish for photo 987515180 begin to download photo : 987515181 download finish for photo 987515230 begin to download photo : 987515231 download finish for photo 987515242 begin to download photo : 987515243 download finish for photo 987515192 begin to download photo : 987515193 download finish for photo 987515181 begin to download photo : 987515182 download finish for photo 987515213 begin to download photo : 987515215 download finish for photo 987515243 begin to download photo : 987515244 download finish for photo 987515231 begin to download photo : 987515232 download finish for photo 987515193 maybe url didn't existe for photo_id 987515195 , please check it begin to download photo : 987515196 download finish for photo 987515182 begin to download photo : 987515183 download finish for photo 987515215 begin to download photo : 987515216 download finish for photo 987515232 begin to download photo : 987515233 download finish for photo 987515244 begin to download photo : 987515245 download finish for photo 987515183 begin to download photo : 987515184 download finish for photo 987515216 begin to download photo : 987515217 download finish for photo 987515196 begin to download photo : 987515198 download finish for photo 987515233 begin to download photo : 987515234 download finish for photo 987515245 begin to download photo : 987515246 download finish for photo 987515184 begin to download photo : 987515185 download finish for photo 987515217 begin to download photo : 987515219 download finish for photo 987515246 begin to download photo : 987515247 download finish for photo 987515198 begin to download photo : 987515200 download finish for photo 987515185 begin to download photo : 987515186 download finish for photo 987515247 maybe url didn't existe for photo_id 987515248 , please check it begin to download photo : 987515249 download finish for photo 987515234 begin to download photo : 987515235 download finish for photo 987515200 begin to download photo : 987515201 download finish for photo 987515219 begin to download photo : 987515220 download finish for photo 987515249 begin to download photo : 987515250 download finish for photo 987515186 begin to download photo : 987515187 download finish for photo 987515235 begin to download photo : 987515236 download finish for photo 987515201 begin to download photo : 987515202 download finish for photo 987515220 begin to download photo : 987515222 download finish for photo 987515187 download finish for photo 987515250 download finish for photo 987515236 begin to download photo : 987515237 download finish for photo 987515202 begin to download photo : 987515204 download finish for photo 987515222 begin to download photo : 987515223 download finish for photo 987515204 begin to download photo : 987515205 download finish for photo 987515237 begin to download photo : 987515238 download finish for photo 987515223 download finish for photo 987515205 download finish for photo 987515238 we have missing 4 photos in the step downloads : photo missing : [987515175, 987515248, 987515212, 987515195] try to delete the photos missing in DB Url missing : :https://www.fotonower.com/api/v1/photo/onerrorloadautomation/987515175 Url missing : :https://www.fotonower.com/api/v1/photo/onerrorloadautomation/987515248 Url missing : :https://www.fotonower.com/api/v1/photo/onerrorloadautomation/987515212 Url missing : :https://www.fotonower.com/api/v1/photo/onerrorloadautomation/987515195 ##### After download_photos length of list_filenames : 60 ; length of list_pids : 60 ; length of list_args : 60 ##### After load_data_input time to download the photos : 2.878007650375366 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 2 step1:thcl Thu Sep 25 17:04:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812679_3157952_987515176_8b398cba2f448622cd9657f5eb3f9796.jpg': 987515176, 'temp/1758812679_3157952_987515177_4a54e9967227806219ddf45d256539d8.jpg': 987515177, 'temp/1758812679_3157952_987515178_298b3d2bfe0fda6787b59a78e2e68867.jpg': 987515178, 'temp/1758812679_3157952_987515179_f7d4d1757a470f4c96dc3541eac88b9e.jpg': 987515179, 'temp/1758812679_3157952_987515180_776a5d7d8486ee2961bbe3a0d90f95b5.jpg': 987515180, 'temp/1758812679_3157952_987515181_1738c2798fb31152809ecb443ac286d6.jpg': 987515181, 'temp/1758812679_3157952_987515182_fe7f29bf6d13e08c3e985f91b5232178.jpg': 987515182, 'temp/1758812679_3157952_987515183_6aab9ca0421398b4899892c10c2594c6.jpg': 987515183, 'temp/1758812679_3157952_987515184_19c8c2177209a285df6014d95fe53f2c.jpg': 987515184, 'temp/1758812679_3157952_987515185_e172d54457cabee9d7f02ee1300f3ae9.jpg': 987515185, 'temp/1758812679_3157952_987515186_797def426440b544aa80dbd63a19234a.jpg': 987515186, 'temp/1758812679_3157952_987515187_9f62f98efd3caca0b9c17d27f5c70440.jpg': 987515187, 'temp/1758812679_3157952_987515239_b3fa6f29636080b5138c8d8c33fea309.jpg': 987515239, 'temp/1758812679_3157952_987515240_7829b9b15f1bf128ea4e2c1a39b9f0dd.jpg': 987515240, 'temp/1758812679_3157952_987515241_073420d938f5f010ffd5b4353c064e09.jpg': 987515241, 'temp/1758812679_3157952_987515242_327abb5215d6fd1f0aad51f53ed8c324.jpg': 987515242, 'temp/1758812679_3157952_987515243_4375283f3bc5cdaa431c2fc6f17f53a4.jpg': 987515243, 'temp/1758812679_3157952_987515244_419530eaef5ef868f75c758b94eea4b4.jpg': 987515244, 'temp/1758812679_3157952_987515245_757d9d208d5bd4375c5f21f68b699148.jpg': 987515245, 'temp/1758812679_3157952_987515246_671a708f67f2efa19004b8257fc7b9c8.jpg': 987515246, 'temp/1758812679_3157952_987515247_e47b65403df916ba909bc9c439b0af73.jpg': 987515247, 'temp/1758812679_3157952_987515249_a70ad88462a22fb62a120721a42b2d42.jpg': 987515249, 'temp/1758812679_3157952_987515250_b2827c9639df69656f23abcc7f2f82d9.jpg': 987515250, 'temp/1758812679_3157952_987515207_de216ddb041e249524b0fb2b949064a5.jpg': 987515207, 'temp/1758812679_3157952_987515208_a2b90cb74908aa64bbc4aae58f0c5ae8.jpg': 987515208, 'temp/1758812679_3157952_987515209_02dfe1ae39f51994652f4a8538844aea.jpg': 987515209, 'temp/1758812679_3157952_987515211_72cc7664d45bd40477351b9b764f1500.jpg': 987515211, 'temp/1758812679_3157952_987515213_b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg': 987515213, 'temp/1758812679_3157952_987515215_902ef348a7eebb9a8b87f42927347936.jpg': 987515215, 'temp/1758812679_3157952_987515216_4f7dc21f1d2cd3fcabadc4a6755921e1.jpg': 987515216, 'temp/1758812679_3157952_987515217_78877bb2c5760be28518d17f77d1c609.jpg': 987515217, 'temp/1758812679_3157952_987515219_c2d417a5ba6ccf7c84527636f8d5eef9.jpg': 987515219, 'temp/1758812679_3157952_987515220_e729f316c4c3b32049adfbaaa336d95c.jpg': 987515220, 'temp/1758812679_3157952_987515222_067a027bc7402f969b6277d0dcb47eaa.jpg': 987515222, 'temp/1758812679_3157952_987515223_ebb57f09941cd11d7ee45a9368a883c1.jpg': 987515223, 'temp/1758812679_3157952_987515188_4116f9906657a69bb76c2fda982037b9.jpg': 987515188, 'temp/1758812679_3157952_987515189_8e8590a26f72249d4c2116dffd0cf668.jpg': 987515189, 'temp/1758812679_3157952_987515190_d56932bfc6ba2a8c974c691108755017.jpg': 987515190, 'temp/1758812679_3157952_987515192_b661073b218f5f056833d6af1c617153.jpg': 987515192, 'temp/1758812679_3157952_987515193_1a97fceb4dcbf5821d783b2e00b52fe6.jpg': 987515193, 'temp/1758812679_3157952_987515196_30ccb89dfe410c445878a7f2819ddc36.jpg': 987515196, 'temp/1758812679_3157952_987515198_599e80f444c876f407e94b533c89360b.jpg': 987515198, 'temp/1758812679_3157952_987515200_978964436b5d5fb0eeda17e3bfafe889.jpg': 987515200, 'temp/1758812679_3157952_987515201_b224d2acdc7fa2bbb134c09db6bca7ce.jpg': 987515201, 'temp/1758812679_3157952_987515202_3314bd90d1404f31b827d8925abf2d62.jpg': 987515202, 'temp/1758812679_3157952_987515204_9779c4f9d44360a9c80499e3b01e8a09.jpg': 987515204, 'temp/1758812679_3157952_987515205_fd4b136d0b3a9a1a347942d7191f6fea.jpg': 987515205, 'temp/1758812679_3157952_987515224_e8747b400e713ecbd08d5b75db4d7568.jpg': 987515224, 'temp/1758812679_3157952_987515226_a18048dca1a77ae086b62cf07759f704.jpg': 987515226, 'temp/1758812679_3157952_987515227_e9c45a0e576ec9e44c1379c3fc5fec7c.jpg': 987515227, 'temp/1758812679_3157952_987515228_9f1759f20c9e603bccb9f9879d2f0d54.jpg': 987515228, 'temp/1758812679_3157952_987515230_846ad925884264181565c81d152a2e94.jpg': 987515230, 'temp/1758812679_3157952_987515231_dbf4cafa71b6db4771c5c8f0c25e9cda.jpg': 987515231, 'temp/1758812679_3157952_987515232_38db7950cdb3c674ee0ad65915b021f3.jpg': 987515232, 'temp/1758812679_3157952_987515233_a92514bed0e8c5724f2d032d3ab1e2ad.jpg': 987515233, 'temp/1758812679_3157952_987515234_2eca3480aed0f8b876242675ad99b666.jpg': 987515234, 'temp/1758812679_3157952_987515235_87075955a2f76b3948b47ffe1825ecd9.jpg': 987515235, 'temp/1758812679_3157952_987515236_8b44a98b1aceadad73ed000d65836a9a.jpg': 987515236, 'temp/1758812679_3157952_987515237_1183dfa371a457f11ce2b622c7cf9467.jpg': 987515237, 'temp/1758812679_3157952_987515238_e6292cb81e05894cfeb4b99f21a1d3f8.jpg': 987515238} map_photo_id_path_extension : {987515176: {'path': 'temp/1758812679_3157952_987515176_8b398cba2f448622cd9657f5eb3f9796.jpg', 'extension': 'jpg'}, 987515177: {'path': 'temp/1758812679_3157952_987515177_4a54e9967227806219ddf45d256539d8.jpg', 'extension': 'jpg'}, 987515178: {'path': 'temp/1758812679_3157952_987515178_298b3d2bfe0fda6787b59a78e2e68867.jpg', 'extension': 'jpg'}, 987515179: {'path': 'temp/1758812679_3157952_987515179_f7d4d1757a470f4c96dc3541eac88b9e.jpg', 'extension': 'jpg'}, 987515180: {'path': 'temp/1758812679_3157952_987515180_776a5d7d8486ee2961bbe3a0d90f95b5.jpg', 'extension': 'jpg'}, 987515181: {'path': 'temp/1758812679_3157952_987515181_1738c2798fb31152809ecb443ac286d6.jpg', 'extension': 'jpg'}, 987515182: {'path': 'temp/1758812679_3157952_987515182_fe7f29bf6d13e08c3e985f91b5232178.jpg', 'extension': 'jpg'}, 987515183: {'path': 'temp/1758812679_3157952_987515183_6aab9ca0421398b4899892c10c2594c6.jpg', 'extension': 'jpg'}, 987515184: {'path': 'temp/1758812679_3157952_987515184_19c8c2177209a285df6014d95fe53f2c.jpg', 'extension': 'jpg'}, 987515185: {'path': 'temp/1758812679_3157952_987515185_e172d54457cabee9d7f02ee1300f3ae9.jpg', 'extension': 'jpg'}, 987515186: {'path': 'temp/1758812679_3157952_987515186_797def426440b544aa80dbd63a19234a.jpg', 'extension': 'jpg'}, 987515187: {'path': 'temp/1758812679_3157952_987515187_9f62f98efd3caca0b9c17d27f5c70440.jpg', 'extension': 'jpg'}, 987515239: {'path': 'temp/1758812679_3157952_987515239_b3fa6f29636080b5138c8d8c33fea309.jpg', 'extension': 'jpg'}, 987515240: {'path': 'temp/1758812679_3157952_987515240_7829b9b15f1bf128ea4e2c1a39b9f0dd.jpg', 'extension': 'jpg'}, 987515241: {'path': 'temp/1758812679_3157952_987515241_073420d938f5f010ffd5b4353c064e09.jpg', 'extension': 'jpg'}, 987515242: {'path': 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'extension': 'jpg'}, 987515208: {'path': 'temp/1758812679_3157952_987515208_a2b90cb74908aa64bbc4aae58f0c5ae8.jpg', 'extension': 'jpg'}, 987515209: {'path': 'temp/1758812679_3157952_987515209_02dfe1ae39f51994652f4a8538844aea.jpg', 'extension': 'jpg'}, 987515211: {'path': 'temp/1758812679_3157952_987515211_72cc7664d45bd40477351b9b764f1500.jpg', 'extension': 'jpg'}, 987515213: {'path': 'temp/1758812679_3157952_987515213_b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg', 'extension': 'jpg'}, 987515215: {'path': 'temp/1758812679_3157952_987515215_902ef348a7eebb9a8b87f42927347936.jpg', 'extension': 'jpg'}, 987515216: {'path': 'temp/1758812679_3157952_987515216_4f7dc21f1d2cd3fcabadc4a6755921e1.jpg', 'extension': 'jpg'}, 987515217: {'path': 'temp/1758812679_3157952_987515217_78877bb2c5760be28518d17f77d1c609.jpg', 'extension': 'jpg'}, 987515219: {'path': 'temp/1758812679_3157952_987515219_c2d417a5ba6ccf7c84527636f8d5eef9.jpg', 'extension': 'jpg'}, 987515220: {'path': 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'extension': 'jpg'}, 987515198: {'path': 'temp/1758812679_3157952_987515198_599e80f444c876f407e94b533c89360b.jpg', 'extension': 'jpg'}, 987515200: {'path': 'temp/1758812679_3157952_987515200_978964436b5d5fb0eeda17e3bfafe889.jpg', 'extension': 'jpg'}, 987515201: {'path': 'temp/1758812679_3157952_987515201_b224d2acdc7fa2bbb134c09db6bca7ce.jpg', 'extension': 'jpg'}, 987515202: {'path': 'temp/1758812679_3157952_987515202_3314bd90d1404f31b827d8925abf2d62.jpg', 'extension': 'jpg'}, 987515204: {'path': 'temp/1758812679_3157952_987515204_9779c4f9d44360a9c80499e3b01e8a09.jpg', 'extension': 'jpg'}, 987515205: {'path': 'temp/1758812679_3157952_987515205_fd4b136d0b3a9a1a347942d7191f6fea.jpg', 'extension': 'jpg'}, 987515224: {'path': 'temp/1758812679_3157952_987515224_e8747b400e713ecbd08d5b75db4d7568.jpg', 'extension': 'jpg'}, 987515226: {'path': 'temp/1758812679_3157952_987515226_a18048dca1a77ae086b62cf07759f704.jpg', 'extension': 'jpg'}, 987515227: {'path': 'temp/1758812679_3157952_987515227_e9c45a0e576ec9e44c1379c3fc5fec7c.jpg', 'extension': 'jpg'}, 987515228: {'path': 'temp/1758812679_3157952_987515228_9f1759f20c9e603bccb9f9879d2f0d54.jpg', 'extension': 'jpg'}, 987515230: {'path': 'temp/1758812679_3157952_987515230_846ad925884264181565c81d152a2e94.jpg', 'extension': 'jpg'}, 987515231: {'path': 'temp/1758812679_3157952_987515231_dbf4cafa71b6db4771c5c8f0c25e9cda.jpg', 'extension': 'jpg'}, 987515232: {'path': 'temp/1758812679_3157952_987515232_38db7950cdb3c674ee0ad65915b021f3.jpg', 'extension': 'jpg'}, 987515233: {'path': 'temp/1758812679_3157952_987515233_a92514bed0e8c5724f2d032d3ab1e2ad.jpg', 'extension': 'jpg'}, 987515234: {'path': 'temp/1758812679_3157952_987515234_2eca3480aed0f8b876242675ad99b666.jpg', 'extension': 'jpg'}, 987515235: {'path': 'temp/1758812679_3157952_987515235_87075955a2f76b3948b47ffe1825ecd9.jpg', 'extension': 'jpg'}, 987515236: {'path': 'temp/1758812679_3157952_987515236_8b44a98b1aceadad73ed000d65836a9a.jpg', 'extension': 'jpg'}, 987515237: {'path': 'temp/1758812679_3157952_987515237_1183dfa371a457f11ce2b622c7cf9467.jpg', 'extension': 'jpg'}, 987515238: {'path': 'temp/1758812679_3157952_987515238_e6292cb81e05894cfeb4b99f21a1d3f8.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Thcl ! multi_thcl or not :False multi_thcl_cond or not :False dic_thcl : {'1528': 1} we are using the classfication for only one thcl 1528 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 In convert_file_to_np l 337 : 6 l343 6 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! In convert_file_to_np l 337 : 6 l343 6 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.004222393035888672 time to convert the images to numpy array : 0.034742116928100586 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.005431175231933594 time to convert the images to numpy array : 0.037020206451416016 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.006081342697143555 time to convert the images to numpy array : 0.03741121292114258 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.009220361709594727 time to convert the images to numpy array : 0.03252911567687988 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.003989458084106445 time to convert the images to numpy array : 0.039742231369018555 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.008023262023925781 time to convert the images to numpy array : 0.036167144775390625 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.004550933837890625 time to convert the images to numpy array : 0.04032731056213379 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.008069992065429688 time to convert the images to numpy array : 0.037108421325683594 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.0073375701904296875 time to convert the images to numpy array : 0.037828922271728516 l357 after caffe.io.load_image dimension du image : (3, (224, 224, 3)) dimension displayed ! time to import caffe and check if the image exist : 0.007784843444824219 time to convert the images to numpy array : 0.040216922760009766 333333333 3 3 àtotal time to convert the images to numpy array : 0.04877209663391113 list photo_ids error: [] list photo_ids correct : [987515208, 987515209, 987515211, 987515213, 987515215, 987515216, 987515182, 987515183, 987515184, 987515185, 987515186, 987515187, 987515176, 987515177, 987515178, 987515179, 987515180, 987515181, 987515226, 987515227, 987515228, 987515230, 987515231, 987515232, 987515245, 987515246, 987515247, 987515249, 987515250, 987515207, 987515189, 987515190, 987515192, 987515193, 987515196, 987515198, 987515217, 987515219, 987515220, 987515222, 987515223, 987515188, 987515200, 987515201, 987515202, 987515204, 987515205, 987515224, 987515233, 987515234, 987515235, 987515236, 987515237, 987515238, 987515239, 987515240, 987515241, 987515242, 987515243, 987515244] number of photos to traite : 60 try to delete the photos incorrect in DB tagging for thcl : 1528 To do loadFromThcl(), then load ParamDescType : thcl1528 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (1528) thcls : [{'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'}] thcl {'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'} Update svm_hashtag_type_desc : 4421 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (4421) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (4421, 'learn_refus_upm_blanches_1924', 16384, 25088, 'learn_refus_upm_blanches_1924', 'res5b', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2019, 10, 22, 17, 39, 25), datetime.datetime(2019, 10, 22, 17, 39, 25)) To loadFromThcl() : net_4421 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 2930 max_wait_temp : 1 max_wait : 0 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (4421) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (4421, 'learn_refus_upm_blanches_1924', 16384, 25088, 'learn_refus_upm_blanches_1924', 'res5b', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2019, 10, 22, 17, 39, 25), datetime.datetime(2019, 10, 22, 17, 39, 25)) param : , param.caffemodel : learn_refus_upm_blanches_1924 None mean_file_type : mean_file_path : prototxt_file_path : model : learn_refus_upm_blanches_1924 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : learn_refus_upm_blanches_1924 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_refus_upm_blanches_1924 /data/models_weight/learn_refus_upm_blanches_1924/caffemodel size_local : 45774543 size in s3 : 45774543 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 caffemodel already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt size_local : 17312 size in s3 : 17312 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:03 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:05 mean.npy already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/synset_words.txt size_local : 218 size in s3 : 218 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/caffe_cuda8_python3/python/:/home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/:/home/admin/workarea/git/apy/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt caffemodel_filename : /data/models_weight/learn_refus_upm_blanches_1924/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 2930 max_wait_temp : 1 max_wait : 0 dict_keys(['prob', 'res5b']) time used to do the prepocess of the images : 0.051714420318603516 time used to do the prediction : 0.1407151222229004 save descriptor for thcl : 1528 (60, 512, 7, 7) Got the blobs of the net to insert : [0, 0, 0, 1, 2, 2, 0, 1, 0, 0] code_as_byte_string:b'0000000102'| Got the blobs of the net to insert : [1, 0, 0, 1, 1, 1, 0, 1, 1, 3] code_as_byte_string:b'0100000101'| Got the blobs of the net to insert : [1, 1, 2, 3, 4, 4, 1, 2, 8, 7] code_as_byte_string:b'0101020304'| Got the blobs of the net to insert : [6, 8, 5, 7, 7, 8, 10, 12, 12, 6] code_as_byte_string:b'0608050707'| Got the blobs of the net to insert : [5, 5, 4, 3, 5, 6, 3, 4, 3, 3] code_as_byte_string:b'0505040305'| Got the blobs of the net to insert : [5, 3, 3, 1, 1, 1, 2, 2, 2, 4] code_as_byte_string:b'0503030101'| Got the blobs of the net to insert : [4, 6, 6, 4, 7, 8, 8, 8, 12, 8] code_as_byte_string:b'0406060407'| Got the blobs of the net to insert : [11, 8, 5, 9, 12, 14, 13, 14, 12, 6] code_as_byte_string:b'0b0805090c'| Got the blobs of the net to insert : [8, 7, 6, 4, 2, 1, 2, 4, 4, 4] code_as_byte_string:b'0807060402'| Got the blobs of the net to insert : [2, 3, 5, 5, 2, 2, 3, 0, 1, 4] code_as_byte_string:b'0203050502'| Got the blobs of the net to insert : [0, 0, 0, 1, 1, 1, 3, 3, 0, 0] code_as_byte_string:b'0000000101'| Got the blobs of the net to insert : [3, 1, 1, 1, 1, 1, 2, 1, 1, 2] code_as_byte_string:b'0301010101'| Got the blobs of the net to insert : [13, 9, 9, 8, 11, 13, 6, 14, 9, 18] code_as_byte_string:b'0d0909080b'| Got the blobs of the net to insert : [2, 2, 6, 7, 8, 6, 4, 3, 1, 8] code_as_byte_string:b'0202060708'| Got the blobs of the net to insert : [1, 2, 2, 1, 0, 1, 1, 2, 1, 1] code_as_byte_string:b'0102020100'| Got the blobs of the net to insert : [2, 2, 1, 3, 2, 3, 2, 0, 0, 1] code_as_byte_string:b'0202010302'| Got the blobs of the net to insert : [1, 0, 1, 2, 1, 0, 3, 3, 3, 8] code_as_byte_string:b'0100010201'| Got the blobs of the net to insert : [5, 5, 6, 4, 3, 6, 9, 7, 7, 7] code_as_byte_string:b'0505060403'| Got the blobs of the net to insert : [3, 3, 3, 1, 6, 7, 10, 5, 3, 5] code_as_byte_string:b'0303030106'| Got the blobs of the net to insert : [3, 2, 2, 1, 1, 2, 2, 3, 2, 5] code_as_byte_string:b'0302020101'| Got the blobs of the net to insert : [1, 0, 3, 1, 0, 0, 0, 0, 0, 5] code_as_byte_string:b'0100030100'| Got the blobs of the net to insert : [0, 0, 2, 2, 0, 0, 0, 0, 0, 3] code_as_byte_string:b'0000020200'| Got the blobs of the net to insert : [1, 1, 2, 1, 0, 0, 0, 3, 6, 7] code_as_byte_string:b'0101020100'| Got the blobs of the net to insert : [1, 3, 3, 3, 0, 1, 5, 6, 7, 4] code_as_byte_string:b'0103030300'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 1, 3, 1, 0] code_as_byte_string:b'0000000000'| Got the blobs of the net to insert : [0, 0, 0, 1, 0, 0, 0, 0, 1, 3] code_as_byte_string:b'0000000100'| Got the blobs of the net to insert : [0, 0, 0, 1, 2, 0, 1, 4, 0, 2] code_as_byte_string:b'0000000102'| Got the blobs of the net to insert : [4, 1, 3, 4, 7, 3, 4, 2, 1, 0] code_as_byte_string:b'0401030407'| Got the blobs of the net to insert : [3, 3, 1, 4, 7, 7, 9, 6, 2, 1] code_as_byte_string:b'0303010407'| Got the blobs of the net to insert : [4, 2, 1, 2, 3, 1, 0, 1, 0, 1] code_as_byte_string:b'0402010203'| Got the blobs of the net to insert : [3, 2, 1, 4, 5, 7, 6, 5, 6, 5] code_as_byte_string:b'0302010405'| Got the blobs of the net to insert : [3, 4, 5, 5, 9, 9, 9, 9, 11, 7] code_as_byte_string:b'0304050509'| Got the blobs of the net to insert : [5, 3, 3, 6, 8, 12, 9, 9, 3, 5] code_as_byte_string:b'0503030608'| Got the blobs of the net to insert : [6, 3, 3, 0, 1, 2, 2, 5, 2, 4] code_as_byte_string:b'0603030001'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 2, 5, 1, 0, 0] code_as_byte_string:b'0000000000'| Got the blobs of the net to insert : [1, 1, 0, 0, 1, 2, 0, 0, 0, 1] code_as_byte_string:b'0101000001'| Got the blobs of the net to insert : [2, 1, 2, 2, 2, 0, 0, 1, 0, 3] code_as_byte_string:b'0201020202'| Got the blobs of the net to insert : [0, 0, 2, 3, 3, 1, 0, 0, 0, 0] code_as_byte_string:b'0000020303'| Got the blobs of the net to insert : [1, 0, 0, 1, 0, 0, 0, 3, 4, 5] code_as_byte_string:b'0100000100'| Got the blobs of the net to insert : [0, 1, 1, 4, 2, 1, 3, 7, 9, 9] code_as_byte_string:b'0001010402'| Got the blobs of the net to insert : [7, 10, 10, 2, 4, 7, 8, 5, 5, 2] code_as_byte_string:b'070a0a0204'| Got the blobs of the net to insert : [1, 1, 1, 2, 0, 3, 4, 3, 4, 5] code_as_byte_string:b'0101010200'| Got the blobs of the net to insert : [0, 1, 0, 1, 3, 4, 2, 1, 3, 5] code_as_byte_string:b'0001000103'| Got the blobs of the net to insert : [3, 3, 3, 8, 7, 5, 5, 4, 5, 3] code_as_byte_string:b'0303030807'| Got the blobs of the net to insert : [2, 5, 4, 6, 9, 9, 10, 9, 11, 5] code_as_byte_string:b'0205040609'| Got the blobs of the net to insert : [5, 2, 3, 7, 5, 7, 6, 2, 4, 3] code_as_byte_string:b'0502030705'| Got the blobs of the net to insert : [5, 7, 3, 2, 1, 2, 2, 2, 0, 0] code_as_byte_string:b'0507030201'| Got the blobs of the net to insert : [7, 7, 3, 8, 9, 6, 7, 10, 11, 6] code_as_byte_string:b'0707030809'| Got the blobs of the net to insert : [5, 7, 3, 2, 5, 9, 10, 3, 5, 0] code_as_byte_string:b'0507030205'| Got the blobs of the net to insert : [6, 8, 3, 6, 6, 6, 5, 10, 10, 3] code_as_byte_string:b'0608030606'| Got the blobs of the net to insert : [1, 2, 1, 5, 7, 10, 8, 2, 2, 1] code_as_byte_string:b'0102010507'| Got the blobs of the net to insert : [0, 0, 0, 1, 5, 4, 6, 3, 1, 3] code_as_byte_string:b'0000000105'| Got the blobs of the net to insert : [0, 2, 1, 0, 0, 0, 0, 0, 4, 2] code_as_byte_string:b'0002010000'| Got the blobs of the net to insert : [0, 2, 0, 1, 1, 0, 0, 0, 1, 3] code_as_byte_string:b'0002000101'| Got the blobs of the net to insert : [1, 1, 0, 0, 0, 0, 0, 3, 5, 1] code_as_byte_string:b'0101000000'| Got the blobs of the net to insert : [0, 3, 0, 1, 1, 6, 7, 5, 5, 3] code_as_byte_string:b'0003000101'| Got the blobs of the net to insert : [6, 6, 3, 3, 8, 8, 6, 6, 2, 0] code_as_byte_string:b'0606030308'| Got the blobs of the net to insert : [5, 5, 2, 4, 6, 5, 9, 9, 4, 2] code_as_byte_string:b'0505020406'| Got the blobs of the net to insert : [2, 1, 3, 5, 7, 5, 3, 4, 1, 3] code_as_byte_string:b'0201030507'| Got the blobs of the net to insert : [0, 0, 0, 1, 1, 3, 2, 1, 0, 2] code_as_byte_string:b'0000000101'| time to traite the descriptors : 2.8920445442199707 Testing : ['987515208', '987515209', '987515211', '987515213', '987515215', '987515216', '987515182', '987515183', '987515184', '987515185', '987515186', '987515187', '987515176', '987515177', '987515178', '987515179', '987515180', '987515181', '987515226', '987515227', '987515228', '987515230', '987515231', '987515232', '987515245', '987515246', '987515247', '987515249', '987515250', '987515207', '987515189', '987515190', '987515192', '987515193', '987515196', '987515198', '987515217', '987515219', '987515220', '987515222', '987515223', '987515188', '987515200', '987515201', '987515202', '987515204', '987515205', '987515224', '987515233', '987515234', '987515235', '987515236', '987515237', '987515238', '987515239', '987515240', '987515241', '987515242', '987515243', '987515244'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (987515208,987515209,987515211,987515213,987515215,987515216,987515182,987515183,987515184,987515185,987515186,987515187,987515176,987515177,987515178,987515179,987515180,987515181,987515226,987515227,987515228,987515230,987515231,987515232,987515245,987515246,987515247,987515249,987515250,987515207,987515189,987515190,987515192,987515193,987515196,987515198,987515217,987515219,987515220,987515222,987515223,987515188,987515200,987515201,987515202,987515204,987515205,987515224,987515233,987515234,987515235,987515236,987515237,987515238,987515239,987515240,987515241,987515242,987515243,987515244) result : {987515176: {'photo_id': 987515176, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/8b398cba2f448622cd9657f5eb3f9796.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_144.jpg'}, 987515177: {'photo_id': 987515177, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/4a54e9967227806219ddf45d256539d8.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_176.jpg'}, 987515178: {'photo_id': 987515178, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/298b3d2bfe0fda6787b59a78e2e68867.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_208.jpg'}, 987515179: {'photo_id': 987515179, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/f7d4d1757a470f4c96dc3541eac88b9e.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_240.jpg'}, 987515180: {'photo_id': 987515180, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/776a5d7d8486ee2961bbe3a0d90f95b5.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_272.jpg'}, 987515181: {'photo_id': 987515181, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/1738c2798fb31152809ecb443ac286d6.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_304.jpg'}, 987515182: {'photo_id': 987515182, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/fe7f29bf6d13e08c3e985f91b5232178.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_112_y_336.jpg'}, 987515183: {'photo_id': 987515183, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/6aab9ca0421398b4899892c10c2594c6.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_112.jpg'}, 987515184: {'photo_id': 987515184, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/19c8c2177209a285df6014d95fe53f2c.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_144.jpg'}, 987515185: {'photo_id': 987515185, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e172d54457cabee9d7f02ee1300f3ae9.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_176.jpg'}, 987515186: {'photo_id': 987515186, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/797def426440b544aa80dbd63a19234a.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_208.jpg'}, 987515187: {'photo_id': 987515187, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/9f62f98efd3caca0b9c17d27f5c70440.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_240.jpg'}, 987515188: {'photo_id': 987515188, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/4116f9906657a69bb76c2fda982037b9.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_272.jpg'}, 987515189: {'photo_id': 987515189, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/8e8590a26f72249d4c2116dffd0cf668.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_304.jpg'}, 987515190: {'photo_id': 987515190, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/d56932bfc6ba2a8c974c691108755017.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_144_y_336.jpg'}, 987515192: {'photo_id': 987515192, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/b661073b218f5f056833d6af1c617153.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_112.jpg'}, 987515193: {'photo_id': 987515193, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/1a97fceb4dcbf5821d783b2e00b52fe6.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_144.jpg'}, 987515196: {'photo_id': 987515196, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/30ccb89dfe410c445878a7f2819ddc36.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_208.jpg'}, 987515198: {'photo_id': 987515198, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/599e80f444c876f407e94b533c89360b.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_240.jpg'}, 987515200: {'photo_id': 987515200, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/978964436b5d5fb0eeda17e3bfafe889.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_272.jpg'}, 987515201: {'photo_id': 987515201, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/b224d2acdc7fa2bbb134c09db6bca7ce.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_304.jpg'}, 987515202: {'photo_id': 987515202, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/3314bd90d1404f31b827d8925abf2d62.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_176_y_336.jpg'}, 987515204: {'photo_id': 987515204, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/9779c4f9d44360a9c80499e3b01e8a09.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_112.jpg'}, 987515205: {'photo_id': 987515205, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/fd4b136d0b3a9a1a347942d7191f6fea.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_144.jpg'}, 987515207: {'photo_id': 987515207, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/de216ddb041e249524b0fb2b949064a5.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_176.jpg'}, 987515208: {'photo_id': 987515208, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/a2b90cb74908aa64bbc4aae58f0c5ae8.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_208.jpg'}, 987515209: {'photo_id': 987515209, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/02dfe1ae39f51994652f4a8538844aea.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_240.jpg'}, 987515211: {'photo_id': 987515211, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/72cc7664d45bd40477351b9b764f1500.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_272.jpg'}, 987515213: {'photo_id': 987515213, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_208_y_336.jpg'}, 987515215: {'photo_id': 987515215, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/902ef348a7eebb9a8b87f42927347936.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_112.jpg'}, 987515216: {'photo_id': 987515216, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/4f7dc21f1d2cd3fcabadc4a6755921e1.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_144.jpg'}, 987515217: {'photo_id': 987515217, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/78877bb2c5760be28518d17f77d1c609.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_176.jpg'}, 987515219: {'photo_id': 987515219, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/c2d417a5ba6ccf7c84527636f8d5eef9.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_208.jpg'}, 987515220: {'photo_id': 987515220, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e729f316c4c3b32049adfbaaa336d95c.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_240.jpg'}, 987515222: {'photo_id': 987515222, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/067a027bc7402f969b6277d0dcb47eaa.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_272.jpg'}, 987515223: {'photo_id': 987515223, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/ebb57f09941cd11d7ee45a9368a883c1.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_304.jpg'}, 987515224: {'photo_id': 987515224, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e8747b400e713ecbd08d5b75db4d7568.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_240_y_336.jpg'}, 987515226: {'photo_id': 987515226, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/a18048dca1a77ae086b62cf07759f704.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_112.jpg'}, 987515227: {'photo_id': 987515227, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e9c45a0e576ec9e44c1379c3fc5fec7c.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_144.jpg'}, 987515228: {'photo_id': 987515228, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/9f1759f20c9e603bccb9f9879d2f0d54.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_176.jpg'}, 987515230: {'photo_id': 987515230, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/846ad925884264181565c81d152a2e94.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_208.jpg'}, 987515231: {'photo_id': 987515231, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/dbf4cafa71b6db4771c5c8f0c25e9cda.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_240.jpg'}, 987515232: {'photo_id': 987515232, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/38db7950cdb3c674ee0ad65915b021f3.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_272.jpg'}, 987515233: {'photo_id': 987515233, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/a92514bed0e8c5724f2d032d3ab1e2ad.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_304.jpg'}, 987515234: {'photo_id': 987515234, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/2eca3480aed0f8b876242675ad99b666.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_272_y_336.jpg'}, 987515235: {'photo_id': 987515235, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/87075955a2f76b3948b47ffe1825ecd9.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_112.jpg'}, 987515236: {'photo_id': 987515236, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/8b44a98b1aceadad73ed000d65836a9a.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_144.jpg'}, 987515237: {'photo_id': 987515237, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/1183dfa371a457f11ce2b622c7cf9467.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_176.jpg'}, 987515238: {'photo_id': 987515238, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e6292cb81e05894cfeb4b99f21a1d3f8.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_208.jpg'}, 987515239: {'photo_id': 987515239, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/b3fa6f29636080b5138c8d8c33fea309.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_240.jpg'}, 987515240: {'photo_id': 987515240, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/7829b9b15f1bf128ea4e2c1a39b9f0dd.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_272.jpg'}, 987515241: {'photo_id': 987515241, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/073420d938f5f010ffd5b4353c064e09.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_304.jpg'}, 987515242: {'photo_id': 987515242, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/327abb5215d6fd1f0aad51f53ed8c324.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_304_y_336.jpg'}, 987515243: {'photo_id': 987515243, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/4375283f3bc5cdaa431c2fc6f17f53a4.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_112.jpg'}, 987515244: {'photo_id': 987515244, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/419530eaef5ef868f75c758b94eea4b4.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_144.jpg'}, 987515245: {'photo_id': 987515245, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/757d9d208d5bd4375c5f21f68b699148.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_176.jpg'}, 987515246: {'photo_id': 987515246, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/671a708f67f2efa19004b8257fc7b9c8.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_208.jpg'}, 987515247: {'photo_id': 987515247, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/e47b65403df916ba909bc9c439b0af73.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_240.jpg'}, 987515249: {'photo_id': 987515249, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/a70ad88462a22fb62a120721a42b2d42.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_304.jpg'}, 987515250: {'photo_id': 987515250, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2019/11/22/b2827c9639df69656f23abcc7f2f82d9.jpg', 'latitude': None, 'longitude': None, 'text': 'photo_origin_x_336_y_336.jpg'}} list_photo_exists : [987515176, 987515177, 987515178, 987515179, 987515180, 987515181, 987515182, 987515183, 987515184, 987515185, 987515186, 987515187, 987515188, 987515189, 987515190, 987515192, 987515193, 987515196, 987515198, 987515200, 987515201, 987515202, 987515204, 987515205, 987515207, 987515208, 987515209, 987515211, 987515213, 987515215, 987515216, 987515217, 987515219, 987515220, 987515222, 987515223, 987515224, 987515226, 987515227, 987515228, 987515230, 987515231, 987515232, 987515233, 987515234, 987515235, 987515236, 987515237, 987515238, 987515239, 987515240, 987515241, 987515242, 987515243, 987515244, 987515245, 987515246, 987515247, 987515249, 987515250] storage_type for insertDescriptorsMulti : 1 To insert : 987515208 To insert : 987515209 To insert : 987515211 To insert : 987515213 To insert : 987515215 To insert : 987515216 To insert : 987515182 To insert : 987515183 To insert : 987515184 To insert : 987515185 To insert : 987515186 To insert : 987515187 To insert : 987515176 To insert : 987515177 To insert : 987515178 To insert : 987515179 To insert : 987515180 To insert : 987515181 To insert : 987515226 To insert : 987515227 To insert : 987515228 To insert : 987515230 To insert : 987515231 To insert : 987515232 To insert : 987515245 To insert : 987515246 To insert : 987515247 To insert : 987515249 To insert : 987515250 To insert : 987515207 To insert : 987515189 To insert : 987515190 To insert : 987515192 To insert : 987515193 To insert : 987515196 To insert : 987515198 To insert : 987515217 To insert : 987515219 To insert : 987515220 To insert : 987515222 To insert : 987515223 To insert : 987515188 To insert : 987515200 To insert : 987515201 To insert : 987515202 To insert : 987515204 To insert : 987515205 To insert : 987515224 To insert : 987515233 To insert : 987515234 To insert : 987515235 To insert : 987515236 To insert : 987515237 To insert : 987515238 To insert : 987515239 To insert : 987515240 To insert : 987515241 To insert : 987515242 To insert : 987515243 To insert : 987515244 time to insert the descriptors : 11.62028455734253 After datou_step_exec type output : time spend for datou_step_exec : 18.355818033218384 time spend to save output : 8.440017700195312e-05 total time spend for step 1 : 18.355902433395386 step2:argmax Thu Sep 25 17:05:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : 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'extension': 'jpg'}, 987515217: {'path': 'temp/1758812679_3157952_987515217_78877bb2c5760be28518d17f77d1c609.jpg', 'extension': 'jpg'}, 987515219: {'path': 'temp/1758812679_3157952_987515219_c2d417a5ba6ccf7c84527636f8d5eef9.jpg', 'extension': 'jpg'}, 987515220: {'path': 'temp/1758812679_3157952_987515220_e729f316c4c3b32049adfbaaa336d95c.jpg', 'extension': 'jpg'}, 987515222: {'path': 'temp/1758812679_3157952_987515222_067a027bc7402f969b6277d0dcb47eaa.jpg', 'extension': 'jpg'}, 987515223: {'path': 'temp/1758812679_3157952_987515223_ebb57f09941cd11d7ee45a9368a883c1.jpg', 'extension': 'jpg'}, 987515188: {'path': 'temp/1758812679_3157952_987515188_4116f9906657a69bb76c2fda982037b9.jpg', 'extension': 'jpg'}, 987515189: {'path': 'temp/1758812679_3157952_987515189_8e8590a26f72249d4c2116dffd0cf668.jpg', 'extension': 'jpg'}, 987515190: {'path': 'temp/1758812679_3157952_987515190_d56932bfc6ba2a8c974c691108755017.jpg', 'extension': 'jpg'}, 987515192: {'path': 'temp/1758812679_3157952_987515192_b661073b218f5f056833d6af1c617153.jpg', 'extension': 'jpg'}, 987515193: {'path': 'temp/1758812679_3157952_987515193_1a97fceb4dcbf5821d783b2e00b52fe6.jpg', 'extension': 'jpg'}, 987515196: {'path': 'temp/1758812679_3157952_987515196_30ccb89dfe410c445878a7f2819ddc36.jpg', 'extension': 'jpg'}, 987515198: {'path': 'temp/1758812679_3157952_987515198_599e80f444c876f407e94b533c89360b.jpg', 'extension': 'jpg'}, 987515200: {'path': 'temp/1758812679_3157952_987515200_978964436b5d5fb0eeda17e3bfafe889.jpg', 'extension': 'jpg'}, 987515201: {'path': 'temp/1758812679_3157952_987515201_b224d2acdc7fa2bbb134c09db6bca7ce.jpg', 'extension': 'jpg'}, 987515202: {'path': 'temp/1758812679_3157952_987515202_3314bd90d1404f31b827d8925abf2d62.jpg', 'extension': 'jpg'}, 987515204: {'path': 'temp/1758812679_3157952_987515204_9779c4f9d44360a9c80499e3b01e8a09.jpg', 'extension': 'jpg'}, 987515205: {'path': 'temp/1758812679_3157952_987515205_fd4b136d0b3a9a1a347942d7191f6fea.jpg', 'extension': 'jpg'}, 987515224: {'path': 'temp/1758812679_3157952_987515224_e8747b400e713ecbd08d5b75db4d7568.jpg', 'extension': 'jpg'}, 987515226: {'path': 'temp/1758812679_3157952_987515226_a18048dca1a77ae086b62cf07759f704.jpg', 'extension': 'jpg'}, 987515227: {'path': 'temp/1758812679_3157952_987515227_e9c45a0e576ec9e44c1379c3fc5fec7c.jpg', 'extension': 'jpg'}, 987515228: {'path': 'temp/1758812679_3157952_987515228_9f1759f20c9e603bccb9f9879d2f0d54.jpg', 'extension': 'jpg'}, 987515230: {'path': 'temp/1758812679_3157952_987515230_846ad925884264181565c81d152a2e94.jpg', 'extension': 'jpg'}, 987515231: {'path': 'temp/1758812679_3157952_987515231_dbf4cafa71b6db4771c5c8f0c25e9cda.jpg', 'extension': 'jpg'}, 987515232: {'path': 'temp/1758812679_3157952_987515232_38db7950cdb3c674ee0ad65915b021f3.jpg', 'extension': 'jpg'}, 987515233: {'path': 'temp/1758812679_3157952_987515233_a92514bed0e8c5724f2d032d3ab1e2ad.jpg', 'extension': 'jpg'}, 987515234: {'path': 'temp/1758812679_3157952_987515234_2eca3480aed0f8b876242675ad99b666.jpg', 'extension': 'jpg'}, 987515235: {'path': 'temp/1758812679_3157952_987515235_87075955a2f76b3948b47ffe1825ecd9.jpg', 'extension': 'jpg'}, 987515236: {'path': 'temp/1758812679_3157952_987515236_8b44a98b1aceadad73ed000d65836a9a.jpg', 'extension': 'jpg'}, 987515237: {'path': 'temp/1758812679_3157952_987515237_1183dfa371a457f11ce2b622c7cf9467.jpg', 'extension': 'jpg'}, 987515238: {'path': 'temp/1758812679_3157952_987515238_e6292cb81e05894cfeb4b99f21a1d3f8.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! calculate argmax for thcl : 1528 After datou_step_exec type output : time spend for datou_step_exec : 0.0011022090911865234 time spend to save output : 0.00011849403381347656 total time spend for step 2 : 0.001220703125 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'987515208': [('987515208', 'Carton', 0.9917299, 1927, '1528'), 'temp/1758812679_3157952_987515208_a2b90cb74908aa64bbc4aae58f0c5ae8.jpg'], '987515209': [('987515209', 'Carton', 0.96777135, 1927, '1528'), 'temp/1758812679_3157952_987515209_02dfe1ae39f51994652f4a8538844aea.jpg'], '987515211': [('987515211', 'Carton', 0.973517, 1927, '1528'), 'temp/1758812679_3157952_987515211_72cc7664d45bd40477351b9b764f1500.jpg'], '987515213': [('987515213', 'Carton', 0.9869299, 1927, '1528'), 'temp/1758812679_3157952_987515213_b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg'], '987515215': [('987515215', 'Papier_Magazine', 0.9939454, 1927, '1528'), 'temp/1758812679_3157952_987515215_902ef348a7eebb9a8b87f42927347936.jpg'], '987515216': [('987515216', 'Papier_Magazine', 0.97745854, 1927, '1528'), 'temp/1758812679_3157952_987515216_4f7dc21f1d2cd3fcabadc4a6755921e1.jpg'], '987515182': [('987515182', 'Carton', 0.9924349, 1927, '1528'), 'temp/1758812679_3157952_987515182_fe7f29bf6d13e08c3e985f91b5232178.jpg'], '987515183': [('987515183', 'Papier_Magazine', 0.99999213, 1927, '1528'), 'temp/1758812679_3157952_987515183_6aab9ca0421398b4899892c10c2594c6.jpg'], '987515184': [('987515184', 'Papier_Magazine', 0.99973196, 1927, '1528'), 'temp/1758812679_3157952_987515184_19c8c2177209a285df6014d95fe53f2c.jpg'], '987515185': [('987515185', 'Papier_Magazine', 0.79789877, 1927, '1528'), 'temp/1758812679_3157952_987515185_e172d54457cabee9d7f02ee1300f3ae9.jpg'], '987515186': [('987515186', 'Carton', 0.9847142, 1927, '1528'), 'temp/1758812679_3157952_987515186_797def426440b544aa80dbd63a19234a.jpg'], '987515187': [('987515187', 'Carton', 0.9811886, 1927, '1528'), 'temp/1758812679_3157952_987515187_9f62f98efd3caca0b9c17d27f5c70440.jpg'], '987515176': [('987515176', 'Papier_Magazine', 0.9998136, 1927, '1528'), 'temp/1758812679_3157952_987515176_8b398cba2f448622cd9657f5eb3f9796.jpg'], '987515177': [('987515177', 'Papier_Magazine', 0.9771638, 1927, '1528'), 'temp/1758812679_3157952_987515177_4a54e9967227806219ddf45d256539d8.jpg'], '987515178': [('987515178', 'Carton', 0.8578075, 1927, '1528'), 'temp/1758812679_3157952_987515178_298b3d2bfe0fda6787b59a78e2e68867.jpg'], '987515179': [('987515179', 'Carton', 0.9269084, 1927, '1528'), 'temp/1758812679_3157952_987515179_f7d4d1757a470f4c96dc3541eac88b9e.jpg'], '987515180': [('987515180', 'Carton', 0.98999035, 1927, '1528'), 'temp/1758812679_3157952_987515180_776a5d7d8486ee2961bbe3a0d90f95b5.jpg'], '987515181': [('987515181', 'Carton', 0.9977792, 1927, '1528'), 'temp/1758812679_3157952_987515181_1738c2798fb31152809ecb443ac286d6.jpg'], '987515226': [('987515226', 'Papier_Magazine', 0.98698527, 1927, '1528'), 'temp/1758812679_3157952_987515226_a18048dca1a77ae086b62cf07759f704.jpg'], '987515227': [('987515227', 'Papier_Magazine', 0.9001, 1927, '1528'), 'temp/1758812679_3157952_987515227_e9c45a0e576ec9e44c1379c3fc5fec7c.jpg'], '987515228': [('987515228', 'Papier_Magazine', 0.52130806, 1927, '1528'), 'temp/1758812679_3157952_987515228_9f1759f20c9e603bccb9f9879d2f0d54.jpg'], '987515230': [('987515230', 'Carton', 0.9994061, 1927, '1528'), 'temp/1758812679_3157952_987515230_846ad925884264181565c81d152a2e94.jpg'], '987515231': [('987515231', 'Carton', 0.9994211, 1927, '1528'), 'temp/1758812679_3157952_987515231_dbf4cafa71b6db4771c5c8f0c25e9cda.jpg'], '987515232': [('987515232', 'Carton', 0.99924326, 1927, '1528'), 'temp/1758812679_3157952_987515232_38db7950cdb3c674ee0ad65915b021f3.jpg'], '987515245': [('987515245', 'Carton', 0.86571115, 1927, '1528'), 'temp/1758812679_3157952_987515245_757d9d208d5bd4375c5f21f68b699148.jpg'], '987515246': [('987515246', 'Carton', 0.9992335, 1927, '1528'), 'temp/1758812679_3157952_987515246_671a708f67f2efa19004b8257fc7b9c8.jpg'], '987515247': [('987515247', 'Carton', 0.9996648, 1927, '1528'), 'temp/1758812679_3157952_987515247_e47b65403df916ba909bc9c439b0af73.jpg'], '987515249': [('987515249', 'Carton', 0.9813059, 1927, '1528'), 'temp/1758812679_3157952_987515249_a70ad88462a22fb62a120721a42b2d42.jpg'], '987515250': [('987515250', 'Carton', 0.9808235, 1927, '1528'), 'temp/1758812679_3157952_987515250_b2827c9639df69656f23abcc7f2f82d9.jpg'], '987515207': [('987515207', 'Papier_Magazine', 0.87375265, 1927, '1528'), 'temp/1758812679_3157952_987515207_de216ddb041e249524b0fb2b949064a5.jpg'], '987515189': [('987515189', 'Carton', 0.9977939, 1927, '1528'), 'temp/1758812679_3157952_987515189_8e8590a26f72249d4c2116dffd0cf668.jpg'], '987515190': [('987515190', 'Carton', 0.9762314, 1927, '1528'), 'temp/1758812679_3157952_987515190_d56932bfc6ba2a8c974c691108755017.jpg'], '987515192': [('987515192', 'Papier_Magazine', 0.99991155, 1927, '1528'), 'temp/1758812679_3157952_987515192_b661073b218f5f056833d6af1c617153.jpg'], '987515193': [('987515193', 'Papier_Magazine', 0.9993961, 1927, '1528'), 'temp/1758812679_3157952_987515193_1a97fceb4dcbf5821d783b2e00b52fe6.jpg'], '987515196': [('987515196', 'Carton', 0.9846747, 1927, '1528'), 'temp/1758812679_3157952_987515196_30ccb89dfe410c445878a7f2819ddc36.jpg'], '987515198': [('987515198', 'Carton', 0.96613806, 1927, '1528'), 'temp/1758812679_3157952_987515198_599e80f444c876f407e94b533c89360b.jpg'], '987515217': [('987515217', 'Carton', 0.5285645, 1927, '1528'), 'temp/1758812679_3157952_987515217_78877bb2c5760be28518d17f77d1c609.jpg'], '987515219': [('987515219', 'Carton', 0.9993698, 1927, '1528'), 'temp/1758812679_3157952_987515219_c2d417a5ba6ccf7c84527636f8d5eef9.jpg'], '987515220': [('987515220', 'Carton', 0.99638546, 1927, '1528'), 'temp/1758812679_3157952_987515220_e729f316c4c3b32049adfbaaa336d95c.jpg'], '987515222': [('987515222', 'Carton', 0.9974716, 1927, '1528'), 'temp/1758812679_3157952_987515222_067a027bc7402f969b6277d0dcb47eaa.jpg'], '987515223': [('987515223', 'Carton', 0.99208087, 1927, '1528'), 'temp/1758812679_3157952_987515223_ebb57f09941cd11d7ee45a9368a883c1.jpg'], '987515188': [('987515188', 'Carton', 0.99565256, 1927, '1528'), 'temp/1758812679_3157952_987515188_4116f9906657a69bb76c2fda982037b9.jpg'], '987515200': [('987515200', 'Carton', 0.9859395, 1927, '1528'), 'temp/1758812679_3157952_987515200_978964436b5d5fb0eeda17e3bfafe889.jpg'], '987515201': [('987515201', 'Carton', 0.9954726, 1927, '1528'), 'temp/1758812679_3157952_987515201_b224d2acdc7fa2bbb134c09db6bca7ce.jpg'], '987515202': [('987515202', 'Carton', 0.9910965, 1927, '1528'), 'temp/1758812679_3157952_987515202_3314bd90d1404f31b827d8925abf2d62.jpg'], '987515204': [('987515204', 'Papier_Magazine', 0.9950883, 1927, '1528'), 'temp/1758812679_3157952_987515204_9779c4f9d44360a9c80499e3b01e8a09.jpg'], '987515205': [('987515205', 'Papier_Magazine', 0.99084806, 1927, '1528'), 'temp/1758812679_3157952_987515205_fd4b136d0b3a9a1a347942d7191f6fea.jpg'], '987515224': [('987515224', 'Carton', 0.9085642, 1927, '1528'), 'temp/1758812679_3157952_987515224_e8747b400e713ecbd08d5b75db4d7568.jpg'], '987515233': [('987515233', 'Carton', 0.98341644, 1927, '1528'), 'temp/1758812679_3157952_987515233_a92514bed0e8c5724f2d032d3ab1e2ad.jpg'], '987515234': [('987515234', 'Carton', 0.94478667, 1927, '1528'), 'temp/1758812679_3157952_987515234_2eca3480aed0f8b876242675ad99b666.jpg'], '987515235': [('987515235', 'Papier_Magazine', 0.89180875, 1927, '1528'), 'temp/1758812679_3157952_987515235_87075955a2f76b3948b47ffe1825ecd9.jpg'], '987515236': [('987515236', 'Papier_Magazine', 0.5377576, 1927, '1528'), 'temp/1758812679_3157952_987515236_8b44a98b1aceadad73ed000d65836a9a.jpg'], '987515237': [('987515237', 'Carton', 0.7702882, 1927, '1528'), 'temp/1758812679_3157952_987515237_1183dfa371a457f11ce2b622c7cf9467.jpg'], '987515238': [('987515238', 'Carton', 0.9995741, 1927, '1528'), 'temp/1758812679_3157952_987515238_e6292cb81e05894cfeb4b99f21a1d3f8.jpg'], '987515239': [('987515239', 'Carton', 0.9997836, 1927, '1528'), 'temp/1758812679_3157952_987515239_b3fa6f29636080b5138c8d8c33fea309.jpg'], '987515240': [('987515240', 'Carton', 0.99952054, 1927, '1528'), 'temp/1758812679_3157952_987515240_7829b9b15f1bf128ea4e2c1a39b9f0dd.jpg'], '987515241': [('987515241', 'Carton', 0.98223835, 1927, '1528'), 'temp/1758812679_3157952_987515241_073420d938f5f010ffd5b4353c064e09.jpg'], '987515242': [('987515242', 'Carton', 0.9358871, 1927, '1528'), 'temp/1758812679_3157952_987515242_327abb5215d6fd1f0aad51f53ed8c324.jpg'], '987515243': [('987515243', 'Papier_Magazine', 0.87423676, 1927, '1528'), 'temp/1758812679_3157952_987515243_4375283f3bc5cdaa431c2fc6f17f53a4.jpg'], '987515244': [('987515244', 'Papier_Magazine', 0.8174118, 1927, '1528'), 'temp/1758812679_3157952_987515244_419530eaef5ef868f75c758b94eea4b4.jpg']} Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1879 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1879 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1879 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1879 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : detect_points list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (987515173) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 987515173 download finish for photo 987515173 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1416630744934082 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:detect_points Thu Sep 25 17:05:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812700_3157952_987515173_91fa471b1a04f95b356afdbaf021f623.jpg': 987515173} map_photo_id_path_extension : {987515173: {'path': 'temp/1758812700_3157952_987515173_91fa471b1a04f95b356afdbaf021f623.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step predict points ! Inside try reload ! classes : ['Autre_Environement', 'Carton', 'Kraft', 'Lointain_Papier_Magazine', 'Metal', 'Papier_Magazine', 'Plastique', 'Sol_Environement', 'Teint_Dans_La_Masse', 'autre_refus'] pht : 1927 model_name : learn_refus_upm_blanches_1924 {'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'} gpu_mode in detect_points : 1 To load net FromThcl() model_param file didn't exist model_name : learn_refus_upm_blanches_1924 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_refus_upm_blanches_1924 /data/models_weight/learn_refus_upm_blanches_1924/caffemodel size_local : 45774543 size in s3 : 45774543 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 caffemodel already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt size_local : 17312 size in s3 : 17312 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:03 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:05 mean.npy already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/synset_words.txt size_local : 218 size in s3 : 218 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 synset_words.txt already exist and didn't need to update reshape net's input to : (224, 224) origin shape : (10, 3, 224, 224) after reshape : (1, 3, 224, 224) [('data', (1, 3, 224, 224)), ('conv1', (1, 64, 112, 112)), ('pool1', (1, 64, 56, 56)), ('pool1_pool1_0_split_0', (1, 64, 56, 56)), ('pool1_pool1_0_split_1', (1, 64, 56, 56)), ('res2a_branch1', (1, 64, 56, 56)), ('res2a_branch2a', (1, 64, 56, 56)), ('res2a_branch2b', (1, 64, 56, 56)), ('res2a', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_0', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_1', (1, 64, 56, 56)), ('res2b_branch2a', (1, 64, 56, 56)), ('res2b_branch2b', (1, 64, 56, 56)), ('res2b', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_0', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_1', (1, 64, 56, 56)), ('res3a_branch1', (1, 128, 28, 28)), ('res3a_branch2a', (1, 128, 28, 28)), ('res3a_branch2b', (1, 128, 28, 28)), ('res3a', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_0', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_1', (1, 128, 28, 28)), ('res3b_branch2a', (1, 128, 28, 28)), ('res3b_branch2b', (1, 128, 28, 28)), ('res3b', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_0', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_1', (1, 128, 28, 28)), ('res4a_branch1', (1, 256, 14, 14)), ('res4a_branch2a', (1, 256, 14, 14)), ('res4a_branch2b', (1, 256, 14, 14)), ('res4a', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_0', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_1', (1, 256, 14, 14)), ('res4b_branch2a', (1, 256, 14, 14)), ('res4b_branch2b', (1, 256, 14, 14)), ('res4b', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_0', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_1', (1, 256, 14, 14)), ('res5a_branch1', (1, 512, 7, 7)), ('res5a_branch2a', (1, 512, 7, 7)), ('res5a_branch2b', (1, 512, 7, 7)), ('res5a', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_0', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_1', (1, 512, 7, 7)), ('res5b_branch2a', (1, 512, 7, 7)), ('res5b_branch2b', (1, 512, 7, 7)), ('res5b', (1, 512, 7, 7)), ('fc2019-10-22_15-02-46', (1, 10, 1, 1)), ('prob', (1, 10, 1, 1))] set image transformer : About to compute detect the points : len(args) : 1 Inside predict_points step exec : nb paths : 1 treate image : temp/1758812700_3157952_987515173_91fa471b1a04f95b356afdbaf021f623.jpg size of numpy array img : 2408584 scale method : caffe/skimage size of numpy array img_scale : 2408584 (448, 448, 3) nb_h 8 nb_w 8 size of sub images : (224, 224, 3) size of caffe_input : 38535320 (64, 3, 224, 224) time to do the preprocess : 0.04121971130371094 time to do a prediction : 0.2430858612060547 dict_keys(['prob']) shape of output (64, 10, 1, 1) shape of the out_put heatmap (10, 8, 8) number of sub_photos vertical and horizon 8 8 size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) After datou_step_exec type output : time spend for datou_step_exec : 1.6616744995117188 time spend to save output : 4.38690185546875e-05 total time spend for step 1 : 1.6617183685302734 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {987515173: [(987515173, 1982, 'Autre_Environement', 112, -1, 112, -1, 6.2485207980023105e-12), (987515173, 1982, 'Autre_Environement', 144, -1, 112, -1, 2.434910606474716e-11), (987515173, 1982, 'Autre_Environement', 176, -1, 112, -1, 1.0680410333918644e-08), (987515173, 1982, 'Autre_Environement', 208, -1, 112, -1, 4.456073838809971e-07), (987515173, 1982, 'Autre_Environement', 240, -1, 112, -1, 1.9237033939134562e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 112, -1, 3.766410372918472e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 112, -1, 0.00012242731463629752), (987515173, 1982, 'Autre_Environement', 336, -1, 112, -1, 2.9587723474833183e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 144, -1, 2.3726059339423955e-08), (987515173, 1982, 'Autre_Environement', 144, -1, 144, -1, 2.2144231337506426e-08), (987515173, 1982, 'Autre_Environement', 176, -1, 144, -1, 1.3774855744941306e-07), (987515173, 1982, 'Autre_Environement', 208, -1, 144, -1, 1.475110366300214e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 144, -1, 1.126193910749862e-05), (987515173, 1982, 'Autre_Environement', 272, -1, 144, -1, 0.00015784135030116886), (987515173, 1982, 'Autre_Environement', 304, -1, 144, -1, 0.00044561439426615834), (987515173, 1982, 'Autre_Environement', 336, -1, 144, -1, 6.531921098940074e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 176, -1, 1.3322739960131003e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 176, -1, 1.6207206954277353e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 176, -1, 2.5210104013240198e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 176, -1, 1.6187811979762046e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 176, -1, 6.246872089832323e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 176, -1, 8.670608076499775e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 176, -1, 0.0003276517672929913), (987515173, 1982, 'Autre_Environement', 336, -1, 176, -1, 0.0003065671189688146), (987515173, 1982, 'Autre_Environement', 112, -1, 208, -1, 1.85898898052983e-05), (987515173, 1982, 'Autre_Environement', 144, -1, 208, -1, 7.909842679509893e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 208, -1, 2.7073852834291756e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 208, -1, 1.800977588573005e-05), (987515173, 1982, 'Autre_Environement', 240, -1, 208, -1, 2.349278838664759e-05), (987515173, 1982, 'Autre_Environement', 272, -1, 208, -1, 1.6967213014140725e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 208, -1, 4.54370774605195e-06), (987515173, 1982, 'Autre_Environement', 336, -1, 208, -1, 8.79766321304487e-06), (987515173, 1982, 'Autre_Environement', 112, -1, 240, -1, 6.0943702919757925e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 240, -1, 1.6433305063401349e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 240, -1, 1.963475369848311e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 240, -1, 1.436825868950109e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 240, -1, 7.857973287173081e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 240, -1, 1.2869812962890137e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 240, -1, 9.282148312195204e-06), (987515173, 1982, 'Autre_Environement', 336, -1, 240, -1, 2.1691068468498997e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 272, -1, 3.825658950518118e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 272, -1, 2.548881866459851e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 272, -1, 2.9645077574969037e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 272, -1, 2.764108785413555e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 272, -1, 4.305159109208034e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 272, -1, 8.191986125893891e-06), (987515173, 1982, 'Autre_Environement', 304, -1, 272, -1, 1.1582290426304098e-05), (987515173, 1982, 'Autre_Environement', 336, -1, 272, -1, 3.9314869354711846e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 304, -1, 1.2066489034623373e-05), (987515173, 1982, 'Autre_Environement', 144, -1, 304, -1, 1.5724088370916434e-05), (987515173, 1982, 'Autre_Environement', 176, -1, 304, -1, 3.347870733705349e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 304, -1, 0.00015448116755578667), (987515173, 1982, 'Autre_Environement', 240, -1, 304, -1, 0.00025915473815985024), (987515173, 1982, 'Autre_Environement', 272, -1, 304, -1, 0.00018799920508172363), (987515173, 1982, 'Autre_Environement', 304, -1, 304, -1, 0.00021310188458301127), (987515173, 1982, 'Autre_Environement', 336, -1, 304, -1, 0.00016375472478102893), (987515173, 1982, 'Autre_Environement', 112, -1, 336, -1, 4.550269295577891e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 336, -1, 1.732831879053265e-05), (987515173, 1982, 'Autre_Environement', 176, -1, 336, -1, 4.928972339257598e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 336, -1, 0.00012161014456069097), (987515173, 1982, 'Autre_Environement', 240, -1, 336, -1, 0.00019641712424345315), (987515173, 1982, 'Autre_Environement', 272, -1, 336, -1, 0.00018776308570522815), (987515173, 1982, 'Autre_Environement', 304, -1, 336, -1, 0.00012362039706204087), (987515173, 1982, 'Autre_Environement', 336, -1, 336, -1, 0.00027186813531443477), (987515173, 1982, 'Carton', 112, -1, 112, -1, 1.582603914584979e-07), (987515173, 1982, 'Carton', 144, -1, 112, -1, 4.027391696581617e-06), (987515173, 1982, 'Carton', 176, -1, 112, -1, 7.02327088220045e-06), (987515173, 1982, 'Carton', 208, -1, 112, -1, 0.0008746891980990767), (987515173, 1982, 'Carton', 240, -1, 112, -1, 0.0026437495835125446), (987515173, 1982, 'Carton', 272, -1, 112, -1, 0.003369416343048215), (987515173, 1982, 'Carton', 304, -1, 112, -1, 0.03131555765867233), (987515173, 1982, 'Carton', 336, -1, 112, -1, 0.055960703641176224), (987515173, 1982, 'Carton', 112, -1, 144, -1, 0.00012460025027394295), (987515173, 1982, 'Carton', 144, -1, 144, -1, 0.0002090697962557897), (987515173, 1982, 'Carton', 176, -1, 144, -1, 0.00036751257721334696), (987515173, 1982, 'Carton', 208, -1, 144, -1, 0.006843219511210918), (987515173, 1982, 'Carton', 240, -1, 144, -1, 0.015893692150712013), (987515173, 1982, 'Carton', 272, -1, 144, -1, 0.00940609723329544), (987515173, 1982, 'Carton', 304, -1, 144, -1, 0.009789012372493744), (987515173, 1982, 'Carton', 336, -1, 144, -1, 0.022109536454081535), (987515173, 1982, 'Carton', 112, -1, 176, -1, 0.021920738741755486), (987515173, 1982, 'Carton', 144, -1, 176, -1, 0.19334731996059418), (987515173, 1982, 'Carton', 176, -1, 176, -1, 0.09639905393123627), (987515173, 1982, 'Carton', 208, -1, 176, -1, 0.12392431497573853), (987515173, 1982, 'Carton', 240, -1, 176, -1, 0.5330705642700195), (987515173, 1982, 'Carton', 272, -1, 176, -1, 0.4613811671733856), (987515173, 1982, 'Carton', 304, -1, 176, -1, 0.7694488167762756), (987515173, 1982, 'Carton', 336, -1, 176, -1, 0.8661088347434998), (987515173, 1982, 'Carton', 112, -1, 208, -1, 0.8503118753433228), (987515173, 1982, 'Carton', 144, -1, 208, -1, 0.9843242168426514), (987515173, 1982, 'Carton', 176, -1, 208, -1, 0.984762966632843), (987515173, 1982, 'Carton', 208, -1, 208, -1, 0.9919539093971252), (987515173, 1982, 'Carton', 240, -1, 208, -1, 0.9993768334388733), (987515173, 1982, 'Carton', 272, -1, 208, -1, 0.9994131326675415), (987515173, 1982, 'Carton', 304, -1, 208, -1, 0.9995883107185364), (987515173, 1982, 'Carton', 336, -1, 208, -1, 0.9992270469665527), (987515173, 1982, 'Carton', 112, -1, 240, -1, 0.9275615811347961), (987515173, 1982, 'Carton', 144, -1, 240, -1, 0.9809370636940002), (987515173, 1982, 'Carton', 176, -1, 240, -1, 0.9662413597106934), (987515173, 1982, 'Carton', 208, -1, 240, -1, 0.967867374420166), (987515173, 1982, 'Carton', 240, -1, 240, -1, 0.9963777661323547), (987515173, 1982, 'Carton', 272, -1, 240, -1, 0.9994211196899414), (987515173, 1982, 'Carton', 304, -1, 240, -1, 0.9997864365577698), (987515173, 1982, 'Carton', 336, -1, 240, -1, 0.9996694326400757), (987515173, 1982, 'Carton', 112, -1, 272, -1, 0.9895153045654297), (987515173, 1982, 'Carton', 144, -1, 272, -1, 0.9954569339752197), (987515173, 1982, 'Carton', 176, -1, 272, -1, 0.9855263233184814), (987515173, 1982, 'Carton', 208, -1, 272, -1, 0.9732471704483032), (987515173, 1982, 'Carton', 240, -1, 272, -1, 0.9974820017814636), (987515173, 1982, 'Carton', 272, -1, 272, -1, 0.9992026686668396), (987515173, 1982, 'Carton', 304, -1, 272, -1, 0.9995168447494507), (987515173, 1982, 'Carton', 336, -1, 272, -1, 0.9991267323493958), (987515173, 1982, 'Carton', 112, -1, 304, -1, 0.9977771639823914), (987515173, 1982, 'Carton', 144, -1, 304, -1, 0.9977606534957886), (987515173, 1982, 'Carton', 176, -1, 304, -1, 0.995557963848114), (987515173, 1982, 'Carton', 208, -1, 304, -1, 0.9927346706390381), (987515173, 1982, 'Carton', 240, -1, 304, -1, 0.9920164346694946), (987515173, 1982, 'Carton', 272, -1, 304, -1, 0.9835741519927979), (987515173, 1982, 'Carton', 304, -1, 304, -1, 0.9820358157157898), (987515173, 1982, 'Carton', 336, -1, 304, -1, 0.9809504747390747), (987515173, 1982, 'Carton', 112, -1, 336, -1, 0.9924246072769165), (987515173, 1982, 'Carton', 144, -1, 336, -1, 0.9762135744094849), (987515173, 1982, 'Carton', 176, -1, 336, -1, 0.9911807179450989), (987515173, 1982, 'Carton', 208, -1, 336, -1, 0.9869133830070496), (987515173, 1982, 'Carton', 240, -1, 336, -1, 0.9084780216217041), (987515173, 1982, 'Carton', 272, -1, 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1982, 'Teint_Dans_La_Masse', 272, -1, 208, -1, 1.1672231266857125e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 304, -1, 208, -1, 1.3333919014257845e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 336, -1, 208, -1, 5.950387640041299e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 112, -1, 240, -1, 4.2273386497981846e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 144, -1, 240, -1, 5.331692591425963e-06), (987515173, 1982, 'Teint_Dans_La_Masse', 176, -1, 240, -1, 3.893332177540287e-06), (987515173, 1982, 'Teint_Dans_La_Masse', 208, -1, 240, -1, 2.4045189093158115e-06), (987515173, 1982, 'Teint_Dans_La_Masse', 240, -1, 240, -1, 5.787132522527827e-06), (987515173, 1982, 'Teint_Dans_La_Masse', 272, -1, 240, -1, 2.1092033421155065e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 304, -1, 240, -1, 1.7756960005499423e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 336, -1, 240, -1, 2.2641110263066366e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 112, -1, 272, -1, 0.00020111992489546537), (987515173, 1982, 'Teint_Dans_La_Masse', 144, -1, 272, -1, 6.70585868647322e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 176, -1, 272, -1, 4.357044235803187e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 208, -1, 272, -1, 1.4579358321498148e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 240, -1, 272, -1, 6.996545835136203e-06), (987515173, 1982, 'Teint_Dans_La_Masse', 272, -1, 272, -1, 1.5510475350311026e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 304, -1, 272, -1, 1.540019002277404e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 336, -1, 272, -1, 0.00010458052565809339), (987515173, 1982, 'Teint_Dans_La_Masse', 112, -1, 304, -1, 9.489571675658226e-05), (987515173, 1982, 'Teint_Dans_La_Masse', 144, -1, 304, -1, 0.00010996792116202414), (987515173, 1982, 'Teint_Dans_La_Masse', 176, -1, 304, -1, 0.00015802575217094272), (987515173, 1982, 'Teint_Dans_La_Masse', 208, -1, 304, -1, 0.0005412314203567803), (987515173, 1982, 'Teint_Dans_La_Masse', 240, -1, 304, -1, 0.0023522961419075727), (987515173, 1982, 'Teint_Dans_La_Masse', 272, -1, 304, -1, 0.007445927243679762), (987515173, 1982, 'Teint_Dans_La_Masse', 304, -1, 304, -1, 0.005831396207213402), (987515173, 1982, 'Teint_Dans_La_Masse', 336, -1, 304, -1, 0.004440108314156532), (987515173, 1982, 'Teint_Dans_La_Masse', 112, -1, 336, -1, 0.0002414347109152004), (987515173, 1982, 'Teint_Dans_La_Masse', 144, -1, 336, -1, 0.0020012822933495045), (987515173, 1982, 'Teint_Dans_La_Masse', 176, -1, 336, -1, 0.000749177997931838), (987515173, 1982, 'Teint_Dans_La_Masse', 208, -1, 336, -1, 0.003359065391123295), (987515173, 1982, 'Teint_Dans_La_Masse', 240, -1, 336, -1, 0.0642060935497284), (987515173, 1982, 'Teint_Dans_La_Masse', 272, -1, 336, -1, 0.038067325949668884), (987515173, 1982, 'Teint_Dans_La_Masse', 304, -1, 336, -1, 0.03904539719223976), (987515173, 1982, 'Teint_Dans_La_Masse', 336, -1, 336, -1, 0.005887859966605902), (987515173, 1982, 'autre_refus', 112, -1, 112, -1, 5.810153469454349e-10), (987515173, 1982, 'autre_refus', 144, -1, 112, -1, 2.0581065740543636e-08), (987515173, 1982, 'autre_refus', 176, -1, 112, -1, 1.4502712701869314e-06), (987515173, 1982, 'autre_refus', 208, -1, 112, -1, 9.249220602214336e-05), (987515173, 1982, 'autre_refus', 240, -1, 112, -1, 0.0002172563545173034), (987515173, 1982, 'autre_refus', 272, -1, 112, -1, 0.0017511143814772367), (987515173, 1982, 'autre_refus', 304, -1, 112, -1, 0.017707305029034615), (987515173, 1982, 'autre_refus', 336, -1, 112, -1, 0.009030723944306374), (987515173, 1982, 'autre_refus', 112, -1, 144, -1, 9.226613997270761e-07), (987515173, 1982, 'autre_refus', 144, -1, 144, -1, 2.9219409043435007e-06), (987515173, 1982, 'autre_refus', 176, -1, 144, -1, 1.030898329190677e-05), (987515173, 1982, 'autre_refus', 208, -1, 144, -1, 0.00013510091230273247), (987515173, 1982, 'autre_refus', 240, -1, 144, -1, 0.000347205379512161), (987515173, 1982, 'autre_refus', 272, -1, 144, -1, 0.004934782162308693), (987515173, 1982, 'autre_refus', 304, -1, 144, -1, 0.04355596750974655), (987515173, 1982, 'autre_refus', 336, -1, 144, -1, 0.0952615812420845), (987515173, 1982, 'autre_refus', 112, -1, 176, -1, 1.5165657714533154e-05), (987515173, 1982, 'autre_refus', 144, -1, 176, -1, 0.00012733052426483482), (987515173, 1982, 'autre_refus', 176, -1, 176, -1, 0.00023670622613281012), (987515173, 1982, 'autre_refus', 208, -1, 176, -1, 0.0008107503526844084), (987515173, 1982, 'autre_refus', 240, -1, 176, -1, 0.0006537463632412255), (987515173, 1982, 'autre_refus', 272, -1, 176, -1, 0.0043275011703372), (987515173, 1982, 'autre_refus', 304, -1, 176, -1, 0.023466000333428383), (987515173, 1982, 'autre_refus', 336, -1, 176, -1, 0.01872607134282589), (987515173, 1982, 'autre_refus', 112, -1, 208, -1, 8.864520350471139e-05), (987515173, 1982, 'autre_refus', 144, -1, 208, -1, 0.00018535240087658167), (987515173, 1982, 'autre_refus', 176, -1, 208, -1, 0.00031954763107933104), (987515173, 1982, 'autre_refus', 208, -1, 208, -1, 0.00035753834526985884), (987515173, 1982, 'autre_refus', 240, -1, 208, -1, 0.00019910263654310256), (987515173, 1982, 'autre_refus', 272, -1, 208, -1, 0.0002863719710148871), (987515173, 1982, 'autre_refus', 304, -1, 208, -1, 0.0002023904671659693), (987515173, 1982, 'autre_refus', 336, -1, 208, -1, 0.00024400379334110767), (987515173, 1982, 'autre_refus', 112, -1, 240, -1, 0.00023376427998300642), (987515173, 1982, 'autre_refus', 144, -1, 240, -1, 0.00010842191841220483), (987515173, 1982, 'autre_refus', 176, -1, 240, -1, 6.486956408480182e-05), (987515173, 1982, 'autre_refus', 208, -1, 240, -1, 2.527677861507982e-05), (987515173, 1982, 'autre_refus', 240, -1, 240, -1, 7.288924098247662e-05), (987515173, 1982, 'autre_refus', 272, -1, 240, -1, 0.00014016672503203154), (987515173, 1982, 'autre_refus', 304, -1, 240, -1, 8.928764145821333e-05), (987515173, 1982, 'autre_refus', 336, -1, 240, -1, 8.166480984073132e-05), (987515173, 1982, 'autre_refus', 112, -1, 272, -1, 0.00026833912124857306), (987515173, 1982, 'autre_refus', 144, -1, 272, -1, 0.00011157286644447595), (987515173, 1982, 'autre_refus', 176, -1, 272, -1, 0.0001247433974640444), (987515173, 1982, 'autre_refus', 208, -1, 272, -1, 5.1280938350828364e-05), (987515173, 1982, 'autre_refus', 240, -1, 272, -1, 2.91460473818006e-05), (987515173, 1982, 'autre_refus', 272, -1, 272, -1, 4.2738149204524234e-05), (987515173, 1982, 'autre_refus', 304, -1, 272, -1, 6.833241786807775e-05), (987515173, 1982, 'autre_refus', 336, -1, 272, -1, 0.00014253244444262236), (987515173, 1982, 'autre_refus', 112, -1, 304, -1, 0.0001154204219346866), (987515173, 1982, 'autre_refus', 144, -1, 304, -1, 0.000217215929296799), (987515173, 1982, 'autre_refus', 176, -1, 304, -1, 0.00042622891487553716), (987515173, 1982, 'autre_refus', 208, -1, 304, -1, 0.00042710095294751227), (987515173, 1982, 'autre_refus', 240, -1, 304, -1, 6.579277396667749e-05), (987515173, 1982, 'autre_refus', 272, -1, 304, -1, 3.164090230711736e-05), (987515173, 1982, 'autre_refus', 304, -1, 304, -1, 1.1666674254229292e-05), (987515173, 1982, 'autre_refus', 336, -1, 304, -1, 1.8799521058099344e-05), (987515173, 1982, 'autre_refus', 112, -1, 336, -1, 0.0002476412628311664), (987515173, 1982, 'autre_refus', 144, -1, 336, -1, 0.000469834019895643), (987515173, 1982, 'autre_refus', 176, -1, 336, -1, 0.00033466910826973617), (987515173, 1982, 'autre_refus', 208, -1, 336, -1, 0.0002366691769566387), (987515173, 1982, 'autre_refus', 240, -1, 336, -1, 0.00010651562479324639), (987515173, 1982, 'autre_refus', 272, -1, 336, -1, 9.579770994605497e-05), (987515173, 1982, 'autre_refus', 304, -1, 336, -1, 0.00013094412861391902), (987515173, 1982, 'autre_refus', 336, -1, 336, -1, 0.0007309786160476506)]} ############################### TEST certificat_qualite_papier ################################ TEST certificat qualite papier Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1848 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1848 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1848 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1848 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Step 4442 tile have less inputs used (1) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 4441 detect_points is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 4443 count_percent_refus is not consistent : 4 used against 3 in the step definition ! Step 4444 send_mail_dechet have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : output 1 of step 4440 have datatype=1 whereas input 0 of step 4443 have datatype=2 WARNING : type of output 1 of step 4441 doesn't seem to be define in the database( WARNING : type of input 4 of step 4443 doesn't seem to be define in the database( DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : init_dechet, tile, detect_points, count_percent_refus, brightness, blur_detection, send_mail_dechet list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (1902940) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (1902940) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 987321136, 'portfolio_id': 1902940}] map_portfolio_id_photo_id: {1902940: [987321136]} ##### Call download_photos : nb_thread : 5 begin to download photo : 987321136 download finish for photo 987321136 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.12129092216491699 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 7 step1:init_dechet Thu Sep 25 17:05:02 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} debut step init detect dechets input : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg ON MODIFIE NB AVEC LE INPUT map photo id path extension : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg scale : 0.9481481481481482 FIN step init dechet After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True saveOutput not yet implemented for datou_step.type : init_dechet we use saveGeneral [987321136] map_info['map_portfolio_photo'] : {1902940: [987321136]} final : False mtd_id 1848 list_pids : [987321136] Looping around the photos to save general results len do output : 1 /987321136Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('1848', '1902940', '987321136', 'None', None, None, None, None, None)] time used for this insertion : 0.015002727508544922 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.0001690387725830078 time spend to save output : 0.015242815017700195 total time spend for step 1 : 0.015411853790283203 step2:tile Thu Sep 25 17:05:02 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'987321136': ()} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg',) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {0: 987321136} verbose : True param_json : {'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'tile_correct_upm', 'ETA': 86400, 'new_width': 1500, 'new_height': 20000, 'host': 'www.fotonower.com', 'protocol': 'https', 'photo_tile_type': 1522, 'option_bande': 'True'} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {406: 410} map_filenames : {987321136: 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 1 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 987321136,987321136,987321136) and `type` in (406) Loaded 0 chid ids of type : 0 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in () created feed_id_new_photos : 27233641 with name tile_correct_upm feed_id_new_photos : 27233641 filename : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg photo_id : 987321136 height_image_input : 439 width_image_input : 562 new_width : 1500 new_height : 20000 stride : 0 stride_relative : 0.1 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 0 list_bib_to_crops : 1 [(0, 562, 0, 439, 0)] calcul des nouveaux crops pour le tile x0:0,x1:562,y0:0,y1:439 chi selectionnes : [] new_crops_tiles : 1 crop_transformed : 0 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) [(987321136, 2090988864, 1522, 0, 562, 0, 439, 1.0)] list_photo_ids_cropped : [987321136] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 987321136) and `type` in (1522) Loaded 1 chid ids of type : 1522 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1608847328) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1608847328) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1608847328) treat the image : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg , 0 before upload mediasElapsed time : 0.013652324676513672 About to upload 1 photos upload in portfolio : 27233641 Result OK ! uploaded one batch 0 Elapsed time : 6.324514865875244 upload mediasElapsed time : 6.338228464126587 , 0insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [(1608847328, 1386159647, 0)] Saving 0 CHIs. list_chi_tile : [] end of tileElapsed time : 6.354310512542725 map_pid_results : {'1386159647': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg']} After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True saveOutput not yet implemented for datou_step.type : tile we use saveGeneral [987321136, 987321136, '1386159647'] map_info['map_portfolio_photo'] : {1902940: [987321136]} final : False mtd_id 1848 list_pids : [987321136, 987321136, '1386159647'] Looping around the photos to save general results len do output : 1 /1386159647Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) ('1848', None, None, None, None, None, None, None, None) ('1848', None, '1386159647', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('1848', None, '1386159647', 'None', None, None, None, None, None), ('1848', '1902940', '987321136', None, None, None, None, None, None)] time used for this insertion : 0.011804580688476562 save_final save missing photos in datou_result : time spend for datou_step_exec : 14.426095962524414 time spend to save output : 0.011931180953979492 total time spend for step 2 : 14.438027143478394 step3:detect_points Thu Sep 25 17:05:16 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'1386159647': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg']} input_args_next_step : {'1386159647': ()} output_args : {'1386159647': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg']} args : 1386159647 depend.output_id : 0 complete output_args for input 1 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'1386159647': ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg',), '987321136': ()} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 2 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg',) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136, 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg': 1386159647} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}, 1386159647: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg'}} map_subphoto_mainphoto : {0: 987321136, 1386159647: 987321136} Beginning of datou step predict points ! Inside try reload ! classes : ['Autre_Environement', 'Carton', 'Kraft', 'Lointain_Papier_Magazine', 'Metal', 'Papier_Magazine', 'Plastique', 'Sol_Environement', 'Teint_Dans_La_Masse', 'autre_refus'] pht : 1927 model_name : learn_refus_upm_blanches_1924 {'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'} gpu_mode in detect_points : False To load net FromThcl() model_param file didn't exist model_name : learn_refus_upm_blanches_1924 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_refus_upm_blanches_1924 /data/models_weight/learn_refus_upm_blanches_1924/caffemodel size_local : 45774543 size in s3 : 45774543 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 caffemodel already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt size_local : 17312 size in s3 : 17312 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:03 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:05 mean.npy already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/synset_words.txt size_local : 218 size in s3 : 218 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 synset_words.txt already exist and didn't need to update reshape net's input to : (224, 224) origin shape : (10, 3, 224, 224) after reshape : (1, 3, 224, 224) [('data', (1, 3, 224, 224)), ('conv1', (1, 64, 112, 112)), ('pool1', (1, 64, 56, 56)), ('pool1_pool1_0_split_0', (1, 64, 56, 56)), ('pool1_pool1_0_split_1', (1, 64, 56, 56)), ('res2a_branch1', (1, 64, 56, 56)), ('res2a_branch2a', (1, 64, 56, 56)), ('res2a_branch2b', (1, 64, 56, 56)), ('res2a', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_0', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_1', (1, 64, 56, 56)), ('res2b_branch2a', (1, 64, 56, 56)), ('res2b_branch2b', (1, 64, 56, 56)), ('res2b', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_0', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_1', (1, 64, 56, 56)), ('res3a_branch1', (1, 128, 28, 28)), ('res3a_branch2a', (1, 128, 28, 28)), ('res3a_branch2b', (1, 128, 28, 28)), ('res3a', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_0', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_1', (1, 128, 28, 28)), ('res3b_branch2a', (1, 128, 28, 28)), ('res3b_branch2b', (1, 128, 28, 28)), ('res3b', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_0', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_1', (1, 128, 28, 28)), ('res4a_branch1', (1, 256, 14, 14)), ('res4a_branch2a', (1, 256, 14, 14)), ('res4a_branch2b', (1, 256, 14, 14)), ('res4a', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_0', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_1', (1, 256, 14, 14)), ('res4b_branch2a', (1, 256, 14, 14)), ('res4b_branch2b', (1, 256, 14, 14)), ('res4b', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_0', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_1', (1, 256, 14, 14)), ('res5a_branch1', (1, 512, 7, 7)), ('res5a_branch2a', (1, 512, 7, 7)), ('res5a_branch2b', (1, 512, 7, 7)), ('res5a', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_0', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_1', (1, 512, 7, 7)), ('res5b_branch2a', (1, 512, 7, 7)), ('res5b_branch2b', (1, 512, 7, 7)), ('res5b', (1, 512, 7, 7)), ('fc2019-10-22_15-02-46', (1, 10, 1, 1)), ('prob', (1, 10, 1, 1))] set image transformer : About to compute detect the points : len(args) : 2 Inside predict_points step exec : nb paths : 1 treate image : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg size of numpy array img : 2960752 scale method : caffe/skimage size of numpy array img_scale : 2655880 (416, 532, 3) nb_h 7 nb_w 11 size of sub images : (224, 224, 3) size of caffe_input : 46362776 (77, 3, 224, 224) time to do the preprocess : 0.03856396675109863 time to do a prediction : 14.275405645370483 dict_keys(['prob']) shape of output (77, 10, 1, 1) shape of the out_put heatmap (10, 7, 11) number of sub_photos vertical and horizon 7 11 size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) size of heatmap : (7,11) After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True Inside savePoints : final : False verbose : True threshold to save the result : 0.05 maximun points to save in the table mtr_datou_result for each class : 100 output flattener 5 example : {1386159647: [(1386159647, 1945, 'Autre_Environement', 185, -1, 118, -1, 1.8337410438107327e-05), (1386159647, 1945, 'Autre_Environement', 320, -1, 118, -1, 0.0001291327498620376), (1386159647, 1945, 'Autre_Environement', 388, -1, 151, -1, 1.3445685908664018e-05), (1386159647, 1945, 'Autre_Environement', 286, -1, 185, -1, 0.00013466527161654085), (1386159647, 1945, 'Autre_Environement', 118, -1, 219, -1, 9.86390750767896e-06), (1386159647, 1945, 'Autre_Environement', 219, -1, 219, -1, 0.00038494516047649086), (1386159647, 1945, 'Autre_Environement', 354, -1, 219, -1, 0.0003431888180784881), (1386159647, 1945, 'Autre_Environement', 421, -1, 253, -1, 1.494663450785083e-07), (1386159647, 1945, 'Autre_Environement', 185, -1, 286, -1, 1.814520658172114e-07), (1386159647, 1945, 'Autre_Environement', 320, -1, 286, -1, 4.115241154067917e-06), (1386159647, 1945, 'Autre_Environement', 118, -1, 320, -1, 2.5274063397695556e-10), (1386159647, 1945, 'Autre_Environement', 253, -1, 320, -1, 1.0447603199237321e-10), (1386159647, 1945, 'Autre_Environement', 388, -1, 320, -1, 4.5192118136583304e-07), (1386159647, 1945, 'Carton', 151, -1, 118, -1, 0.9897055625915527), (1386159647, 1945, 'Carton', 286, -1, 118, -1, 0.8210961222648621), (1386159647, 1945, 'Carton', 421, -1, 118, -1, 0.4851985573768616), (1386159647, 1945, 'Carton', 219, -1, 151, -1, 0.9841372966766357), (1386159647, 1945, 'Carton', 118, -1, 185, -1, 0.9978604912757874), (1386159647, 1945, 'Carton', 185, -1, 219, -1, 0.7996194958686829), (1386159647, 1945, 'Carton', 354, -1, 219, -1, 0.13047637045383453), (1386159647, 1945, 'Carton', 286, -1, 253, -1, 0.05070793256163597), (1386159647, 1945, 'Carton', 118, -1, 286, -1, 0.31989040970802307), (1386159647, 1945, 'Carton', 219, -1, 286, -1, 0.0034983144141733646), (1386159647, 1945, 'Carton', 421, -1, 286, -1, 0.01660206913948059), (1386159647, 1945, 'Carton', 354, -1, 320, -1, 0.0016258988762274384), (1386159647, 1945, 'Kraft', 185, -1, 118, -1, 0.004793279338628054), (1386159647, 1945, 'Kraft', 286, -1, 118, -1, 0.0023909551091492176), (1386159647, 1945, 'Kraft', 421, -1, 118, -1, 0.002102428814396262), (1386159647, 1945, 'Kraft', 354, -1, 151, -1, 0.05212335288524628), (1386159647, 1945, 'Kraft', 118, -1, 185, -1, 0.0017166697653010488), (1386159647, 1945, 'Kraft', 253, -1, 185, -1, 0.04599893465638161), (1386159647, 1945, 'Kraft', 185, -1, 219, -1, 0.021099306643009186), (1386159647, 1945, 'Kraft', 388, -1, 219, -1, 6.061792737455107e-05), (1386159647, 1945, 'Kraft', 286, -1, 253, -1, 0.0037522290367633104), (1386159647, 1945, 'Kraft', 118, -1, 286, -1, 0.010319208726286888), (1386159647, 1945, 'Kraft', 219, -1, 286, -1, 5.351284926291555e-05), (1386159647, 1945, 'Kraft', 421, -1, 286, -1, 9.467339623370208e-06), (1386159647, 1945, 'Kraft', 320, -1, 320, -1, 0.00017124204896390438), (1386159647, 1945, 'Lointain_Papier_Magazine', 185, -1, 118, -1, 2.352082447032444e-06), (1386159647, 1945, 'Lointain_Papier_Magazine', 320, -1, 118, -1, 1.991412864299491e-05), (1386159647, 1945, 'Lointain_Papier_Magazine', 253, -1, 151, -1, 1.1851832823595032e-05), (1386159647, 1945, 'Lointain_Papier_Magazine', 354, -1, 185, -1, 8.877575601218268e-05), (1386159647, 1945, 'Lointain_Papier_Magazine', 118, -1, 219, -1, 2.1015976017224602e-06), (1386159647, 1945, 'Lointain_Papier_Magazine', 219, -1, 219, -1, 7.86672972026281e-05), (1386159647, 1945, 'Lointain_Papier_Magazine', 421, -1, 219, -1, 5.019426794206083e-07), (1386159647, 1945, 'Lointain_Papier_Magazine', 320, -1, 253, -1, 8.220934978453442e-05), (1386159647, 1945, 'Lointain_Papier_Magazine', 185, -1, 286, -1, 3.6812457437918056e-07), (1386159647, 1945, 'Lointain_Papier_Magazine', 388, -1, 286, -1, 3.3782250739022857e-06), (1386159647, 1945, 'Lointain_Papier_Magazine', 118, -1, 320, -1, 3.5824958555252806e-09), (1386159647, 1945, 'Lointain_Papier_Magazine', 286, -1, 320, -1, 1.2866975396264024e-07), (1386159647, 1945, 'Metal', 185, -1, 118, -1, 7.473808364011347e-05), (1386159647, 1945, 'Metal', 286, -1, 118, -1, 3.432366065680981e-05), (1386159647, 1945, 'Metal', 118, -1, 151, -1, 1.1519473446242046e-06), (1386159647, 1945, 'Metal', 354, -1, 151, -1, 0.001217490527778864), (1386159647, 1945, 'Metal', 253, -1, 185, -1, 0.001836584648117423), (1386159647, 1945, 'Metal', 421, -1, 185, -1, 3.084278432652354e-05), (1386159647, 1945, 'Metal', 185, -1, 219, -1, 0.0011127882171422243), (1386159647, 1945, 'Metal', 118, -1, 253, -1, 2.7215228328714147e-05), (1386159647, 1945, 'Metal', 354, -1, 253, -1, 0.0005037166411057115), (1386159647, 1945, 'Metal', 219, -1, 286, -1, 1.657771281315945e-05), (1386159647, 1945, 'Metal', 421, -1, 286, -1, 2.2439740860136226e-05), (1386159647, 1945, 'Metal', 151, -1, 320, -1, 1.393576087860282e-10), (1386159647, 1945, 'Metal', 320, -1, 320, -1, 3.1560623028781265e-05), (1386159647, 1945, 'Papier_Magazine', 118, -1, 118, -1, 0.001665871823206544), (1386159647, 1945, 'Papier_Magazine', 253, -1, 118, -1, 0.28050497174263), (1386159647, 1945, 'Papier_Magazine', 185, -1, 151, -1, 0.003942570183426142), (1386159647, 1945, 'Papier_Magazine', 421, -1, 151, -1, 0.9828073978424072), (1386159647, 1945, 'Papier_Magazine', 354, -1, 185, -1, 0.7690255045890808), (1386159647, 1945, 'Papier_Magazine', 286, -1, 219, -1, 0.9288092851638794), (1386159647, 1945, 'Papier_Magazine', 118, -1, 253, -1, 0.04313919320702553), (1386159647, 1945, 'Papier_Magazine', 219, -1, 253, -1, 0.8978631496429443), (1386159647, 1945, 'Papier_Magazine', 388, -1, 253, -1, 0.9886879324913025), (1386159647, 1945, 'Papier_Magazine', 151, -1, 320, -1, 0.9999996423721313), (1386159647, 1945, 'Papier_Magazine', 253, -1, 320, -1, 0.9999960660934448), (1386159647, 1945, 'Papier_Magazine', 354, -1, 320, -1, 0.9942159056663513), (1386159647, 1945, 'Plastique', 118, -1, 118, -1, 1.236031312146224e-05), (1386159647, 1945, 'Plastique', 219, -1, 118, -1, 0.00030184732167981565), (1386159647, 1945, 'Plastique', 320, -1, 118, -1, 0.0002493929350748658), (1386159647, 1945, 'Plastique', 253, -1, 185, -1, 0.007031592074781656), (1386159647, 1945, 'Plastique', 354, -1, 185, -1, 0.032503753900527954), (1386159647, 1945, 'Plastique', 185, -1, 219, -1, 0.050375860184431076), (1386159647, 1945, 'Plastique', 421, -1, 219, -1, 0.00012226666149217635), (1386159647, 1945, 'Plastique', 118, -1, 253, -1, 0.003930176142603159), (1386159647, 1945, 'Plastique', 286, -1, 253, -1, 0.0025490771513432264), (1386159647, 1945, 'Plastique', 219, -1, 286, -1, 6.120907346485183e-05), (1386159647, 1945, 'Plastique', 354, -1, 286, -1, 0.00538312504068017), (1386159647, 1945, 'Plastique', 151, -1, 320, -1, 1.8926894773674263e-10), (1386159647, 1945, 'Plastique', 421, -1, 320, -1, 0.00020204381144139916), (1386159647, 1945, 'Sol_Environement', 185, -1, 118, -1, 9.372543900099117e-06), (1386159647, 1945, 'Sol_Environement', 320, -1, 118, -1, 2.7338848667568527e-05), (1386159647, 1945, 'Sol_Environement', 118, -1, 151, -1, 2.5881729470711434e-07), (1386159647, 1945, 'Sol_Environement', 253, -1, 185, -1, 0.00011454988998593763), (1386159647, 1945, 'Sol_Environement', 354, -1, 185, -1, 0.00020838991622440517), (1386159647, 1945, 'Sol_Environement', 185, -1, 219, -1, 9.349620813736692e-05), (1386159647, 1945, 'Sol_Environement', 421, -1, 219, -1, 1.1348908657282664e-07), (1386159647, 1945, 'Sol_Environement', 118, -1, 253, -1, 7.004572921687213e-07), (1386159647, 1945, 'Sol_Environement', 320, -1, 253, -1, 5.724640504922718e-05), (1386159647, 1945, 'Sol_Environement', 219, -1, 286, -1, 3.869550369017816e-08), (1386159647, 1945, 'Sol_Environement', 388, -1, 286, -1, 6.792529802623903e-06), (1386159647, 1945, 'Sol_Environement', 151, -1, 320, -1, 2.6225014184994705e-14), (1386159647, 1945, 'Sol_Environement', 286, -1, 320, -1, 1.5886031690115487e-07), (1386159647, 1945, 'Teint_Dans_La_Masse', 185, -1, 118, -1, 0.002272234996780753), (1386159647, 1945, 'Teint_Dans_La_Masse', 286, -1, 118, -1, 0.001813237671740353), (1386159647, 1945, 'Teint_Dans_La_Masse', 388, -1, 118, -1, 0.04538803920149803), (1386159647, 1945, 'Teint_Dans_La_Masse', 118, -1, 151, -1, 0.00010940170614048839), (1386159647, 1945, 'Teint_Dans_La_Masse', 253, -1, 185, -1, 0.0056123328395187855), (1386159647, 1945, 'Teint_Dans_La_Masse', 354, -1, 185, -1, 0.15166763961315155), (1386159647, 1945, 'Teint_Dans_La_Masse', 185, -1, 219, -1, 0.0013750138459727168), (1386159647, 1945, 'Teint_Dans_La_Masse', 118, -1, 253, -1, 6.252125604078174e-05), (1386159647, 1945, 'Teint_Dans_La_Masse', 286, -1, 253, -1, 0.0018639108166098595), (1386159647, 1945, 'Teint_Dans_La_Masse', 388, -1, 253, -1, 0.001438076258637011), (1386159647, 1945, 'Teint_Dans_La_Masse', 219, -1, 286, -1, 1.016586884361459e-05), (1386159647, 1945, 'Teint_Dans_La_Masse', 151, -1, 320, -1, 3.425693932967988e-07), (1386159647, 1945, 'Teint_Dans_La_Masse', 320, -1, 320, -1, 0.0020001486409455538), (1386159647, 1945, 'Teint_Dans_La_Masse', 421, -1, 320, -1, 8.311669807881117e-05), (1386159647, 1945, 'autre_refus', 185, -1, 118, -1, 0.028516046702861786), (1386159647, 1945, 'autre_refus', 354, -1, 118, -1, 0.0014720888575538993), (1386159647, 1945, 'autre_refus', 118, -1, 151, -1, 3.824138184427284e-05), (1386159647, 1945, 'autre_refus', 253, -1, 185, -1, 0.07516990602016449), (1386159647, 1945, 'autre_refus', 185, -1, 219, -1, 0.010234796442091465), (1386159647, 1945, 'autre_refus', 354, -1, 219, -1, 0.04460597038269043), (1386159647, 1945, 'autre_refus', 118, -1, 253, -1, 0.00015751634782645851), (1386159647, 1945, 'autre_refus', 286, -1, 253, -1, 0.01393966656178236), (1386159647, 1945, 'autre_refus', 219, -1, 286, -1, 4.3672833271557465e-05), (1386159647, 1945, 'autre_refus', 388, -1, 286, -1, 0.0030952864326536655), (1386159647, 1945, 'autre_refus', 151, -1, 320, -1, 1.5080686699420198e-10), (1386159647, 1945, 'autre_refus', 320, -1, 320, -1, 0.0030849112663418055)]} hashtag or score ? = 0.9897055625915527 hashtag or score ? = 0.8210961222648621 hashtag or score ? = 0.4851985573768616 hashtag or score ? = 0.9841372966766357 hashtag or score ? = 0.9978604912757874 hashtag or score ? = 0.7996194958686829 hashtag or score ? = 0.13047637045383453 hashtag or score ? = 0.05070793256163597 hashtag or score ? = 0.31989040970802307 hashtag or score ? = 0.05212335288524628 hashtag or score ? = 0.28050497174263 hashtag or score ? = 0.9828073978424072 hashtag or score ? = 0.7690255045890808 hashtag or score ? = 0.9288092851638794 hashtag or score ? = 0.8978631496429443 hashtag or score ? = 0.9886879324913025 hashtag or score ? = 0.9999996423721313 hashtag or score ? = 0.9999960660934448 hashtag or score ? = 0.9942159056663513 hashtag or score ? = 0.050375860184431076 hashtag or score ? = 0.15166763961315155 hashtag or score ? = 0.07516990602016449 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) [('1386159647', '492774966', '1945', '151', '-1', '118', '-1', '0.9897055625915527'), ('1386159647', '492774966', '1945', '286', '-1', '118', '-1', '0.8210961222648621'), ('1386159647', '492774966', '1945', '421', '-1', '118', '-1', '0.4851985573768616'), ('1386159647', '492774966', '1945', '219', '-1', '151', '-1', '0.9841372966766357'), ('1386159647', '492774966', '1945', '118', '-1', '185', '-1', '0.9978604912757874'), ('1386159647', '492774966', '1945', '185', '-1', '219', '-1', '0.7996194958686829'), ('1386159647', '492774966', '1945', '354', '-1', '219', '-1', '0.13047637045383453'), ('1386159647', '492774966', '1945', '286', '-1', '253', '-1', '0.05070793256163597'), ('1386159647', '492774966', '1945', '118', '-1', '286', '-1', '0.31989040970802307'), ('1386159647', '493202403', '1945', '354', '-1', '151', '-1', '0.05212335288524628'), ('1386159647', '2107752386', '1945', '253', '-1', '118', '-1', '0.28050497174263'), ('1386159647', '2107752386', '1945', '421', '-1', '151', '-1', '0.9828073978424072'), ('1386159647', '2107752386', '1945', '354', '-1', '185', '-1', '0.7690255045890808'), ('1386159647', '2107752386', '1945', '286', '-1', '219', '-1', '0.9288092851638794'), ('1386159647', '2107752386', '1945', '219', '-1', '253', '-1', '0.8978631496429443'), ('1386159647', '2107752386', '1945', '388', '-1', '253', '-1', '0.9886879324913025'), ('1386159647', '2107752386', '1945', '151', '-1', '320', '-1', '0.9999996423721313'), ('1386159647', '2107752386', '1945', '253', '-1', '320', '-1', '0.9999960660934448'), ('1386159647', '2107752386', '1945', '354', '-1', '320', '-1', '0.9942159056663513'), ('1386159647', '492725882', '1945', '185', '-1', '219', '-1', '0.050375860184431076'), ('1386159647', '2107752385', '1945', '354', '-1', '185', '-1', '0.15166763961315155'), ('1386159647', '2107752406', '1945', '253', '-1', '185', '-1', '0.07516990602016449')] final : False save missing photos in datou_result : time spend for datou_step_exec : 15.449866771697998 time spend to save output : 0.05748176574707031 total time spend for step 3 : 15.507348537445068 step4:count_percent_refus Thu Sep 25 17:05:32 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'987321136': ()} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 1 complete output_args for input 1 : {'1386159647': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg']} input_args_next_step : {'987321136': (987321136,), '1386159647': ()} output_args : {'1386159647': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg']} args : 1386159647 depend.output_id : 0 complete output_args for input 2 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'987321136': (987321136,), '1386159647': ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg',)} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 2 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : (987321136, 0.9481481481481482) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136, 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg': 1386159647} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}, 1386159647: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg'}} map_subphoto_mainphoto : {0: 987321136, 1386159647: 987321136} debut step count percent refus args : {'987321136': (987321136, 0.9481481481481482), '1386159647': ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg',)} (987321136, 0.9481481481481482) ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg',) on trouve le portfolio_id = 1902940 list_photo : [987321136] list_photo_correc : [1386159647] debut step count percent refus Treating photo_id : 987321136 Calcul du count_res count res : ((492774966, 3), (2107752386, 7)) Hashtag_id : 492774966 Hashtag_id : 2107752386 We have 2 classes in this image After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True map_info[mapportfolio_photo] : {1902940: [987321136]} dans le for photo id : 987321136 output[photo_id] : [({'carton': 3, 'Papier_Magazine': 7}, [1386159647], {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164}, 1902940)] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_surface',1902940,30.0,'refus_total',1945) on duplicate key update value= 30.0 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945]] insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_gravi',1902940,61.64383561643836,'refus_total',1945) on duplicate key update value= 61.64383561643836 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'refus_total', 1945]] insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_surface',1902940,30.0,'carton',1945) on duplicate key update value= 30.0 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'refus_total', 1945], ['0', 'qualipapia_surface', 1902940, 30.0, 'carton', 1945]] insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_gravi',1902940,61.64383561643836,'carton',1945) on duplicate key update value= 61.64383561643836 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'refus_total', 1945], ['0', 'qualipapia_surface', 1902940, 30.0, 'carton', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'carton', 1945]] insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_surface',1902940,70.0,'Papier_Magazine',1945) on duplicate key update value= 70.0 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'refus_total', 1945], ['0', 'qualipapia_surface', 1902940, 30.0, 'carton', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'carton', 1945], ['0', 'qualipapia_surface', 1902940, 70.0, 'Papier_Magazine', 1945]] insert into MTRLabel.upm_carac (ol,type_carac,portfolio_id,value,material,hashtag_type) values (0,'qualipapia_gravi',1902940,38.35616438356164,'Papier_Magazine',1945) on duplicate key update value= 38.35616438356164 list_values : [['0', 'qualipapia_surface', 1902940, 30.0, 'refus_total', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'refus_total', 1945], ['0', 'qualipapia_surface', 1902940, 30.0, 'carton', 1945], ['0', 'qualipapia_gravi', 1902940, 61.64383561643836, 'carton', 1945], ['0', 'qualipapia_surface', 1902940, 70.0, 'Papier_Magazine', 1945], ['0', 'qualipapia_gravi', 1902940, 38.35616438356164, 'Papier_Magazine', 1945]] time used for this insertion : 0.05274319648742676 save missing photos in datou_result : time spend for datou_step_exec : 0.017015695571899414 time spend to save output : 0.052996158599853516 total time spend for step 4 : 0.07001185417175293 step5:brightness Thu Sep 25 17:05:32 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'987321136': ()} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg',) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136, 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg': 1386159647} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}, 1386159647: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg'}} map_subphoto_mainphoto : {0: 987321136, 1386159647: 987321136} inside step calcul brightness treat image : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg pour la photo_id : -0.39870825574700136, le score de luminosite est de 987321136 brightness_score : {987321136: [(987321136, -0.39870825574700136, 496442774)]} After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True select photo_hashtag_type from MTRDatou.classification_theme where id = 1154 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 0.007959604263305664 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) first line : ('987321136', '496442774', '1426') ... last line : ('987321136', '496442774', '1426') time used for this insertion : 0.007945060729980469 save missing photos in datou_result : time spend for datou_step_exec : 0.05672597885131836 time spend to save output : 0.02029871940612793 total time spend for step 5 : 0.07702469825744629 step6:blur_detection Thu Sep 25 17:05:32 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} input_args_next_step : {'987321136': ()} output_args : {'987321136': ['temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 987321136, 0.9481481481481482]} args : 987321136 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ('temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg',) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136, 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg': 1386159647} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}, 1386159647: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg'}} map_subphoto_mainphoto : {0: 987321136, 1386159647: 987321136} inside step blur_detection score_blur_detection : {} methode: ratio et variance treat image : temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg resize: (439, 562) 987321136 -5.392404060312662 score_blur_detection : {987321136: [(987321136, -5.392404060312662, 492609224)]} After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : False verbose : True select photo_hashtag_type from MTRDatou.classification_theme where id = 1055 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1 insert into MTRPhoto.class_photo_score (thcl, photo_id, hashtag_id, score) values (%s,%s,%s,%s) on duplicate key update score = values(score) time used for this insertion : 0.008137226104736328 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) first line : ('987321136', '492609224', '1294') ... last line : ('987321136', '492609224', '1294') time used for this insertion : 0.007658481597900391 save missing photos in datou_result : time spend for datou_step_exec : 0.0923318862915039 time spend to save output : 0.0205535888671875 total time spend for step 6 : 0.1128854751586914 step7:send_mail_dechet Thu Sep 25 17:05:32 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {987321136: [(987321136, -5.392404060312662, 492609224)]} input_args_next_step : {987321136: ()} output_args : {987321136: [(987321136, -5.392404060312662, 492609224)]} args : 987321136 depend.output_id : 0 complete output_args for input 1 : {987321136: [(987321136, -0.39870825574700136, 496442774)]} input_args_next_step : {987321136: ((987321136, -5.392404060312662, 492609224),)} output_args : {987321136: [(987321136, -0.39870825574700136, 496442774)]} args : 987321136 depend.output_id : 0 complete output_args for input 2 : {987321136: [({'carton': 3, 'Papier_Magazine': 7}, [1386159647], {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164}, 1902940)]} input_args_next_step : {987321136: ((987321136, -5.392404060312662, 492609224), (987321136, -0.39870825574700136, 496442774))} output_args : {987321136: [({'carton': 3, 'Papier_Magazine': 7}, [1386159647], {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164}, 1902940)]} args : 987321136 depend.output_id : 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :1, first value : ((987321136, -5.392404060312662, 492609224), (987321136, -0.39870825574700136, 496442774), ({'carton': 3, 'Papier_Magazine': 7}, [1386159647], {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164}, 1902940)) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg': 987321136, 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg': 1386159647} map_photo_id_path_extension : {987321136: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea.jpg', 'extension': 'jpg'}, 1386159647: {'path': 'temp/1758812702_3157952_987321136_6a08497399a24a3041045c21475a90ea_0.jpg'}} map_subphoto_mainphoto : {0: 987321136, 1386159647: 987321136} dans la step send mail dechet list_name : ['one', 'sample', 'debug', 'board', 'détect', 'port'] corps du mail : La photo est trop sombre et nette, merci de reprendre la photo
Lien affichage photo


Dans ces conditions de prise de photo, les résultats sur le tas sont les suivants :
Le pourcentage de matière impropre est de 61.64 %.

Pour plus de détails:

Teint Dans La Masse: 0%.

carton: 61.64%.

metal: 0%.

plastique: 0%.

senders@fotonower.com retour de l'envoi du mail : None After datou_step_exec type output : map_portfolio_photo : len 1 keys : dict_keys([1902940]) Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : send_mail_dechet we use saveGeneral [987321136, 987321136, '1386159647'] map_info['map_portfolio_photo'] : {1902940: [987321136]} final : True mtd_id 1848 list_pids : [987321136, 987321136, '1386159647'] Looping around the photos to save general results len do output : 1 /987321136. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) ('1848', None, None, None, None, None, None, None, None) ('1848', None, '1386159647', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('1848', '1902940', '987321136', "{'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}", None, None, None, None, None), ('1848', None, '1386159647', None, None, None, None, None, None)] time used for this insertion : 0.012275218963623047 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.5994718074798584 time spend to save output : 0.012547016143798828 total time spend for step 7 : 0.6120188236236572 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 7 output : {987321136: (-110, -0.39870825574700136, -5.392404060312662, 30.0, 61.64383561643836, {'carton': 3, 'Papier_Magazine': 7}, {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164}, 0.6164383561643836)} ############################### TEST image_temperature_detection ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1807 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1807 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1807 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1807 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : image_temperature_detection list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (984484223) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 984484223 download finish for photo 984484223 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1493988037109375 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:image_temperature_detection Thu Sep 25 17:05:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812733_3157952_984484223_2e25dc219a9a57a9f85bcae482a80c35.jpg': 984484223} map_photo_id_path_extension : {984484223: {'path': 'temp/1758812733_3157952_984484223_2e25dc219a9a57a9f85bcae482a80c35.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} inside step blanche_jaune_detection treat image : temp/1758812733_3157952_984484223_2e25dc219a9a57a9f85bcae482a80c35.jpg 984484223 1.004309911525615 After datou_step_exec type output : time spend for datou_step_exec : 0.15230560302734375 time spend to save output : 5.745887756347656e-05 total time spend for step 1 : 0.15236306190490723 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {984484223: [(984484223, 1.004309911525615, 492630606)]} {984484223: [(984484223, 1.004309911525615, 492630606)]} ############################### TEST broca ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4041 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4041 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4041 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4041 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5205529) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5205529) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1064921404, 'portfolio_id': 5205529}, {'photo_id': 1064921402, 'portfolio_id': 5205529}, {'photo_id': 1064921401, 'portfolio_id': 5205529}, {'photo_id': 1064921201, 'portfolio_id': 5205529}, {'photo_id': 1064921196, 'portfolio_id': 5205529}, {'photo_id': 1064919876, 'portfolio_id': 5205529}, {'photo_id': 1064919873, 'portfolio_id': 5205529}, {'photo_id': 1064919869, 'portfolio_id': 5205529}, {'photo_id': 1064919862, 'portfolio_id': 5205529}, {'photo_id': 1064919858, 'portfolio_id': 5205529}, {'photo_id': 1064919856, 'portfolio_id': 5205529}, {'photo_id': 1064919752, 'portfolio_id': 5205529}, {'photo_id': 1064919748, 'portfolio_id': 5205529}, {'photo_id': 1064919745, 'portfolio_id': 5205529}, {'photo_id': 1064919741, 'portfolio_id': 5205529}, {'photo_id': 1064919737, 'portfolio_id': 5205529}, {'photo_id': 1064919730, 'portfolio_id': 5205529}, {'photo_id': 1064919660, 'portfolio_id': 5205529}] map_portfolio_id_photo_id: {5205529: [1064921404, 1064921402, 1064921401, 1064921201, 1064921196, 1064919876, 1064919873, 1064919869, 1064919862, 1064919858, 1064919856, 1064919752, 1064919748, 1064919745, 1064919741, 1064919737, 1064919730, 1064919660]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.015215396881103516 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:split_time_score Thu Sep 25 17:05:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} split portfolio by speed calcul order for each photo with time calcul time for a portfolio query : SELECT photo_id, text FROM MTRBack.view_photos_with_urls_250912 where photo_id in (SELECT mtr_photo_id FROM MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 5205529); result : ((1064919660, 'image_01122021_10_11_30_014389.jpg'), (1064919730, 'image_01122021_10_12_17_665202.jpg'), (1064919737, 'image_01122021_10_11_40_031052.jpg'), (1064919741, 'image_01122021_10_11_34_021658.jpg'), (1064919745, 'image_01122021_10_11_32_018001.jpg'), (1064919748, 'image_01122021_10_12_27_027057.jpg'), (1064919752, 'image_01122021_10_12_24_005017.jpg'), (1064919856, 'image_01122021_10_13_13_399843.jpg'), (1064919858, 'image_01122021_10_13_04_729164.jpg'), (1064919862, 'image_01122021_10_12_56_581019.jpg'), (1064919869, 'image_01122021_10_12_29_030603.jpg'), (1064919873, 'image_01122021_10_13_30_005720.jpg'), (1064919876, 'image_01122021_10_13_22_147712.jpg'), (1064921196, 'image_01122021_10_16_18_114975.jpg'), (1064921201, 'image_01122021_10_16_14_925132.jpg'), (1064921401, 'image_01122021_10_16_57_981306.jpg'), (1064921402, 'image_01122021_10_16_53_913663.jpg'), (1064921404, 'image_01122021_10_16_47_889875.jpg')) INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) VALUES (%s, %s, %s) on duplicate key update `order`=VALUES(`order`); first line : (5205529, 1064919660, 1098136690) ... last line : (5205529, 1064921404, 1098137007) ERROR in datou_step_exec, will save and exit ! tuple index out of range File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2523, in datou_step_exec return lib_process.datou_step_split_time_score(param, json_param, args, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 2348, in datou_step_split_time_score dic_gps_portfolio, dic_gps_portfolios_already_done = sgps.split_portfolio_from_gps_info( File "/home/admin/workarea/git/Velours/python/mtr/split_time_gps_score.py", line 609, in split_portfolio_from_gps_info dic_time_useful = get_dic_time_with_speed(portfolio_id, device_id, threshold_speed, threshold_max_time, File "/home/admin/workarea/git/Velours/python/mtr/split_time_gps_score.py", line 425, in get_dic_time_with_speed start_time, score_start, latitude_start, longitude_start = text_to_datetime(data[0][0]), data[0][1], data[0][2], \ ERROR in last step split_time_score, tuple index out of range time spend for datou_step_exec : 0.042615413665771484 time spend to save output : 0.0024192333221435547 total time spend for step 0 : 0.04503464698791504 Useless call to update_current_state caffe_path_current : About to save ! 0 After save, about to update current ! None 'NoneType' object has no attribute 'keys' ERROR broca FAILED ############################### TEST crop_conditional ################################ t Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=719 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=719 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 719 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=719 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 1335 frcnn is not linked in the step_by_step architecture ! WARNING : step 1336 crop_condition is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : frcnn, crop_condition list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (1981316) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (1981316) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 950003838, 'portfolio_id': 1981316}, {'photo_id': 950003813, 'portfolio_id': 1981316}, {'photo_id': 950003812, 'portfolio_id': 1981316}, {'photo_id': 950003696, 'portfolio_id': 1981316}, {'photo_id': 950003695, 'portfolio_id': 1981316}, {'photo_id': 926687666, 'portfolio_id': 1981316}] map_portfolio_id_photo_id: {1981316: [950003838, 950003813, 950003812, 950003696, 950003695, 926687666]} ##### Call download_photos : nb_thread : 5 begin to download photo : 950003838 begin to download photo : 950003812 begin to download photo : 950003695 download finish for photo 950003838 begin to download photo : 950003813 download finish for photo 950003812 begin to download photo : 950003696 download finish for photo 950003695 begin to download photo : 926687666 download finish for photo 950003813 download finish for photo 950003696 download finish for photo 926687666 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 6 ; length of list_pids : 6 ; length of list_args : 6 ##### After load_data_input time to download the photos : 0.3307645320892334 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 2 step1:frcnn Thu Sep 25 17:05:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg': 950003838, 'temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg': 950003813, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg': 950003812, 'temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg': 950003696, 'temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg': 950003695, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg': 926687666} map_photo_id_path_extension : {950003838: {'path': 'temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg', 'extension': 'jpg'}, 950003813: {'path': 'temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg', 'extension': 'jpg'}, 950003812: {'path': 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg', 'extension': 'jpg'}, 950003696: {'path': 'temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg', 'extension': 'jpg'}, 950003695: {'path': 'temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg', 'extension': 'jpg'}, 926687666: {'path': 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Faster rcnn ! Inside try reload ! classes : ['background', 'retroviseur', 'roue', 'capot', 'pare-brise', 'vitre', 'phare', 'feu-antibrouillard', 'feu-arriere', 'poignee', 'porte', 'radiateur', 'logo-marque', 'cache-reservoir', 'plaque-immatriculation', 'pot-echappement', 'info-modele', 'essuie-glace', 'pare-choc', 'coffre', 'carrosserie-autre', 'toit', 'logo-roue', 'aile-avant', 'aile-arriere', 'autre'] pht : 757 caffemodel_name (should be vgg16_immat_307 but not used because net loaded outside in the fonction) : {'id': 685, 'mtr_user_id': 31, 'name': 'learn_piece_voiture_0808_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,retroviseur,roue,capot,pare-brise,vitre,phare,feu-antibrouillard,feu-arriere,poignee,porte,radiateur,logo-marque,cache-reservoir,plaque-immatriculation,pot-echappement,info-modele,essuie-glace,pare-choc,coffre,carrosserie-autre,toit,logo-roue,aile-avant,aile-arriere,autre', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 757, 'photo_desc_type': 3800, 'type_classification': 'caffe_faster_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} To loadFromThcl() model_param file didn't exist model_name : learn_piece_voiture_0808_v2 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] local folder : /data/models_weight/learn_piece_voiture_0808_v2 /data/models_weight/learn_piece_voiture_0808_v2/caffemodel size_local : 350215080 size in s3 : 350215080 create time local : 2021-08-09 05:30:22 create time in s3 : 2021-08-06 19:24:16 caffemodel already exist and didn't need to update /data/models_weight/learn_piece_voiture_0808_v2/test.prototxt size_local : 7166 size in s3 : 7166 create time local : 2021-08-09 05:30:22 create time in s3 : 2021-08-06 19:24:16 test.prototxt already exist and didn't need to update prototxt : /data/models_weight/learn_piece_voiture_0808_v2/test.prototxt caffemodel : /data/models_weight/learn_piece_voiture_0808_v2/caffemodel Loaded network /data/models_weight/learn_piece_voiture_0808_v2/caffemodel About to compute detect_faster_rcnn : len(args) : 6 Inside frcnn step exec : nb paths : 6 image_path : temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg image_size (294, 285, 3) [[[ 29 29 29] [ 29 29 29] [ 30 30 30] ... [182 172 165] [141 131 124] [103 94 90]] [[ 29 29 29] [ 29 29 29] [ 31 31 31] ... [231 220 212] [202 193 184] [164 154 147]] [[ 30 30 30] [ 27 27 27] [ 26 26 26] ... [223 211 199] [229 219 209] [228 217 209]] ... [[ 22 27 25] [ 16 21 19] [ 11 16 14] ... [166 145 123] [168 147 125] [170 149 127]] [[ 20 25 23] [ 17 22 20] [ 15 20 18] ... [163 142 120] [165 144 122] [166 145 123]] [[ 13 18 16] [ 17 22 20] [ 20 25 23] ... [162 141 119] [163 142 120] [163 142 121]]] Detection took 0.082s for 300 object proposals c : aile-arriere list_crops.shape (29, 5) proba : 0.052096367 (104.29355, 64.893715, 245.01569, 262.5957) proba : 0.01147381 (156.04828, 154.27747, 276.97528, 234.77829) proba : 0.010066274 (133.89166, 191.03581, 199.79562, 262.36087) c : aile-avant list_crops.shape (30, 5) proba : 0.16406414 (93.39934, 110.00657, 261.18365, 244.4562) proba : 0.011732286 (153.08563, 215.95956, 224.00381, 288.5535) c : autre list_crops.shape (31, 5) c : cache-reservoir list_crops.shape (30, 5) proba : 0.01679054 (12.161736, 54.52997, 94.04323, 89.234604) c : capot list_crops.shape (24, 5) proba : 0.101516075 (69.293, 0.0, 280.00424, 54.912407) proba : 0.08459719 (113.75963, 84.13779, 262.94427, 231.19153) proba : 0.040668678 (6.739399, 36.86412, 96.112305, 92.563995) c : carrosserie-autre list_crops.shape (27, 5) c : coffre list_crops.shape (23, 5) proba : 0.04764697 (53.505318, 0.0, 284.0, 92.37445) proba : 0.032663688 (10.158447, 31.722492, 95.70244, 100.60936) proba : 0.0121540455 (235.39505, 155.04231, 284.0, 216.00706) c : essuie-glace list_crops.shape (31, 5) proba : 0.80940473 (149.03458, 63.96386, 284.0, 87.61506) proba : 0.034234226 (13.640041, 56.073277, 92.06749, 89.415985) proba : 0.020680286 (234.32034, 175.75385, 284.0, 231.14685) c : feu-antibrouillard list_crops.shape (33, 5) proba : 0.055683102 (27.497038, 50.043278, 86.94486, 89.45697) proba : 0.018113298 (229.45229, 178.30977, 279.93097, 220.47224) proba : 0.010317451 (206.26294, 260.46304, 253.11868, 293.0) c : feu-arriere list_crops.shape (34, 5) proba : 0.068286695 (27.727901, 49.24185, 86.893036, 88.09239) proba : 0.024005363 (231.78021, 177.12973, 279.95206, 219.17023) c : info-modele list_crops.shape (34, 5) proba : 0.015900698 (27.181301, 48.779984, 87.638535, 89.72066) c : logo-marque list_crops.shape (32, 5) proba : 0.010619333 (206.26877, 219.39255, 262.95175, 293.0) c : logo-roue list_crops.shape (30, 5) c : pare-brise list_crops.shape (24, 5) proba : 0.38033852 (84.45198, 0.0, 284.0, 80.629425) proba : 0.06984858 (21.856419, 45.93213, 86.82936, 90.58226) proba : 0.010922711 (162.28929, 212.50713, 227.27986, 293.0) proba : 0.010167454 (238.71916, 156.77779, 284.0, 216.5884) c : pare-choc list_crops.shape (20, 5) proba : 0.15659314 (75.041214, 12.039795, 284.0, 83.46875) proba : 0.039184783 (173.62772, 206.8929, 284.0, 287.13156) proba : 0.029328886 (3.5338058, 39.446266, 99.708824, 103.58506) proba : 0.021780988 (236.46072, 158.82742, 284.0, 219.94086) c : phare list_crops.shape (33, 5) proba : 0.29548955 (16.08509, 55.13311, 94.491005, 86.99996) proba : 0.01716362 (85.86744, 17.95664, 272.2648, 68.439156) proba : 0.013773416 (241.5822, 159.23846, 284.0, 213.74615) proba : 0.011595914 (207.11023, 255.55263, 262.2596, 293.0) c : plaque-immatriculation list_crops.shape (37, 5) proba : 0.13104841 (235.83813, 174.31505, 284.0, 225.21608) proba : 0.039649326 (30.735771, 49.49452, 81.55668, 87.7057) c : poignee list_crops.shape (27, 5) c : porte list_crops.shape (24, 5) proba : 0.6000436 (23.91537, 0.0, 103.22275, 219.54791) proba : 0.028163597 (2.5912304, 0.0, 48.60354, 196.39478) proba : 0.012119712 (103.534, 0.101737976, 235.16919, 252.15588) c : pot-echappement list_crops.shape (30, 5) proba : 0.02131951 (228.93701, 176.45145, 280.01184, 221.2583) proba : 0.013256723 (208.91805, 255.16234, 263.81366, 293.0) proba : 0.013241499 (26.967642, 48.15839, 87.17605, 89.94566) c : radiateur list_crops.shape (30, 5) c : retroviseur list_crops.shape (32, 5) proba : 0.03768621 (14.680901, 54.76747, 94.671074, 89.58748) proba : 0.012228387 (210.4583, 255.86531, 263.11288, 293.0) proba : 0.010143452 (231.18497, 176.60303, 279.56503, 220.06207) c : roue list_crops.shape (34, 5) proba : 0.8120733 (146.79518, 218.47331, 218.13359, 292.02487) proba : 0.27969825 (135.7283, 224.49391, 169.58667, 293.0) proba : 0.044858478 (29.87716, 37.66617, 91.515976, 83.93997) proba : 0.025316466 (7.384598, 0.09248543, 44.255005, 34.973885) proba : 0.018802246 (234.255, 172.02249, 277.34998, 219.31058) proba : 0.011280988 (206.81795, 251.68658, 258.8723, 293.0) c : toit list_crops.shape (29, 5) c : vitre list_crops.shape (32, 5) proba : 0.14830734 (152.67358, 220.60931, 208.97363, 293.0) proba : 0.034724515 (235.50754, 173.75595, 284.0, 228.07697) proba : 0.030441048 (137.98093, 226.12851, 164.95541, 293.0) proba : 0.01885243 (18.03835, 51.718384, 93.859055, 87.637375) We are managing local photo_id image_path : temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg image_size (254, 229, 3) [[[202 190 186] [205 193 189] [205 194 190] ... [ 81 70 56] [ 80 69 55] [ 78 67 53]] [[198 187 183] [200 189 185] [198 189 185] ... [ 50 41 28] [ 44 36 23] [ 45 36 23]] [[192 187 184] [191 186 183] [191 186 183] ... [ 36 30 23] [ 32 29 21] [ 33 27 20]] ... [[187 186 190] [186 185 189] [188 184 189] ... [ 43 38 35] [ 37 33 28] [ 33 28 25]] [[184 185 189] [183 184 188] [184 183 187] ... [ 28 23 22] [ 29 24 21] [ 33 28 27]] [[181 185 186] [180 184 185] [182 184 185] ... [ 23 15 16] [ 22 14 14] [ 24 16 17]]] Detection took 0.061s for 300 object proposals c : aile-arriere list_crops.shape (29, 5) proba : 0.0676943 (98.07235, 150.88171, 151.94044, 223.72348) proba : 0.04091063 (33.36522, 90.135475, 179.12746, 182.83743) proba : 0.016988335 (79.351364, 122.719086, 111.495316, 230.36475) c : aile-avant list_crops.shape (31, 5) proba : 0.048582956 (43.720093, 17.109566, 139.32678, 207.16653) proba : 0.01007987 (62.04381, 104.14325, 183.71765, 182.30496) c : autre list_crops.shape (32, 5) c : cache-reservoir list_crops.shape (33, 5) c : capot list_crops.shape (22, 5) proba : 0.09677551 (38.044334, 75.4243, 207.15027, 166.65959) c : carrosserie-autre list_crops.shape (24, 5) c : coffre list_crops.shape (21, 5) proba : 0.06442337 (165.4751, 115.30365, 226.39896, 165.47678) c : essuie-glace list_crops.shape (34, 5) proba : 0.3860973 (88.270065, 10.885819, 179.58443, 31.358536) proba : 0.04240274 (133.09924, 1.8784552, 227.74323, 26.529877) proba : 0.024032252 (169.25471, 117.38413, 218.91545, 165.4338) proba : 0.010854663 (61.5513, 1.937788, 117.820786, 33.00418) c : feu-antibrouillard list_crops.shape (32, 5) proba : 0.019599574 (168.92467, 117.953415, 219.53084, 165.85646) c : feu-arriere list_crops.shape (30, 5) proba : 0.022236556 (171.0735, 119.67668, 221.0096, 164.20021) c : info-modele list_crops.shape (31, 5) proba : 0.01020085 (168.5222, 116.05222, 219.95375, 166.43416) c : logo-marque list_crops.shape (34, 5) proba : 0.015150817 (154.45406, 207.10782, 180.12437, 244.77243) c : logo-roue list_crops.shape (29, 5) c : pare-brise list_crops.shape (27, 5) proba : 0.04709421 (168.768, 117.313614, 222.88739, 165.84215) proba : 0.0136061115 (53.45957, 0.0, 178.92084, 22.404284) proba : 0.012164364 (15.941434, 0.0, 44.89673, 48.295246) c : pare-choc list_crops.shape (23, 5) proba : 0.089851975 (166.06534, 118.16012, 226.88037, 168.71373) proba : 0.012228154 (108.19693, 130.85791, 228.0, 249.22647) c : phare list_crops.shape (37, 5) proba : 0.013691323 (172.01453, 118.39657, 223.30783, 162.23991) c : plaque-immatriculation list_crops.shape (38, 5) proba : 0.051209282 (173.59468, 120.67762, 218.52486, 161.78477) c : poignee list_crops.shape (31, 5) c : porte list_crops.shape (25, 5) proba : 0.03930467 (4.7745304, 0.0, 38.132317, 169.7076) proba : 0.014844477 (170.32507, 112.39807, 220.70605, 170.46451) proba : 0.013463728 (19.340092, 0.0, 92.46385, 176.28668) c : pot-echappement list_crops.shape (31, 5) proba : 0.021787692 (168.5678, 115.56282, 219.416, 166.48653) proba : 0.016470816 (154.52562, 206.31924, 179.71242, 244.10657) c : radiateur list_crops.shape (30, 5) c : retroviseur list_crops.shape (34, 5) proba : 0.010121827 (169.53546, 116.20875, 219.60461, 166.28908) c : roue list_crops.shape (36, 5) proba : 0.106334195 (83.71924, 166.05328, 133.41441, 253.0) proba : 0.050476946 (73.95791, 164.66762, 104.24108, 236.1451) proba : 0.032672014 (18.137667, 0.0, 45.997704, 33.78601) c : toit list_crops.shape (33, 5) c : vitre list_crops.shape (34, 5) proba : 0.028296245 (20.599483, 0.0, 45.493412, 43.05545) proba : 0.01535127 (170.8744, 118.45862, 221.03395, 164.4949) We are managing local photo_id image_path : temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg image_size (480, 614, 3) [[[ 44 44 44] [ 49 51 51] [ 42 44 44] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[ 43 43 43] [ 36 38 38] [ 39 41 41] ... [ 5 7 7] [ 5 7 7] [ 5 7 7]] [[ 70 70 70] [ 40 42 42] [ 41 43 43] ... [ 4 6 6] [ 4 6 6] [ 4 6 6]] ... [[103 101 101] [110 108 108] [ 61 59 59] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[ 98 96 96] [115 113 113] [ 73 71 71] ... [ 0 2 2] [ 11 13 13] [ 21 23 23]] [[ 92 90 90] [114 112 112] [ 87 82 83] ... [ 10 12 12] [ 18 20 20] [ 25 27 27]]] Detection took 0.052s for 300 object proposals c : aile-arriere list_crops.shape (30, 5) proba : 0.13238405 (133.29669, 172.3922, 280.82635, 321.4948) proba : 0.013274833 (153.19455, 232.50517, 369.7673, 359.78223) c : aile-avant list_crops.shape (35, 5) proba : 0.95040345 (133.96732, 146.16475, 305.78027, 344.49078) proba : 0.020742293 (128.14935, 143.01099, 188.89832, 305.02817) proba : 0.014927024 (294.2434, 331.83652, 412.498, 415.32944) proba : 0.011199896 (533.05774, 198.27531, 583.4977, 268.45807) proba : 0.010005645 (0.0, 114.21178, 47.5912, 234.00252) c : autre list_crops.shape (36, 5) c : cache-reservoir list_crops.shape (35, 5) proba : 0.025677225 (426.69934, 57.936348, 496.61865, 125.30952) proba : 0.025273118 (342.52142, 266.61572, 421.3423, 330.5551) proba : 0.017258476 (306.41116, 352.42963, 382.60562, 422.00146) c : capot list_crops.shape (32, 5) proba : 0.9904717 (196.74286, 110.37725, 532.5119, 291.96216) proba : 0.22523193 (40.243317, 25.965664, 253.15472, 48.718327) proba : 0.058450643 (318.88824, 286.61377, 481.5902, 427.89368) proba : 0.017961597 (64.439835, 38.402863, 331.2721, 64.356415) proba : 0.010635582 (116.14848, 36.75095, 368.6385, 155.92462) c : carrosserie-autre list_crops.shape (29, 5) proba : 0.030299842 (429.34695, 22.058395, 497.81882, 122.47656) c : coffre list_crops.shape (29, 5) proba : 0.12301332 (421.33716, 15.516624, 501.77582, 119.21833) proba : 0.10120072 (112.74458, 46.268486, 395.271, 193.28424) proba : 0.06281985 (247.78203, 171.97653, 517.5131, 335.85648) c : essuie-glace list_crops.shape (37, 5) proba : 0.77173024 (178.34586, 109.07056, 389.54172, 147.69672) proba : 0.14846176 (343.2803, 268.29132, 419.46036, 332.34406) proba : 0.10076672 (364.45496, 261.52084, 501.2329, 317.8652) proba : 0.04793521 (446.582, 21.59082, 508.33078, 88.69631) proba : 0.03781278 (328.7603, 360.4611, 389.8579, 423.33487) proba : 0.014704341 (85.60539, 24.02155, 308.09546, 43.355793) proba : 0.0138524 (267.0359, 240.33751, 412.96118, 348.48767) proba : 0.012839942 (427.07437, 58.155735, 496.3522, 124.40059) c : feu-antibrouillard list_crops.shape (37, 5) proba : 0.21096717 (307.2801, 354.3133, 381.79547, 421.6104) proba : 0.056849163 (342.86563, 269.36578, 420.85953, 329.4417) proba : 0.028138764 (427.12225, 58.81718, 496.14905, 124.54837) proba : 0.02352742 (362.92978, 264.4477, 504.08957, 316.84088) c : feu-arriere list_crops.shape (34, 5) proba : 0.09635551 (303.1505, 259.64267, 431.2906, 316.44614) proba : 0.041332804 (428.95145, 25.616848, 497.48532, 104.48291) proba : 0.034464166 (305.4746, 351.55835, 379.5114, 423.94067) c : info-modele list_crops.shape (36, 5) proba : 0.04286134 (306.7388, 353.51434, 383.17557, 421.5606) proba : 0.035218082 (426.5226, 57.952568, 497.43954, 125.60998) proba : 0.033363197 (342.9605, 267.56012, 422.67786, 330.89575) proba : 0.016014084 (363.5862, 261.26434, 507.57114, 317.39355) proba : 0.010809551 (445.90082, 19.32677, 507.99744, 91.462265) c : logo-marque list_crops.shape (36, 5) proba : 0.1054157 (327.43378, 361.32648, 387.95605, 423.03455) proba : 0.028344732 (344.9641, 265.39224, 421.62677, 329.04623) proba : 0.025367932 (370.86057, 261.33978, 500.61533, 316.38782) proba : 0.017481606 (427.6004, 57.646923, 496.7885, 125.72131) c : logo-roue list_crops.shape (34, 5) proba : 0.014206161 (327.66263, 360.7192, 388.8018, 424.041) c : pare-brise list_crops.shape (30, 5) proba : 0.95463413 (113.60896, 42.325066, 417.92413, 147.55585) proba : 0.10699682 (294.67813, 24.328571, 399.70676, 129.18077) proba : 0.05409858 (258.52264, 161.27579, 521.57104, 295.06735) proba : 0.027621958 (424.62595, 20.861965, 499.57193, 97.22345) proba : 0.017620575 (72.589516, 41.742493, 127.2532, 168.79144) c : pare-choc list_crops.shape (25, 5) proba : 0.9485578 (247.46962, 265.46924, 552.9361, 445.27606) proba : 0.09525997 (194.32129, 225.23447, 348.43274, 419.22806) proba : 0.019616487 (422.4505, 329.6103, 549.53204, 424.81177) proba : 0.014918469 (455.54388, 26.130047, 592.81805, 120.21626) c : phare list_crops.shape (35, 5) proba : 0.67818624 (318.13217, 264.66098, 489.9061, 310.63443) proba : 0.4032982 (261.64102, 234.11661, 408.51443, 331.02536) proba : 0.0958863 (301.10492, 356.4171, 385.49835, 425.23444) proba : 0.0146546895 (525.66785, 198.54634, 575.2178, 289.94904) proba : 0.013314551 (427.9971, 23.331573, 501.30173, 100.64505) proba : 0.01149545 (277.73444, 207.81836, 557.2648, 296.85666) c : plaque-immatriculation list_crops.shape (36, 5) proba : 0.19051768 (491.39282, 294.22284, 563.82385, 390.17578) proba : 0.05778237 (439.5157, 291.40857, 531.0522, 407.16632) proba : 0.022951912 (298.9806, 257.41486, 447.53516, 319.1723) proba : 0.011338366 (309.84082, 356.20654, 386.1568, 421.93427) c : poignee list_crops.shape (34, 5) proba : 0.02566818 (327.50882, 360.97052, 388.4728, 424.01904) proba : 0.024166513 (342.31433, 266.8902, 422.4926, 331.5276) proba : 0.02198733 (426.42493, 57.753025, 497.07886, 125.79361) proba : 0.013409225 (559.00696, 0.020671844, 613.0, 71.291824) c : porte list_crops.shape (27, 5) proba : 0.9922959 (51.419865, 40.442154, 152.79797, 306.3875) proba : 0.97203034 (4.568035, 51.356575, 72.87387, 242.4668) proba : 0.058669373 (425.32166, 19.071342, 501.1234, 130.87851) proba : 0.030508326 (132.0904, 46.46113, 397.16486, 213.57916) proba : 0.014543873 (360.30084, 244.28181, 551.60815, 395.6197) c : pot-echappement list_crops.shape (36, 5) proba : 0.050581794 (328.17007, 360.69583, 387.76968, 423.7305) proba : 0.020144396 (427.15628, 57.463238, 496.2933, 125.83847) c : radiateur list_crops.shape (35, 5) c : retroviseur list_crops.shape (35, 5) proba : 0.43164772 (427.40793, 56.776558, 495.94437, 123.66572) proba : 0.18574244 (344.11078, 266.81497, 421.86224, 331.86935) proba : 0.11663176 (446.8671, 19.43835, 506.4647, 90.9491) proba : 0.048031725 (316.7072, 363.191, 377.64038, 430.7927) proba : 0.027538888 (150.80759, 116.12115, 381.5804, 150.21878) proba : 0.012776406 (366.313, 260.31454, 504.9254, 318.49118) proba : 0.011191596 (77.32764, 81.656105, 130.17624, 174.47586) c : roue list_crops.shape (37, 5) proba : 0.9375714 (166.73569, 261.1281, 275.22195, 420.81134) proba : 0.1407698 (307.79385, 351.35474, 385.35544, 430.9654) proba : 0.1140408 (4.555546, 161.28644, 50.800537, 253.07123) proba : 0.04501529 (513.95447, 252.5576, 573.92175, 393.47748) proba : 0.037105616 (526.667, 191.77759, 581.6012, 303.9039) c : toit list_crops.shape (33, 5) proba : 0.7964363 (58.20688, 31.456625, 315.98834, 55.60418) c : vitre list_crops.shape (33, 5) proba : 0.9803713 (69.39561, 49.35136, 135.83417, 142.42262) proba : 0.89376307 (14.669529, 41.220253, 66.174484, 115.178764) proba : 0.11748845 (205.48804, 48.10255, 379.2744, 127.90593) proba : 0.043755725 (428.1292, 21.894924, 499.21252, 97.15134) proba : 0.017627256 (308.70776, 352.4777, 385.6867, 423.24918) proba : 0.012128216 (338.94943, 258.5372, 419.88406, 323.73868) We are managing local photo_id image_path : temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg image_size (2160, 3264, 3) [[[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 48 60 64] [ 48 60 64]] [[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 47 59 63] [ 48 60 64]] [[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 47 59 63] [ 47 59 63]] ... [[167 164 160] [167 164 160] [167 164 160] ... [ 44 59 61] [ 44 59 61] [ 44 59 61]] [[165 162 158] [165 162 158] [165 162 158] ... [ 45 60 62] [ 45 60 62] [ 45 60 62]] [[164 161 157] [164 161 157] [164 161 157] ... [ 45 60 62] [ 45 60 62] [ 45 60 62]]] Detection took 0.520s for 300 object proposals c : aile-arriere list_crops.shape (52, 5) proba : 0.020719577 (396.2245, 192.55806, 703.2379, 482.50806) proba : 0.013662897 (2606.4897, 1489.7299, 2954.4062, 2131.4053) proba : 0.010280435 (2270.172, 1651.426, 2706.3909, 2138.8591) proba : 0.010019158 (2922.7314, 683.2668, 3263.0, 1188.8936) c : aile-avant list_crops.shape (55, 5) proba : 0.025828574 (2616.2104, 1475.3445, 2938.8496, 2144.0435) c : autre list_crops.shape (53, 5) proba : 0.013096905 (405.69452, 192.22098, 689.0905, 476.5048) c : cache-reservoir list_crops.shape (50, 5) proba : 0.029480321 (2629.4827, 1461.0199, 2954.7288, 2148.8547) proba : 0.024528176 (299.2472, 89.55818, 716.6851, 498.42566) proba : 0.020116448 (2232.0417, 676.7409, 2590.5046, 1171.211) proba : 0.018791577 (2298.3838, 1682.7819, 2783.6611, 2156.6443) proba : 0.012400466 (2317.1362, 1436.0558, 2614.482, 1924.9562) proba : 0.012134888 (2925.1462, 677.3064, 3258.8938, 1209.0406) c : capot list_crops.shape (44, 5) proba : 0.018008478 (2645.9812, 973.0471, 3214.7253, 1642.1089) proba : 0.016425703 (77.7561, 795.98584, 694.0069, 1481.0928) c : carrosserie-autre list_crops.shape (45, 5) proba : 0.029314604 (251.58325, 0.0, 712.4898, 635.08594) proba : 0.013687955 (2284.6914, 1569.4844, 2687.3735, 2159.0) c : coffre list_crops.shape (42, 5) proba : 0.13924892 (283.02768, 0.0, 631.68384, 633.48413) proba : 0.013912267 (1720.5803, 507.76526, 2227.85, 1191.3527) c : essuie-glace list_crops.shape (56, 5) proba : 0.018920245 (320.89423, 110.24249, 601.0042, 462.48285) proba : 0.013811163 (2187.618, 749.49316, 2497.301, 1214.4868) proba : 0.013558354 (2629.338, 1462.9316, 2950.878, 2139.6565) proba : 0.013338867 (74.38945, 721.2061, 391.74988, 1112.9604) c : feu-antibrouillard list_crops.shape (52, 5) proba : 0.060828418 (372.09964, 242.49052, 759.4325, 515.9196) proba : 0.018308356 (2928.3782, 694.31165, 3257.6501, 1206.6497) proba : 0.018102916 (2299.5396, 1693.8378, 2784.125, 2158.6943) proba : 0.015854396 (2230.3591, 698.5269, 2591.159, 1175.3013) proba : 0.014356949 (2630.7583, 1480.992, 2954.4863, 2151.759) proba : 0.011739812 (383.55118, 1437.1143, 937.13855, 1845.135) c : feu-arriere list_crops.shape (48, 5) proba : 0.6467292 (354.84918, 213.38074, 730.16315, 532.05084) proba : 0.12030472 (2225.6543, 661.1727, 2605.204, 1235.9158) proba : 0.07936382 (256.18628, 24.234161, 540.24786, 478.1276) proba : 0.060695384 (1807.4303, 656.74536, 2155.9155, 1147.374) proba : 0.03355737 (2308.1821, 1667.5486, 2786.7573, 2159.0) proba : 0.03225385 (2930.4414, 638.0899, 3237.7632, 1243.1941) proba : 0.018528348 (619.94104, 619.2474, 953.74414, 1223.5903) proba : 0.017302794 (2630.691, 1496.9172, 2955.3926, 2159.0) proba : 0.016656768 (2317.2385, 1411.098, 2618.2644, 1961.6954) proba : 0.015818803 (770.6277, 939.7135, 1053.5712, 1456.1444) proba : 0.010593495 (2489.446, 424.4935, 2939.1882, 1234.4342) proba : 0.01026499 (828.05396, 1.9253082, 1174.967, 369.9041) proba : 0.01009242 (14.196335, 430.89423, 165.1028, 734.0275) c : info-modele list_crops.shape (49, 5) proba : 0.070082396 (403.72897, 194.21658, 693.0519, 475.90335) proba : 0.022201959 (2299.2515, 1684.2316, 2787.1143, 2154.6643) proba : 0.019053577 (2232.6008, 682.5195, 2592.7273, 1170.8376) proba : 0.017020209 (2630.5908, 1468.2188, 2959.734, 2151.3535) proba : 0.0108795455 (1.752594, 575.78156, 261.91144, 885.70245) c : logo-marque list_crops.shape (51, 5) proba : 0.051871262 (408.49652, 200.25783, 688.27155, 481.55695) proba : 0.03407735 (2304.7751, 1690.4198, 2793.888, 2159.0) proba : 0.01823612 (2631.481, 1489.2504, 2968.0078, 2159.0) proba : 0.013036681 (2236.6812, 683.87805, 2594.5835, 1180.4908) proba : 0.011358813 (2319.9644, 1440.41, 2621.3862, 1933.8365) c : logo-roue list_crops.shape (52, 5) proba : 0.030217335 (402.7812, 191.06863, 692.7535, 478.26584) proba : 0.020897489 (2230.9229, 677.73157, 2592.7095, 1174.0024) proba : 0.01841293 (2512.7625, 492.6867, 2833.548, 843.9898) proba : 0.018072013 (2298.681, 1681.3318, 2786.0852, 2156.1255) proba : 0.0135518005 (2610.3855, 558.7982, 3007.5432, 1178.0172) proba : 0.013282783 (1762.7916, 675.1025, 2234.7014, 1109.9496) proba : 0.01241142 (2317.805, 1434.3556, 2615.2634, 1928.4249) proba : 0.011196002 (2783.5847, 1527.397, 3036.1204, 2077.7458) c : pare-brise list_crops.shape (46, 5) proba : 0.05498652 (2411.583, 398.6714, 2957.3633, 1171.552) proba : 0.045020048 (2240.3418, 634.8826, 2579.25, 1217.4407) proba : 0.026920388 (1424.812, 304.90222, 2074.727, 1161.5814) proba : 0.025702408 (312.56268, 97.23491, 605.9277, 472.6078) proba : 0.024203345 (2954.8008, 604.7595, 3255.359, 1264.4849) proba : 0.021961335 (2056.8357, 93.68915, 2392.5325, 713.71936) proba : 0.020823507 (323.8213, 1090.7004, 787.156, 1678.9487) proba : 0.018579325 (103.63376, 794.4404, 696.1987, 1524.2559) proba : 0.017086867 (2701.8296, 949.3695, 3158.2666, 1362.841) proba : 0.011480583 (2240.9001, 3.3525085, 2720.197, 772.58704) proba : 0.010906513 (1694.8032, 659.71497, 2162.8691, 1116.593) c : pare-choc list_crops.shape (38, 5) proba : 0.10620872 (347.37628, 1367.4347, 1073.0273, 1857.0646) proba : 0.016681604 (1310.4026, 1570.4387, 2576.619, 2051.2708) proba : 0.010976646 (0.0, 545.1286, 997.89185, 1254.1321) proba : 0.010150011 (2850.2505, 1465.3861, 3233.6406, 2099.7593) c : phare list_crops.shape (49, 5) proba : 0.069437556 (2930.6902, 682.54517, 3257.6667, 1220.2439) proba : 0.064080894 (310.52557, 118.370575, 715.9687, 508.6002) proba : 0.028813202 (324.57782, 1179.3375, 758.8121, 1634.1952) proba : 0.01300311 (2226.5676, 695.22253, 2603.422, 1195.8141) proba : 0.011197574 (83.41025, 743.99414, 419.8773, 1117.4803) proba : 0.010500739 (2318.0784, 1449.4445, 2631.681, 1922.1332) c : plaque-immatriculation list_crops.shape (55, 5) proba : 0.057370443 (399.6289, 207.96259, 679.6095, 493.95404) proba : 0.04577197 (1744.0753, 665.8771, 2221.145, 1071.6555) proba : 0.023891516 (2294.981, 1697.7318, 2792.1958, 2132.5781) proba : 0.023444267 (2538.7993, 1521.5615, 2898.8838, 2073.3552) proba : 0.013997716 (2783.4597, 1564.867, 3034.8918, 2056.8074) proba : 0.013539241 (2245.3252, 695.2412, 2573.151, 1168.4343) proba : 0.011301861 (2945.9404, 676.89905, 3251.0142, 1190.9658) c : poignee list_crops.shape (48, 5) proba : 0.057077583 (2629.5178, 1457.6078, 2958.7805, 2152.9727) proba : 0.023787366 (2299.084, 1682.4124, 2785.609, 2157.3928) proba : 0.018130451 (2232.1616, 677.8313, 2592.0854, 1173.5872) proba : 0.014418898 (403.02374, 191.03104, 692.2663, 478.382) c : porte list_crops.shape (42, 5) proba : 0.1267895 (2295.5688, 1531.376, 2685.6729, 2159.0) proba : 0.044976473 (2857.496, 1450.7213, 3263.0, 2032.975) proba : 0.041269414 (2466.1396, 1663.939, 3030.1982, 2159.0) proba : 0.028293677 (390.16754, 1195.2137, 897.94586, 1796.6759) proba : 0.02354853 (1444.4933, 1494.0955, 2537.7573, 2103.8562) proba : 0.017233398 (311.32562, 15.95459, 609.7352, 659.82587) proba : 0.012646953 (2938.5774, 622.9835, 3247.807, 1300.464) c : pot-echappement list_crops.shape (49, 5) proba : 0.033075772 (2632.8594, 1456.6216, 2954.8047, 2152.6938) proba : 0.030936684 (2302.484, 1680.4087, 2781.5732, 2157.6838) proba : 0.01597139 (405.3097, 189.9853, 691.1432, 477.748) proba : 0.011721044 (67.239105, 695.82544, 394.60754, 1122.9237) proba : 0.01140144 (1748.3528, 537.0469, 2217.0151, 1143.0498) proba : 0.01103084 (2926.5422, 674.97546, 3258.5608, 1211.8668) c : radiateur list_crops.shape (50, 5) c : retroviseur list_crops.shape (52, 5) proba : 0.083660826 (2235.1975, 682.09314, 2591.194, 1175.4066) proba : 0.05949097 (2321.9436, 1443.8893, 2613.5676, 1922.5814) proba : 0.043869168 (2937.0735, 682.27844, 3252.615, 1205.0328) proba : 0.042291325 (2632.658, 1459.1208, 2953.6814, 2146.3203) proba : 0.034057986 (71.96506, 699.8376, 393.33105, 1120.5234) proba : 0.031865153 (308.8125, 91.405136, 716.18225, 497.2406) proba : 0.025061456 (2306.495, 1681.1897, 2777.2515, 2150.3696) proba : 0.019788656 (2394.7383, 1122.3638, 2636.1616, 1534.4548) proba : 0.018270776 (2293.5222, 971.49164, 2576.6477, 1378.5416) proba : 0.016419461 (2956.3328, 1594.2266, 3251.535, 2041.866) proba : 0.015729198 (10.903412, 573.5215, 252.96967, 882.49963) proba : 0.015471095 (2710.9854, 884.648, 3001.4468, 1337.111) proba : 0.014098432 (2619.5127, 564.0324, 2997.3813, 1174.5017) proba : 0.013077104 (162.06436, 998.621, 907.7864, 1740.724) proba : 0.012830584 (2117.2524, 1467.145, 2431.4873, 2134.7542) proba : 0.012179985 (2070.648, 153.15704, 2426.6426, 695.5728) c : roue list_crops.shape (48, 5) proba : 0.082094155 (2921.282, 638.3745, 3254.5286, 1258.6927) proba : 0.058019046 (2507.5454, 1513.9666, 2926.2568, 2083.45) proba : 0.05731458 (2746.1392, 1692.6099, 3205.8574, 2127.3523) proba : 0.038226057 (2267.4512, 1589.3489, 2719.9434, 2144.457) proba : 0.029192938 (2521.5913, 448.81375, 3069.205, 1139.6516) proba : 0.026400486 (416.58347, 1400.4655, 896.45886, 1839.0773) proba : 0.022052616 (258.25232, 30.393005, 777.6583, 579.3261) proba : 0.018167527 (269.49878, 1082.432, 809.20154, 1696.9535) proba : 0.016243223 (814.93805, 0.0, 1180.1425, 343.59534) proba : 0.014417619 (1708.7582, 636.12256, 2206.2188, 1093.413) proba : 0.011404251 (2210.2676, 646.71826, 2617.3242, 1202.6737) c : toit list_crops.shape (51, 5) c : vitre list_crops.shape (47, 5) proba : 0.17965077 (2201.5337, 706.0818, 2505.7798, 1225.6472) proba : 0.13707449 (2332.1965, 1420.2551, 2614.7712, 1932.4609) proba : 0.09206075 (2941.3252, 639.2759, 3238.2432, 1233.308) proba : 0.0470937 (321.51086, 101.227646, 604.4596, 480.11346) proba : 0.041154016 (2545.2322, 540.129, 2972.1355, 1045.7649) proba : 0.03956984 (2362.6423, 1470.2004, 2901.4387, 2152.2366) proba : 0.03047886 (2784.095, 1531.0565, 3025.3738, 2079.112) proba : 0.017644214 (1748.7019, 547.4535, 2193.044, 1162.6233) proba : 0.01580093 (2879.637, 1427.3702, 3199.202, 2141.8413) proba : 0.010809802 (2403.9185, 706.2735, 2720.5195, 1277.5847) proba : 0.010705742 (2683.073, 868.77246, 2997.196, 1348.8635) We are managing local photo_id image_path : temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg image_size (2160, 3840, 3) [[[111 118 91] [113 120 93] [115 120 93] ... [ 23 40 37] [ 23 40 37] [ 24 41 38]] [[111 118 91] [112 119 92] [115 120 93] ... [ 23 40 37] [ 23 40 37] [ 23 40 37]] [[113 118 91] [114 119 92] [115 120 93] ... [ 22 39 36] [ 23 40 37] [ 23 40 37]] ... [[120 125 94] [119 124 93] [118 123 92] ... [ 22 36 34] [ 22 36 34] [ 23 37 35]] [[119 124 93] [119 124 93] [118 123 92] ... [ 22 36 34] [ 22 36 34] [ 22 36 34]] [[118 123 91] [117 122 90] [117 122 91] ... [ 22 36 34] [ 22 36 34] [ 22 36 34]]] Detection took 0.562s for 300 object proposals c : aile-arriere list_crops.shape (45, 5) proba : 0.016373789 (3266.6855, 1031.8986, 3839.0, 1714.3236) proba : 0.016076747 (16.381027, 491.0994, 406.7693, 799.849) proba : 0.012598177 (1997.6627, 259.4715, 2506.435, 848.935) proba : 0.011020518 (51.399033, 1690.1292, 479.94873, 1966.644) c : aile-avant list_crops.shape (41, 5) c : autre list_crops.shape (46, 5) c : cache-reservoir list_crops.shape (46, 5) c : capot list_crops.shape (38, 5) c : carrosserie-autre list_crops.shape (44, 5) c : coffre list_crops.shape (31, 5) c : essuie-glace list_crops.shape (49, 5) c : feu-antibrouillard list_crops.shape (44, 5) proba : 0.014230826 (3282.5625, 1219.762, 3793.543, 1821.4719) proba : 0.01260681 (27.949036, 498.89844, 410.0082, 789.6411) c : feu-arriere list_crops.shape (44, 5) proba : 0.07466659 (7.5945587, 454.29477, 376.21832, 791.5873) proba : 0.025199622 (3284.6672, 1151.9435, 3782.7156, 1834.2306) proba : 0.011051963 (17.657333, 1586.6896, 282.01056, 1995.7555) c : info-modele list_crops.shape (44, 5) proba : 0.018716345 (35.89969, 482.71857, 414.19577, 791.4683) c : logo-marque list_crops.shape (46, 5) proba : 0.017160183 (41.252396, 486.37555, 409.73505, 792.7204) c : logo-roue list_crops.shape (45, 5) c : pare-brise list_crops.shape (38, 5) proba : 0.016602192 (24.736755, 0.0, 388.8653, 684.5264) c : pare-choc list_crops.shape (35, 5) c : phare list_crops.shape (48, 5) c : plaque-immatriculation list_crops.shape (47, 5) proba : 0.02555914 (26.287476, 479.65466, 404.91632, 771.07556) proba : 0.016561054 (28.251678, 1620.7407, 299.37387, 1974.603) proba : 0.014698438 (18.401123, 3.583046, 386.72403, 255.02792) c : poignee list_crops.shape (43, 5) c : porte list_crops.shape (40, 5) proba : 0.11932412 (1872.7771, 10.179535, 2442.9543, 862.2648) proba : 0.11468544 (2136.5093, 52.94925, 2855.9824, 815.28906) proba : 0.024793515 (3234.8892, 69.59454, 3823.1216, 847.89233) proba : 0.013810583 (109.56218, 1835.4788, 459.84216, 2159.0) proba : 0.01138565 (3315.0046, 1115.5972, 3779.0125, 1883.8894) proba : 0.011384841 (1348.9752, 1049.3457, 1927.9532, 1777.0027) proba : 0.01075901 (2525.6794, 168.77109, 3531.5002, 924.1312) c : pot-echappement list_crops.shape (43, 5) proba : 0.03342415 (5.1139526, 1746.7181, 343.44092, 2019.2858) proba : 0.010659135 (117.19685, 1862.9634, 459.0335, 2155.1729) c : radiateur list_crops.shape (43, 5) c : retroviseur list_crops.shape (47, 5) proba : 0.018038457 (3296.5784, 1199.9899, 3787.9963, 1822.6254) proba : 0.013666872 (13.038879, 1748.9756, 340.38116, 2015.7693) proba : 0.012991171 (124.44557, 1867.7467, 456.31787, 2150.5205) c : roue list_crops.shape (45, 5) proba : 0.58397144 (3132.7485, 1107.5466, 3839.0, 1925.3428) proba : 0.045886155 (3481.2869, 1409.8824, 3814.301, 1997.3827) proba : 0.037302066 (38.59897, 1751.9751, 339.52823, 2013.6797) proba : 0.029176455 (3244.3843, 40.531464, 3721.561, 739.1975) proba : 0.018185057 (3167.0647, 383.71738, 3484.2498, 1016.3552) proba : 0.012425922 (229.07335, 0.0, 685.79785, 557.6339) proba : 0.010359958 (2689.1797, 224.92719, 3238.7783, 934.28436) c : toit list_crops.shape (48, 5) c : vitre list_crops.shape (44, 5) proba : 0.018343914 (23.036499, 0.0, 379.9069, 299.27448) proba : 0.014215506 (3321.2227, 1194.2993, 3770.2026, 1805.9485) We are managing local photo_id image_path : temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg image_size (480, 640, 3) [[[36 41 44] [36 41 44] [35 40 43] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[37 42 45] [36 41 44] [35 40 43] ... [ 5 7 7] [ 5 7 7] [ 5 7 7]] [[37 42 45] [36 41 44] [35 40 43] ... [ 3 5 5] [ 4 6 6] [ 4 6 6]] ... [[42 47 50] [41 46 49] [40 45 48] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[41 46 49] [41 46 49] [40 45 48] ... [ 0 2 2] [10 12 12] [22 24 24]] [[40 45 48] [40 45 48] [40 45 48] ... [10 12 12] [17 19 19] [26 28 28]]] Detection took 0.033s for 300 object proposals c : aile-arriere list_crops.shape (32, 5) proba : 0.12728998 (160.85881, 172.84787, 306.19507, 321.39444) proba : 0.011535905 (538.53436, 190.83368, 613.96515, 298.88898) proba : 0.010253662 (197.33133, 160.36865, 490.47403, 311.2705) c : aile-avant list_crops.shape (40, 5) proba : 0.94816077 (161.79846, 149.53621, 330.65472, 343.41577) proba : 0.09030602 (20.760735, 105.88429, 54.77575, 195.62886) proba : 0.022172904 (152.80403, 143.2782, 217.16698, 306.2615) proba : 0.013756868 (320.7013, 330.90726, 439.32996, 414.4456) proba : 0.011393955 (557.7656, 199.67093, 608.6659, 270.50903) c : autre list_crops.shape (36, 5) proba : 0.011426617 (458.26984, 15.2985, 521.1442, 98.992836) c : cache-reservoir list_crops.shape (37, 5) proba : 0.02974975 (470.567, 21.584114, 531.465, 89.200676) proba : 0.025542457 (368.27377, 265.8575, 446.90073, 331.26767) proba : 0.014927573 (353.33173, 360.48917, 412.48853, 423.13065) proba : 0.014714181 (451.11142, 57.610893, 523.16016, 125.93424) c : capot list_crops.shape (33, 5) proba : 0.99442816 (211.27887, 115.14381, 555.7708, 300.73825) proba : 0.23342976 (65.786194, 24.149918, 285.7371, 46.317528) proba : 0.034848675 (343.23743, 279.90952, 508.2091, 431.92087) proba : 0.017473388 (89.42586, 37.517284, 357.51453, 63.628742) proba : 0.010151449 (424.37415, 246.66705, 564.6234, 357.00262) c : carrosserie-autre list_crops.shape (35, 5) proba : 0.028548172 (454.54193, 25.079899, 523.52313, 121.41275) c : coffre list_crops.shape (31, 5) proba : 0.12967257 (446.42743, 19.300499, 528.34015, 117.91085) proba : 0.10254791 (139.89572, 45.98311, 419.52652, 192.66502) proba : 0.030864097 (269.2943, 162.00276, 553.942, 348.9416) c : essuie-glace list_crops.shape (40, 5) proba : 0.78950614 (203.8663, 108.231415, 416.75748, 147.35805) proba : 0.14472218 (369.06223, 267.5312, 445.0356, 332.95917) proba : 0.09796423 (391.05817, 261.18802, 527.0125, 318.13095) proba : 0.07720581 (470.4784, 22.210793, 532.07385, 88.022446) proba : 0.03541778 (354.3854, 360.35913, 414.2043, 422.9771) proba : 0.014148804 (114.83396, 22.670881, 335.36813, 42.9103) proba : 0.012224146 (254.57944, 94.72234, 456.81888, 288.5599) proba : 0.010930237 (353.83878, 285.56616, 484.79013, 414.69592) c : feu-antibrouillard list_crops.shape (39, 5) proba : 0.21194343 (341.78375, 363.48312, 404.84973, 430.65854) proba : 0.055868752 (368.6624, 268.62848, 446.445, 330.09277) proba : 0.025236217 (470.42902, 21.90839, 531.3952, 89.25705) proba : 0.023562737 (389.44672, 264.04688, 529.7876, 316.9602) proba : 0.016472628 (451.48767, 58.84027, 522.913, 125.210205) proba : 0.010562196 (467.00485, 343.55106, 573.7637, 420.2034) c : feu-arriere list_crops.shape (39, 5) proba : 0.10164772 (329.6699, 259.25992, 456.7178, 315.5507) proba : 0.042247683 (454.30167, 28.761307, 522.9135, 104.09885) proba : 0.025247276 (333.511, 352.84512, 405.06036, 425.97482) proba : 0.010692404 (475.56583, 341.53827, 575.44336, 420.15222) c : info-modele list_crops.shape (37, 5) proba : 0.070463724 (470.4895, 21.814594, 532.04236, 89.57263) proba : 0.038773835 (353.82886, 361.54083, 412.9958, 422.8529) proba : 0.033352006 (368.70792, 266.8143, 448.24356, 331.6299) proba : 0.023052989 (450.84167, 57.47097, 524.0725, 126.34316) proba : 0.015797926 (390.14072, 260.85123, 533.16876, 317.53494) c : logo-marque list_crops.shape (39, 5) proba : 0.119364776 (352.9692, 361.31387, 412.53116, 422.70078) proba : 0.032974675 (470.55667, 20.779179, 530.959, 88.80179) proba : 0.027512193 (370.8139, 264.58493, 447.2083, 329.64175) proba : 0.025026701 (397.47104, 260.82574, 526.3078, 316.55194) proba : 0.014329742 (584.1553, 0.7487526, 639.0, 70.73627) c : logo-roue list_crops.shape (37, 5) proba : 0.014609044 (353.32263, 360.72873, 413.24713, 423.6066) proba : 0.013224688 (470.34464, 21.601044, 532.06506, 89.58125) c : pare-brise list_crops.shape (34, 5) proba : 0.95698434 (141.09874, 42.466057, 444.0935, 147.77316) proba : 0.105155274 (319.45673, 22.01649, 424.03186, 129.1291) proba : 0.06655773 (453.8549, 19.659801, 523.2707, 91.54532) proba : 0.050983947 (287.21332, 164.06183, 547.3186, 296.7373) proba : 0.023291461 (95.5975, 40.14807, 158.49211, 162.53922) c : pare-choc list_crops.shape (29, 5) proba : 0.9453769 (272.90222, 257.5048, 580.24146, 444.44418) proba : 0.21968256 (233.4891, 224.18576, 397.76102, 411.54428) proba : 0.028822506 (487.97647, 17.564323, 613.4246, 120.57482) proba : 0.028756179 (435.96844, 307.78876, 588.6746, 426.5788) c : phare list_crops.shape (38, 5) proba : 0.77764606 (326.83917, 251.8909, 477.7754, 312.86343) proba : 0.07698666 (328.22107, 359.6377, 410.24243, 426.9674) proba : 0.03882485 (292.80957, 225.13927, 466.74323, 392.34332) proba : 0.033100802 (538.241, 197.21066, 600.21686, 303.43942) proba : 0.026038753 (466.65094, 20.84031, 531.7361, 84.11861) proba : 0.018856412 (305.6134, 209.47235, 597.71545, 307.11432) proba : 0.014261379 (478.9217, 344.12787, 578.6281, 416.75366) proba : 0.011289968 (96.66909, 66.9865, 163.91147, 147.69199) c : plaque-immatriculation list_crops.shape (38, 5) proba : 0.23006542 (518.56104, 294.1786, 582.3436, 390.77216) proba : 0.03377354 (438.4397, 271.76178, 568.42175, 386.55963) proba : 0.025868714 (347.18573, 259.77948, 452.87927, 315.9447) proba : 0.021144696 (470.38925, 23.621948, 531.61096, 85.3791) c : poignee list_crops.shape (35, 5) proba : 0.05437769 (583.3567, 0.030948639, 639.0, 70.98575) proba : 0.03403372 (470.4538, 21.59821, 531.6743, 89.77431) proba : 0.026380563 (353.17117, 360.95795, 412.89438, 423.59967) proba : 0.024485892 (368.05457, 266.1231, 448.0562, 332.26868) c : porte list_crops.shape (28, 5) proba : 0.98540986 (78.16702, 43.08365, 169.6531, 306.44498) proba : 0.9672482 (33.643547, 44.17678, 90.64844, 241.29678) proba : 0.09156001 (452.36978, 19.605885, 521.0887, 113.535675) proba : 0.034177084 (158.70956, 46.13968, 421.3383, 212.15402) proba : 0.012427902 (436.9631, 223.38242, 575.0617, 403.32608) c : pot-echappement list_crops.shape (37, 5) proba : 0.05553789 (353.8215, 360.70197, 412.23117, 423.33868) proba : 0.018788753 (458.05475, 14.546017, 521.2206, 99.67023) proba : 0.0129386345 (584.3939, 0.0, 639.0, 71.10063) proba : 0.01131859 (466.14355, 340.3402, 575.4005, 420.8803) c : radiateur list_crops.shape (38, 5) c : retroviseur list_crops.shape (39, 5) proba : 0.23814872 (452.17685, 56.797928, 522.1693, 124.12831) proba : 0.20779781 (471.1537, 21.540245, 531.2206, 89.272316) proba : 0.19335543 (369.90253, 266.02124, 447.44714, 332.58777) proba : 0.045618884 (342.49417, 362.45773, 404.12796, 431.0339) proba : 0.02658142 (176.92099, 115.94908, 409.85074, 150.13237) proba : 0.02146147 (584.3822, 0.0, 639.0, 70.68934) proba : 0.013624489 (392.94098, 259.885, 530.6082, 318.64453) proba : 0.010495384 (101.94341, 73.78746, 164.67833, 158.12709) c : roue list_crops.shape (38, 5) proba : 0.94178003 (187.78752, 271.24307, 306.50916, 426.33243) proba : 0.13538548 (334.87296, 358.32178, 400.07706, 428.79816) proba : 0.049759693 (538.71344, 251.02905, 600.0018, 395.29547) proba : 0.037402768 (12.769295, 136.7544, 64.16164, 244.91565) proba : 0.03481417 (549.3074, 192.38574, 605.79675, 305.71307) proba : 0.015747672 (479.68683, 335.91556, 572.48224, 421.2673) c : toit list_crops.shape (34, 5) proba : 0.79195976 (83.631485, 31.277035, 341.39124, 55.134907) c : vitre list_crops.shape (37, 5) proba : 0.9804714 (95.8302, 50.273872, 162.35284, 142.97385) proba : 0.8425389 (42.27382, 43.052338, 91.28218, 114.968216) proba : 0.07668867 (277.4176, 28.777885, 404.6596, 139.5506) proba : 0.06447827 (455.88464, 20.459625, 518.84155, 90.14311) proba : 0.027514724 (148.30182, 51.20488, 356.01385, 112.50839) proba : 0.013178153 (336.1944, 352.38312, 408.22076, 424.23248) proba : 0.0124606155 (364.9295, 257.4683, 445.5263, 324.0403) We are managing local photo_id len de result frcnn : 6 After datou_step_exec type output : time spend for datou_step_exec : 3.8016819953918457 time spend to save output : 0.00043201446533203125 total time spend for step 1 : 3.8021140098571777 step2:crop_condition Thu Sep 25 17:05:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg': 950003838, 'temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg': 950003813, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg': 950003812, 'temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg': 950003696, 'temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg': 950003695, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg': 926687666} map_photo_id_path_extension : {950003838: {'path': 'temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg', 'extension': 'jpg'}, 950003813: {'path': 'temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg', 'extension': 'jpg'}, 950003812: {'path': 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg', 'extension': 'jpg'}, 950003696: {'path': 'temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg', 'extension': 'jpg'}, 950003695: {'path': 'temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg', 'extension': 'jpg'}, 926687666: {'path': 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} param_json : {'photo_hashtag_type': 757, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'feed_id_new_photos': 1981313, 'host': 'www.fotonower.com', 'filter': {'phare': {'margin_type': 'margin', 'margin_value': 300, 'feed_id_new_photos': 1097966}, 'aile-avant': {}}, 'crop_type': 'bib', 'margin_type': 'margin_relative', 'margin_value': [0.5, 0.1, 0.5, 0.1], 'min_score': 0.3} list_filenames in step crop : ['temp/1758812733_3157952_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg', 'temp/1758812733_3157952_950003813_e28be02dfcce79cce594a390a9911a0a.jpg', 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg', 'temp/1758812733_3157952_950003696_11e3a77b72af4b332d366d98984039c7.jpg', 'temp/1758812733_3157952_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg', 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg'] Loading chi in step crop with photo_hashtag_type : 757 Loading chi in step crop for subpids : 6 ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 950003838,950003813,950003812,950003696,950003695,926687666) and `type` in (757) Loaded 32 chid ids of type : 757 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1655713604,1655713607,1655713608,1655713612,1655713617,1655713619,1655713621,1655713623,1655713624,1655713628,1655713630,1655713631,1655713632,1655713634,1655713635,1655713639,1655713644,1655713646,1655713647,1655713648,1655713650,1655713651,1655713652,1655713655,1655713658,1655713659,1655713660,1655713662,1655713695,1655713696,1655713700,1655713701) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1655713604,1655713607,1655713608,1655713612,1655713617,1655713619,1655713621,1655713623,1655713624,1655713628,1655713630,1655713631,1655713632,1655713634,1655713635,1655713639,1655713644,1655713646,1655713647,1655713648,1655713650,1655713651,1655713652,1655713655,1655713658,1655713659,1655713660,1655713662,1655713695,1655713696,1655713700,1655713701) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1655713604,1655713607,1655713608,1655713612,1655713617,1655713619,1655713621,1655713623,1655713624,1655713628,1655713630,1655713631,1655713632,1655713634,1655713635,1655713639,1655713644,1655713646,1655713647,1655713648,1655713650,1655713651,1655713652,1655713655,1655713658,1655713659,1655713660,1655713662,1655713695,1655713696,1655713700,1655713701) select photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type, id from MTRPhoto.photo_sub_photos where photo_id in ( 950003838,950003813,950003812,950003696,950003695,926687666) select sub_photo_id, crop_hashtag_id from MTRPhoto.crop_sub_photo_ids where sub_photo_id in (971020109,971021726,971022383,1071808962,1071808969,1071808957,1071808960,1071808966) map_pid_crop from SQL : ['[]', '[, , , , , , , , , , , ]', '[, , , , , , , , , , , , , ]', '[]', '[, , , ]'] begin to crop the class : phare param for this class : {'margin_type': 'margin', 'margin_value': 300, 'feed_id_new_photos': 1097966} filtre for class : phare hashtag_id of this class : 492624020 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 757 and photo_id in (950003838,950003813,950003812,950003696,950003695,926687666) and hashtag_id = 492624020) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [1655713621] chi_id interessant : [1655713621, 1655713648] chi_id interessant : [1655713621, 1655713648, 1655713647] WARNING : margin is only used for type bib ! type of cropped photo chosen : bib we resize croppped photo by 1 on x axis and by 1 on y axis new_file_path_bib_crop : temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg new_file_path_bib_crop : temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg new_file_path_bib_crop : temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg map_result returned by crop_photo_return_map_crop : length : 3 map_result after crop : {1655713647: {'crop': 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg', 'photo_id': 950003812, 'sub_photo_id': 1071808957, 'coordonates': (318, 489, 264, 310), 'sub_photo_infos': (18, 614, 0, 480, 1, 1), 'same_chi': True}, 1655713648: {'crop': 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg', 'photo_id': 950003812, 'sub_photo_id': 1071808960, 'coordonates': (261, 408, 234, 331), 'sub_photo_infos': (0, 614, 0, 480, 1, 1), 'same_chi': True}, 1655713621: {'crop': 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg', 'photo_id': 926687666, 'sub_photo_id': 1071808962, 'coordonates': (326, 477, 251, 312), 'sub_photo_infos': (26, 640, 0, 480, 1, 1), 'same_chi': True}} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {1071808957: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg', (318, 489, 264, 310)], 1071808960: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg', (261, 408, 234, 331)], 1071808962: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg', (326, 477, 251, 312)]} we have finished the crop for the class : phare begin to crop the class : aile-avant param for this class : {} filtre for class : aile-avant hashtag_id of this class : 2106233860 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 757 and photo_id in (950003838,950003813,950003812,950003696,950003695,926687666) and hashtag_id = 2106233860) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [1655713607] chi_id interessant : [1655713607, 1655713634] WARNING : margin is only used for type bib ! type of cropped photo chosen : bib we resize croppped photo by 1 on x axis and by 1 on y axis new_file_path_bib_crop : temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg now we use margin_relative for the photo_id : 950003812 new_file_path_bib_crop : temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg now we use margin_relative for the photo_id : 926687666 map_result returned by crop_photo_return_map_crop : length : 2 map_result after crop : {1655713634: {'crop': 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg', 'photo_id': 950003812, 'sub_photo_id': 1071808966, 'coordonates': (133, 305, 146, 344), 'sub_photo_infos': (34, 324, 60, 361, 1, 1), 'same_chi': True}, 1655713607: {'crop': 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg', 'photo_id': 926687666, 'sub_photo_id': 1071808969, 'coordonates': (161, 330, 149, 343), 'sub_photo_infos': (64, 349, 65, 359, 1, 1), 'same_chi': True}} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {1071808966: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg', (133, 305, 146, 344)], 1071808969: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg', (161, 330, 149, 343)]} we have finished the crop for the class : aile-avant map of total cropped photos with some data : {1071808957: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg', (318, 489, 264, 310)], 1071808960: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg', (261, 408, 234, 331)], 1071808962: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg', (326, 477, 251, 312)], 1071808966: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg', (133, 305, 146, 344)], 1071808969: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg', (161, 330, 149, 343)]} After datou_step_exec type output : time spend for datou_step_exec : 0.7704861164093018 time spend to save output : 8.487701416015625e-05 total time spend for step 2 : 0.7705709934234619 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {1071808957: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg', (318, 489, 264, 310)], 1071808960: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg', (261, 408, 234, 331)], 1071808962: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg', (326, 477, 251, 312)], 1071808966: [950003812, 'temp/1758812733_3157952_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg', (133, 305, 146, 344)], 1071808969: [926687666, 'temp/1758812733_3157952_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg', (161, 330, 149, 343)]} ############################### TEST image_blanchir ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=1818 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=1818 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 1818 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=1818 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : image_blanchir list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (990111206) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 990111206 download finish for photo 990111206 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.19866013526916504 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:image_blanchir Thu Sep 25 17:05:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png': 990111206} map_photo_id_path_extension : {990111206: {'path': 'temp/1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png', 'extension': 'png'}} map_subphoto_mainphoto : {} inside step blanchir_image feed_id_new_photos:27233655 treat image : temp/1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png blanchir func in upload media Upload medias : ['temp/1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png'] : url : https://www.fotonower.com/api/v1/secured/photo/upload?token=78d09a0790ec6ecbf119343125a81fdc&datou=0 temp/1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png after data_to_send, before sending request after request b'{"photo_ids":["1386160021"],"photo_id":"1386160021","photo_detail":[{"mtr_user_id":440,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/dc6cf683682fd534dfb1486553ca088a.png","text":"TemporaryFile(/tmp/multipartBody1269382745158430442asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812742067,"filename":"1758812738_3157952_990111206_7ca22c7e68dd0a10509c7987af0cf549.png","height":0,"width":0}],"map_files_photo_id":{"file0":"1386160021"},"map_files_photo_id_array":[{"photo_id":"file0","filename":"1386160021"}],"hashtags":[],"portfolio_id":"27233655","result":[],"list_datou_current":[]}' Result OK ! After datou_step_exec type output : time spend for datou_step_exec : 9.401524305343628 time spend to save output : 1.7881393432617188e-05 total time spend for step 1 : 9.40154218673706 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True sauvegarde pour la step blanchir_image begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [[1818, 0, 990111206, 1, 1, 1, None, 1, None]] time used for this insertion : 0.014089584350585938 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : [(990111206, '1386160021', 0, 300, 0, 381, 1, 1, 'blanc')] [(990111206, '1386160021', 0, 300, 0, 381, 1, 1, 'blanc')] ############################### TEST darker_image ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2085 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2085 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2085 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2085 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : darker_image list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (2077915) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (2077915) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 989962950, 'portfolio_id': 2077915}] map_portfolio_id_photo_id: {2077915: [989962950]} ##### Call download_photos : nb_thread : 5 begin to download photo : 989962950 download finish for photo 989962950 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.14263916015625 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:darker_image Thu Sep 25 17:05:48 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg': 989962950} map_photo_id_path_extension : {989962950: {'path': 'temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} dans la step darker batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 989962950) and `type` in (2228) Loaded 7 chid ids of type : 2228 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) +WARNING : Unexpected points, we should remove this data for chi_id : 1753484977, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484978, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484979, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484980, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484981, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484982, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484983, for now we just ignore these empty polygon points SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) treat image : temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg in upload media Upload medias : ['temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0badarker.jpg'] : url : https://www.fotonower.com/api/v1/secured/photo/upload?token=78d09a0790ec6ecbf119343125a81fdc&datou=0 temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0badarker.jpg after data_to_send, before sending request after request b'\n\n400 Bad Request\n\n

Bad Request

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Your browser sent a request that this server could not understand.
\n

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Apache/2.4.41 (Ubuntu) Server at www.fotonower.com Port 443
\n\n' 400 ERROR in datou_step_exec, will save and exit ! 'temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0badarker.jpg' File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2590, in datou_step_exec return pre_process.datou_step_exec_darker_image(param, json_param, args, context, map_info, verbose) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py", line 1624, in datou_step_exec_darker_image chi_obj.photo_id=int(map_result_insert_aux[new_path]) [989962950] map_info['map_portfolio_photo'] : {2077915: [989962950]} final : True mtd_id 2085 list_pids : [989962950] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('2085', '2077915', '989962950', '[>, , , , , "\'temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0badarker.jpg\'"]', '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.013671875 save_final ERROR in last step darker_image, 'temp/1758812748_3157952_989962950_4d2e56be59e275c3d57b085a836be0badarker.jpg' time spend for datou_step_exec : 0.6422374248504639 time spend to save output : 0.019115924835205078 total time spend for step 0 : 0.661353349685669 Useless call to update_current_state caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True ouput is None saving photo_ids in datou_result begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('2085', '2077915', '989962950', '0', '0', '0', '492764225', '0', None)] time used for this insertion : 0.01185750961303711 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None None 'NoneType' object is not subscriptable ERROR darker_image FAILED ############################### TEST img_aug ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2041 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2041 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2041 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2041 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : data_aug list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (2077915) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (2077915) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 989962950, 'portfolio_id': 2077915}] map_portfolio_id_photo_id: {2077915: [989962950]} ##### Call download_photos : nb_thread : 5 begin to download photo : 989962950 download finish for photo 989962950 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.15941333770751953 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:data_aug Thu Sep 25 17:05:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812749_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg': 989962950} map_photo_id_path_extension : {989962950: {'path': 'temp/1758812749_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} numpy.version est ancienne, on utilise l'ancien bit generator numpy.version est ancienne, on utilise l'ancien bit generator batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 989962950) and `type` in (2228) Loaded 7 chid ids of type : 2228 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) +WARNING : Unexpected points, we should remove this data for chi_id : 1753484977, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484978, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484979, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484980, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484981, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484982, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484983, for now we just ignore these empty polygon points SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1753484977,1753484978,1753484979,1753484980,1753484981,1753484982,1753484983) on traite des points in upload media Upload medias : ['temp/1758812749_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba_aug.jpg'] : url : https://www.fotonower.com/api/v1/secured/photo/upload?token=7ad776945df9e5335881f03fafdabb27&datou=0 temp/1758812749_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba_aug.jpg after data_to_send, before sending request after request b'{"photo_ids":["1386160127"],"photo_id":"1386160127","photo_detail":[{"mtr_user_id":0,"url":"https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/9/25/4c95282dddbb08b94eb0d8a60c86f6e8.jpg","text":"TemporaryFile(/tmp/multipartBody6789295875383316813asTemporaryFile)","latitude":0.0,"longitude":0.0,"uploaded_at":1758812749975,"filename":"1758812749_3157952_989962950_4d2e56be59e275c3d57b085a836be0ba_aug.jpg","height":0,"width":0}],"map_files_photo_id":{"file0":"1386160127"},"map_files_photo_id_array":[{"photo_id":"file0","filename":"1386160127"}],"hashtags":[],"portfolio_id":"2095671","result":[],"list_datou_current":[]}' Result OK ! insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 7 chid ids of type : 2260 ERROR missing MTRPhoto.crop_hashtag_ids : 492774966 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492774966 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492725882 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492725882 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1386160127 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1386160127 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! photo_uploade augmentation faite pour la photo : 989962950 After datou_step_exec type output : time spend for datou_step_exec : 9.225278377532959 time spend to save output : 2.7894973754882812e-05 total time spend for step 1 : 9.225306272506714 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True sauvegarde pour la step blanchir_image begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [[2041, 0, 989962950, 1, 1, 1, None, 1, None]] time used for this insertion : 0.011944055557250977 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : [(989962950, 1386160127, 0, 1431, 0, 897, 1, 1, 'img_aug')] [(989962950, 1386160127, 0, 1431, 0, 897, 1, 1, 'img_aug')] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1386160127) and `type` in (2260) Loaded 7 chid ids of type : 2260 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975220835,3975220836,3975220834,3975220832,3975220833,3975220830,3975220831) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975220835,3975220836,3975220834,3975220832,3975220833,3975220830,3975220831) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975220835,3975220836,3975220834,3975220832,3975220833,3975220830,3975220831) ############################### TEST rubbia ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3789 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3789 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3789 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3789 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4599398) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4599398) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1049318362, 'portfolio_id': 4599398}, {'photo_id': 1049318360, 'portfolio_id': 4599398}, {'photo_id': 1049318358, 'portfolio_id': 4599398}, {'photo_id': 1049318356, 'portfolio_id': 4599398}, {'photo_id': 1049318342, 'portfolio_id': 4599398}, {'photo_id': 1049318339, 'portfolio_id': 4599398}, {'photo_id': 1049318337, 'portfolio_id': 4599398}, {'photo_id': 1049318311, 'portfolio_id': 4599398}, {'photo_id': 1049318310, 'portfolio_id': 4599398}, {'photo_id': 1049318309, 'portfolio_id': 4599398}, {'photo_id': 1049318294, 'portfolio_id': 4599398}, {'photo_id': 1049318293, 'portfolio_id': 4599398}, {'photo_id': 1049318291, 'portfolio_id': 4599398}, {'photo_id': 1049318289, 'portfolio_id': 4599398}, {'photo_id': 1049318288, 'portfolio_id': 4599398}, {'photo_id': 1049318287, 'portfolio_id': 4599398}, {'photo_id': 1049318279, 'portfolio_id': 4599398}, {'photo_id': 1049318276, 'portfolio_id': 4599398}, {'photo_id': 1049318273, 'portfolio_id': 4599398}, {'photo_id': 1049318271, 'portfolio_id': 4599398}, {'photo_id': 1049318268, 'portfolio_id': 4599398}, {'photo_id': 1049318265, 'portfolio_id': 4599398}, {'photo_id': 1049318260, 'portfolio_id': 4599398}, {'photo_id': 1049318257, 'portfolio_id': 4599398}, {'photo_id': 1049318253, 'portfolio_id': 4599398}, {'photo_id': 1049318250, 'portfolio_id': 4599398}, {'photo_id': 1049318247, 'portfolio_id': 4599398}, {'photo_id': 1049318246, 'portfolio_id': 4599398}, {'photo_id': 1049318222, 'portfolio_id': 4599398}, {'photo_id': 1049318219, 'portfolio_id': 4599398}, {'photo_id': 1049318216, 'portfolio_id': 4599398}, {'photo_id': 1049318214, 'portfolio_id': 4599398}, {'photo_id': 1049318213, 'portfolio_id': 4599398}, {'photo_id': 1049318212, 'portfolio_id': 4599398}, {'photo_id': 1049317554, 'portfolio_id': 4599398}, {'photo_id': 1049317551, 'portfolio_id': 4599398}, {'photo_id': 1049317549, 'portfolio_id': 4599398}, {'photo_id': 1049317546, 'portfolio_id': 4599398}, {'photo_id': 1049317542, 'portfolio_id': 4599398}, {'photo_id': 1049317536, 'portfolio_id': 4599398}, {'photo_id': 1049317526, 'portfolio_id': 4599398}, {'photo_id': 1049317525, 'portfolio_id': 4599398}, {'photo_id': 1049317524, 'portfolio_id': 4599398}, {'photo_id': 1049317522, 'portfolio_id': 4599398}, {'photo_id': 1049317520, 'portfolio_id': 4599398}, {'photo_id': 1049317517, 'portfolio_id': 4599398}, {'photo_id': 1049317497, 'portfolio_id': 4599398}, {'photo_id': 1049317493, 'portfolio_id': 4599398}, {'photo_id': 1049317491, 'portfolio_id': 4599398}, {'photo_id': 1049317489, 'portfolio_id': 4599398}, {'photo_id': 1049317487, 'portfolio_id': 4599398}, {'photo_id': 1049317485, 'portfolio_id': 4599398}, {'photo_id': 1049317468, 'portfolio_id': 4599398}, {'photo_id': 1049317461, 'portfolio_id': 4599398}, {'photo_id': 1049317457, 'portfolio_id': 4599398}, {'photo_id': 1049317453, 'portfolio_id': 4599398}, {'photo_id': 1049317444, 'portfolio_id': 4599398}, {'photo_id': 1049317440, 'portfolio_id': 4599398}, {'photo_id': 1049317359, 'portfolio_id': 4599398}, {'photo_id': 1049317333, 'portfolio_id': 4599398}, {'photo_id': 1049317282, 'portfolio_id': 4599398}, {'photo_id': 1049317225, 'portfolio_id': 4599398}, {'photo_id': 1049317210, 'portfolio_id': 4599398}, {'photo_id': 1049317197, 'portfolio_id': 4599398}, {'photo_id': 1049316790, 'portfolio_id': 4599398}, {'photo_id': 1049316785, 'portfolio_id': 4599398}, {'photo_id': 1049316782, 'portfolio_id': 4599398}, {'photo_id': 1049316778, 'portfolio_id': 4599398}, {'photo_id': 1049316752, 'portfolio_id': 4599398}, {'photo_id': 1049316749, 'portfolio_id': 4599398}, {'photo_id': 1049316610, 'portfolio_id': 4599398}, {'photo_id': 1049316600, 'portfolio_id': 4599398}, {'photo_id': 1049316597, 'portfolio_id': 4599398}, {'photo_id': 1049316594, 'portfolio_id': 4599398}, {'photo_id': 1049316588, 'portfolio_id': 4599398}, {'photo_id': 1049316582, 'portfolio_id': 4599398}, {'photo_id': 1049316545, 'portfolio_id': 4599398}, {'photo_id': 1049316543, 'portfolio_id': 4599398}, {'photo_id': 1049316540, 'portfolio_id': 4599398}, {'photo_id': 1049316537, 'portfolio_id': 4599398}, {'photo_id': 1049316534, 'portfolio_id': 4599398}, {'photo_id': 1049316520, 'portfolio_id': 4599398}, {'photo_id': 1049316338, 'portfolio_id': 4599398}, {'photo_id': 1049316336, 'portfolio_id': 4599398}, {'photo_id': 1049316332, 'portfolio_id': 4599398}, {'photo_id': 1049316331, 'portfolio_id': 4599398}, {'photo_id': 1049316257, 'portfolio_id': 4599398}, {'photo_id': 1049316255, 'portfolio_id': 4599398}, {'photo_id': 1049316222, 'portfolio_id': 4599398}, {'photo_id': 1049316216, 'portfolio_id': 4599398}, {'photo_id': 1049316214, 'portfolio_id': 4599398}, {'photo_id': 1049316212, 'portfolio_id': 4599398}, {'photo_id': 1049316210, 'portfolio_id': 4599398}, {'photo_id': 1049316209, 'portfolio_id': 4599398}, {'photo_id': 1049313025, 'portfolio_id': 4599398}, {'photo_id': 1049312984, 'portfolio_id': 4599398}, {'photo_id': 1049312803, 'portfolio_id': 4599398}, {'photo_id': 1049312588, 'portfolio_id': 4599398}, {'photo_id': 1049312585, 'portfolio_id': 4599398}, {'photo_id': 1049312583, 'portfolio_id': 4599398}, {'photo_id': 1049312579, 'portfolio_id': 4599398}, {'photo_id': 1049312574, 'portfolio_id': 4599398}, {'photo_id': 1049312573, 'portfolio_id': 4599398}, {'photo_id': 1049312571, 'portfolio_id': 4599398}, {'photo_id': 1049312568, 'portfolio_id': 4599398}, {'photo_id': 1049312566, 'portfolio_id': 4599398}, {'photo_id': 1049312562, 'portfolio_id': 4599398}, {'photo_id': 1049312556, 'portfolio_id': 4599398}, {'photo_id': 1049312508, 'portfolio_id': 4599398}, {'photo_id': 1049312489, 'portfolio_id': 4599398}, {'photo_id': 1049312488, 'portfolio_id': 4599398}, {'photo_id': 1049312487, 'portfolio_id': 4599398}, {'photo_id': 1049312485, 'portfolio_id': 4599398}, {'photo_id': 1049312484, 'portfolio_id': 4599398}, {'photo_id': 1049312464, 'portfolio_id': 4599398}, {'photo_id': 1049312463, 'portfolio_id': 4599398}, {'photo_id': 1049312462, 'portfolio_id': 4599398}, {'photo_id': 1049312461, 'portfolio_id': 4599398}, {'photo_id': 1049312460, 'portfolio_id': 4599398}, {'photo_id': 1049312449, 'portfolio_id': 4599398}, {'photo_id': 1049312445, 'portfolio_id': 4599398}, {'photo_id': 1049312444, 'portfolio_id': 4599398}, {'photo_id': 1049312442, 'portfolio_id': 4599398}, {'photo_id': 1049312440, 'portfolio_id': 4599398}, {'photo_id': 1049312438, 'portfolio_id': 4599398}, {'photo_id': 1049312429, 'portfolio_id': 4599398}, {'photo_id': 1049312426, 'portfolio_id': 4599398}, {'photo_id': 1049312424, 'portfolio_id': 4599398}, {'photo_id': 1049312422, 'portfolio_id': 4599398}, {'photo_id': 1049312420, 'portfolio_id': 4599398}, {'photo_id': 1049312409, 'portfolio_id': 4599398}, {'photo_id': 1049312406, 'portfolio_id': 4599398}, {'photo_id': 1049312404, 'portfolio_id': 4599398}, {'photo_id': 1049312363, 'portfolio_id': 4599398}, {'photo_id': 1049312208, 'portfolio_id': 4599398}, {'photo_id': 1049311964, 'portfolio_id': 4599398}, {'photo_id': 1049311963, 'portfolio_id': 4599398}, {'photo_id': 1049311962, 'portfolio_id': 4599398}, {'photo_id': 1049311961, 'portfolio_id': 4599398}, {'photo_id': 1049311960, 'portfolio_id': 4599398}, {'photo_id': 1049311943, 'portfolio_id': 4599398}, {'photo_id': 1049311938, 'portfolio_id': 4599398}, {'photo_id': 1049311937, 'portfolio_id': 4599398}, {'photo_id': 1049311935, 'portfolio_id': 4599398}, {'photo_id': 1049311934, 'portfolio_id': 4599398}, {'photo_id': 1049311932, 'portfolio_id': 4599398}, {'photo_id': 1049311795, 'portfolio_id': 4599398}, {'photo_id': 1049311793, 'portfolio_id': 4599398}, {'photo_id': 1049311791, 'portfolio_id': 4599398}, {'photo_id': 1049311771, 'portfolio_id': 4599398}, {'photo_id': 1049311767, 'portfolio_id': 4599398}, {'photo_id': 1049311267, 'portfolio_id': 4599398}, {'photo_id': 1049311266, 'portfolio_id': 4599398}, {'photo_id': 1049311263, 'portfolio_id': 4599398}, {'photo_id': 1049311252, 'portfolio_id': 4599398}, {'photo_id': 1049311199, 'portfolio_id': 4599398}, {'photo_id': 1049311136, 'portfolio_id': 4599398}, {'photo_id': 1049311073, 'portfolio_id': 4599398}, {'photo_id': 1049311009, 'portfolio_id': 4599398}, {'photo_id': 1049311006, 'portfolio_id': 4599398}, {'photo_id': 1049310994, 'portfolio_id': 4599398}, {'photo_id': 1049310992, 'portfolio_id': 4599398}, {'photo_id': 1049310991, 'portfolio_id': 4599398}, {'photo_id': 1049310984, 'portfolio_id': 4599398}, {'photo_id': 1049310982, 'portfolio_id': 4599398}, {'photo_id': 1049310981, 'portfolio_id': 4599398}, {'photo_id': 1049310919, 'portfolio_id': 4599398}, {'photo_id': 1049310914, 'portfolio_id': 4599398}, {'photo_id': 1049310911, 'portfolio_id': 4599398}, {'photo_id': 1049310909, 'portfolio_id': 4599398}, {'photo_id': 1049310907, 'portfolio_id': 4599398}, {'photo_id': 1049310905, 'portfolio_id': 4599398}, {'photo_id': 1049310165, 'portfolio_id': 4599398}, {'photo_id': 1049310162, 'portfolio_id': 4599398}, {'photo_id': 1049310159, 'portfolio_id': 4599398}, {'photo_id': 1049310145, 'portfolio_id': 4599398}, {'photo_id': 1049310141, 'portfolio_id': 4599398}, {'photo_id': 1049310139, 'portfolio_id': 4599398}, {'photo_id': 1049310138, 'portfolio_id': 4599398}, {'photo_id': 1049310134, 'portfolio_id': 4599398}, {'photo_id': 1049310132, 'portfolio_id': 4599398}, {'photo_id': 1049309737, 'portfolio_id': 4599398}, {'photo_id': 1049309734, 'portfolio_id': 4599398}, {'photo_id': 1049309732, 'portfolio_id': 4599398}, {'photo_id': 1049309706, 'portfolio_id': 4599398}, {'photo_id': 1049309703, 'portfolio_id': 4599398}, {'photo_id': 1049309701, 'portfolio_id': 4599398}, {'photo_id': 1049309686, 'portfolio_id': 4599398}, {'photo_id': 1049309681, 'portfolio_id': 4599398}, {'photo_id': 1049309677, 'portfolio_id': 4599398}, {'photo_id': 1049309675, 'portfolio_id': 4599398}, {'photo_id': 1049309672, 'portfolio_id': 4599398}, {'photo_id': 1049309670, 'portfolio_id': 4599398}, {'photo_id': 1049309658, 'portfolio_id': 4599398}, {'photo_id': 1049309657, 'portfolio_id': 4599398}, {'photo_id': 1049309656, 'portfolio_id': 4599398}, {'photo_id': 1049309655, 'portfolio_id': 4599398}, {'photo_id': 1049309653, 'portfolio_id': 4599398}, {'photo_id': 1049309651, 'portfolio_id': 4599398}, {'photo_id': 1049309605, 'portfolio_id': 4599398}, {'photo_id': 1049309603, 'portfolio_id': 4599398}, {'photo_id': 1049309599, 'portfolio_id': 4599398}, {'photo_id': 1049309597, 'portfolio_id': 4599398}, {'photo_id': 1049309595, 'portfolio_id': 4599398}, {'photo_id': 1049309592, 'portfolio_id': 4599398}, {'photo_id': 1049309385, 'portfolio_id': 4599398}, {'photo_id': 1049309383, 'portfolio_id': 4599398}, {'photo_id': 1049309382, 'portfolio_id': 4599398}, {'photo_id': 1049309381, 'portfolio_id': 4599398}, {'photo_id': 1049309380, 'portfolio_id': 4599398}, {'photo_id': 1049309379, 'portfolio_id': 4599398}, {'photo_id': 1049309345, 'portfolio_id': 4599398}, {'photo_id': 1049308384, 'portfolio_id': 4599398}, {'photo_id': 1049308381, 'portfolio_id': 4599398}, {'photo_id': 1049308376, 'portfolio_id': 4599398}, {'photo_id': 1049308280, 'portfolio_id': 4599398}, {'photo_id': 1049308276, 'portfolio_id': 4599398}, {'photo_id': 1049308275, 'portfolio_id': 4599398}, {'photo_id': 1049308235, 'portfolio_id': 4599398}, {'photo_id': 1049307693, 'portfolio_id': 4599398}, {'photo_id': 1049306823, 'portfolio_id': 4599398}, {'photo_id': 1049306804, 'portfolio_id': 4599398}, {'photo_id': 1049306792, 'portfolio_id': 4599398}, {'photo_id': 1049306791, 'portfolio_id': 4599398}, {'photo_id': 1049306635, 'portfolio_id': 4599398}, {'photo_id': 1049306205, 'portfolio_id': 4599398}, {'photo_id': 1049304810, 'portfolio_id': 4599398}, {'photo_id': 1049303925, 'portfolio_id': 4599398}, {'photo_id': 1049296996, 'portfolio_id': 4599398}, {'photo_id': 1049296121, 'portfolio_id': 4599398}, {'photo_id': 1049294990, 'portfolio_id': 4599398}, {'photo_id': 1049293230, 'portfolio_id': 4599398}] map_portfolio_id_photo_id: {4599398: [1049318362, 1049318360, 1049318358, 1049318356, 1049318342, 1049318339, 1049318337, 1049318311, 1049318310, 1049318309, 1049318294, 1049318293, 1049318291, 1049318289, 1049318288, 1049318287, 1049318279, 1049318276, 1049318273, 1049318271, 1049318268, 1049318265, 1049318260, 1049318257, 1049318253, 1049318250, 1049318247, 1049318246, 1049318222, 1049318219, 1049318216, 1049318214, 1049318213, 1049318212, 1049317554, 1049317551, 1049317549, 1049317546, 1049317542, 1049317536, 1049317526, 1049317525, 1049317524, 1049317522, 1049317520, 1049317517, 1049317497, 1049317493, 1049317491, 1049317489, 1049317487, 1049317485, 1049317468, 1049317461, 1049317457, 1049317453, 1049317444, 1049317440, 1049317359, 1049317333, 1049317282, 1049317225, 1049317210, 1049317197, 1049316790, 1049316785, 1049316782, 1049316778, 1049316752, 1049316749, 1049316610, 1049316600, 1049316597, 1049316594, 1049316588, 1049316582, 1049316545, 1049316543, 1049316540, 1049316537, 1049316534, 1049316520, 1049316338, 1049316336, 1049316332, 1049316331, 1049316257, 1049316255, 1049316222, 1049316216, 1049316214, 1049316212, 1049316210, 1049316209, 1049313025, 1049312984, 1049312803, 1049312588, 1049312585, 1049312583, 1049312579, 1049312574, 1049312573, 1049312571, 1049312568, 1049312566, 1049312562, 1049312556, 1049312508, 1049312489, 1049312488, 1049312487, 1049312485, 1049312484, 1049312464, 1049312463, 1049312462, 1049312461, 1049312460, 1049312449, 1049312445, 1049312444, 1049312442, 1049312440, 1049312438, 1049312429, 1049312426, 1049312424, 1049312422, 1049312420, 1049312409, 1049312406, 1049312404, 1049312363, 1049312208, 1049311964, 1049311963, 1049311962, 1049311961, 1049311960, 1049311943, 1049311938, 1049311937, 1049311935, 1049311934, 1049311932, 1049311795, 1049311793, 1049311791, 1049311771, 1049311767, 1049311267, 1049311266, 1049311263, 1049311252, 1049311199, 1049311136, 1049311073, 1049311009, 1049311006, 1049310994, 1049310992, 1049310991, 1049310984, 1049310982, 1049310981, 1049310919, 1049310914, 1049310911, 1049310909, 1049310907, 1049310905, 1049310165, 1049310162, 1049310159, 1049310145, 1049310141, 1049310139, 1049310138, 1049310134, 1049310132, 1049309737, 1049309734, 1049309732, 1049309706, 1049309703, 1049309701, 1049309686, 1049309681, 1049309677, 1049309675, 1049309672, 1049309670, 1049309658, 1049309657, 1049309656, 1049309655, 1049309653, 1049309651, 1049309605, 1049309603, 1049309599, 1049309597, 1049309595, 1049309592, 1049309385, 1049309383, 1049309382, 1049309381, 1049309380, 1049309379, 1049309345, 1049308384, 1049308381, 1049308376, 1049308280, 1049308276, 1049308275, 1049308235, 1049307693, 1049306823, 1049306804, 1049306792, 1049306791, 1049306635, 1049306205, 1049304810, 1049303925, 1049296996, 1049296121, 1049294990, 1049293230]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.031710147857666016 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Thu Sep 25 17:05:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} begin split time score 2022-04-13 10:29:59 0 SELECT app_name, token FROM MTRUser.mtr_app_api_token WHERE mtr_user_id=739 AND app_name="token_split_time_score" AND expire_at > NOW() TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] select SUBSTRING(ph.text,16,2) as h, count(*) from MTRUser.mtr_portfolio_photos mpp inner join MTRBack.view_photos_with_urls_250912 ph on mpp.mtr_photo_id = ph.photo_id where mpp.mtr_portfolio_id = 4599398 group by h (('05', 1), ('07', 16), (None, 115), ('08', 43), ('09', 24), ('10', 33)) SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4599398 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4599398) AND cps.thcl in (861) order by cps.score desc LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4599398) AND cps.thcl in (758) order by cps.score desc LIMIT 0, 100000 ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 188, 2: 36, 3: 8} ERROR in datou_step_exec, will save and exit ! 'NoneType' object has no attribute 'startswith' File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2523, in datou_step_exec return lib_process.datou_step_split_time_score(param, json_param, args, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 2295, in datou_step_split_time_score one_result = split_port_in_batch_balle( File "/home/admin/workarea/git/Velours/python/misc/split_time_score.py", line 336, in split_port_in_batch_balle meta_photos, scores, densite, result_taggue_densite = load_data_split_time_score(int(mtr_portfolio), thcl, thcl_volume, context, limit, File "/home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py", line 2604, in load_data_split_time_score current_datetime, mean_pixel = parse_text_to_date(meta_photos[0]["text"]) File "/home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py", line 74, in parse_text_to_date if text.startswith("image_"): [1049318362, 1049318360, 1049318358, 1049318356, 1049318342, 1049318339, 1049318337, 1049318311, 1049318310, 1049318309, 1049318294, 1049318293, 1049318291, 1049318289, 1049318288, 1049318287, 1049318279, 1049318276, 1049318273, 1049318271, 1049318268, 1049318265, 1049318260, 1049318257, 1049318253, 1049318250, 1049318247, 1049318246, 1049318222, 1049318219, 1049318216, 1049318214, 1049318213, 1049318212, 1049317554, 1049317551, 1049317549, 1049317546, 1049317542, 1049317536, 1049317526, 1049317525, 1049317524, 1049317522, 1049317520, 1049317517, 1049317497, 1049317493, 1049317491, 1049317489, 1049317487, 1049317485, 1049317468, 1049317461, 1049317457, 1049317453, 1049317444, 1049317440, 1049317359, 1049317333, 1049317282, 1049317225, 1049317210, 1049317197, 1049316790, 1049316785, 1049316782, 1049316778, 1049316752, 1049316749, 1049316610, 1049316600, 1049316597, 1049316594, 1049316588, 1049316582, 1049316545, 1049316543, 1049316540, 1049316537, 1049316534, 1049316520, 1049316338, 1049316336, 1049316332, 1049316331, 1049316257, 1049316255, 1049316222, 1049316216, 1049316214, 1049316212, 1049316210, 1049316209, 1049313025, 1049312984, 1049312803, 1049312588, 1049312585, 1049312583, 1049312579, 1049312574, 1049312573, 1049312571, 1049312568, 1049312566, 1049312562, 1049312556, 1049312508, 1049312489, 1049312488, 1049312487, 1049312485, 1049312484, 1049312464, 1049312463, 1049312462, 1049312461, 1049312460, 1049312449, 1049312445, 1049312444, 1049312442, 1049312440, 1049312438, 1049312429, 1049312426, 1049312424, 1049312422, 1049312420, 1049312409, 1049312406, 1049312404, 1049312363, 1049312208, 1049311964, 1049311963, 1049311962, 1049311961, 1049311960, 1049311943, 1049311938, 1049311937, 1049311935, 1049311934, 1049311932, 1049311795, 1049311793, 1049311791, 1049311771, 1049311767, 1049311267, 1049311266, 1049311263, 1049311252, 1049311199, 1049311136, 1049311073, 1049311009, 1049311006, 1049310994, 1049310992, 1049310991, 1049310984, 1049310982, 1049310981, 1049310919, 1049310914, 1049310911, 1049310909, 1049310907, 1049310905, 1049310165, 1049310162, 1049310159, 1049310145, 1049310141, 1049310139, 1049310138, 1049310134, 1049310132, 1049309737, 1049309734, 1049309732, 1049309706, 1049309703, 1049309701, 1049309686, 1049309681, 1049309677, 1049309675, 1049309672, 1049309670, 1049309658, 1049309657, 1049309656, 1049309655, 1049309653, 1049309651, 1049309605, 1049309603, 1049309599, 1049309597, 1049309595, 1049309592, 1049309385, 1049309383, 1049309382, 1049309381, 1049309380, 1049309379, 1049309345, 1049308384, 1049308381, 1049308376, 1049308280, 1049308276, 1049308275, 1049308235, 1049307693, 1049306823, 1049306804, 1049306792, 1049306791, 1049306635, 1049306205, 1049304810, 1049303925, 1049296996, 1049296121, 1049294990, 1049293230] map_info['map_portfolio_photo'] : {4599398: [1049318362, 1049318360, 1049318358, 1049318356, 1049318342, 1049318339, 1049318337, 1049318311, 1049318310, 1049318309, 1049318294, 1049318293, 1049318291, 1049318289, 1049318288, 1049318287, 1049318279, 1049318276, 1049318273, 1049318271, 1049318268, 1049318265, 1049318260, 1049318257, 1049318253, 1049318250, 1049318247, 1049318246, 1049318222, 1049318219, 1049318216, 1049318214, 1049318213, 1049318212, 1049317554, 1049317551, 1049317549, 1049317546, 1049317542, 1049317536, 1049317526, 1049317525, 1049317524, 1049317522, 1049317520, 1049317517, 1049317497, 1049317493, 1049317491, 1049317489, 1049317487, 1049317485, 1049317468, 1049317461, 1049317457, 1049317453, 1049317444, 1049317440, 1049317359, 1049317333, 1049317282, 1049317225, 1049317210, 1049317197, 1049316790, 1049316785, 1049316782, 1049316778, 1049316752, 1049316749, 1049316610, 1049316600, 1049316597, 1049316594, 1049316588, 1049316582, 1049316545, 1049316543, 1049316540, 1049316537, 1049316534, 1049316520, 1049316338, 1049316336, 1049316332, 1049316331, 1049316257, 1049316255, 1049316222, 1049316216, 1049316214, 1049316212, 1049316210, 1049316209, 1049313025, 1049312984, 1049312803, 1049312588, 1049312585, 1049312583, 1049312579, 1049312574, 1049312573, 1049312571, 1049312568, 1049312566, 1049312562, 1049312556, 1049312508, 1049312489, 1049312488, 1049312487, 1049312485, 1049312484, 1049312464, 1049312463, 1049312462, 1049312461, 1049312460, 1049312449, 1049312445, 1049312444, 1049312442, 1049312440, 1049312438, 1049312429, 1049312426, 1049312424, 1049312422, 1049312420, 1049312409, 1049312406, 1049312404, 1049312363, 1049312208, 1049311964, 1049311963, 1049311962, 1049311961, 1049311960, 1049311943, 1049311938, 1049311937, 1049311935, 1049311934, 1049311932, 1049311795, 1049311793, 1049311791, 1049311771, 1049311767, 1049311267, 1049311266, 1049311263, 1049311252, 1049311199, 1049311136, 1049311073, 1049311009, 1049311006, 1049310994, 1049310992, 1049310991, 1049310984, 1049310982, 1049310981, 1049310919, 1049310914, 1049310911, 1049310909, 1049310907, 1049310905, 1049310165, 1049310162, 1049310159, 1049310145, 1049310141, 1049310139, 1049310138, 1049310134, 1049310132, 1049309737, 1049309734, 1049309732, 1049309706, 1049309703, 1049309701, 1049309686, 1049309681, 1049309677, 1049309675, 1049309672, 1049309670, 1049309658, 1049309657, 1049309656, 1049309655, 1049309653, 1049309651, 1049309605, 1049309603, 1049309599, 1049309597, 1049309595, 1049309592, 1049309385, 1049309383, 1049309382, 1049309381, 1049309380, 1049309379, 1049309345, 1049308384, 1049308381, 1049308376, 1049308280, 1049308276, 1049308275, 1049308235, 1049307693, 1049306823, 1049306804, 1049306792, 1049306791, 1049306635, 1049306205, 1049304810, 1049303925, 1049296996, 1049296121, 1049294990, 1049293230]} final : True mtd_id 3789 list_pids : [1049318362, 1049318360, 1049318358, 1049318356, 1049318342, 1049318339, 1049318337, 1049318311, 1049318310, 1049318309, 1049318294, 1049318293, 1049318291, 1049318289, 1049318288, 1049318287, 1049318279, 1049318276, 1049318273, 1049318271, 1049318268, 1049318265, 1049318260, 1049318257, 1049318253, 1049318250, 1049318247, 1049318246, 1049318222, 1049318219, 1049318216, 1049318214, 1049318213, 1049318212, 1049317554, 1049317551, 1049317549, 1049317546, 1049317542, 1049317536, 1049317526, 1049317525, 1049317524, 1049317522, 1049317520, 1049317517, 1049317497, 1049317493, 1049317491, 1049317489, 1049317487, 1049317485, 1049317468, 1049317461, 1049317457, 1049317453, 1049317444, 1049317440, 1049317359, 1049317333, 1049317282, 1049317225, 1049317210, 1049317197, 1049316790, 1049316785, 1049316782, 1049316778, 1049316752, 1049316749, 1049316610, 1049316600, 1049316597, 1049316594, 1049316588, 1049316582, 1049316545, 1049316543, 1049316540, 1049316537, 1049316534, 1049316520, 1049316338, 1049316336, 1049316332, 1049316331, 1049316257, 1049316255, 1049316222, 1049316216, 1049316214, 1049316212, 1049316210, 1049316209, 1049313025, 1049312984, 1049312803, 1049312588, 1049312585, 1049312583, 1049312579, 1049312574, 1049312573, 1049312571, 1049312568, 1049312566, 1049312562, 1049312556, 1049312508, 1049312489, 1049312488, 1049312487, 1049312485, 1049312484, 1049312464, 1049312463, 1049312462, 1049312461, 1049312460, 1049312449, 1049312445, 1049312444, 1049312442, 1049312440, 1049312438, 1049312429, 1049312426, 1049312424, 1049312422, 1049312420, 1049312409, 1049312406, 1049312404, 1049312363, 1049312208, 1049311964, 1049311963, 1049311962, 1049311961, 1049311960, 1049311943, 1049311938, 1049311937, 1049311935, 1049311934, 1049311932, 1049311795, 1049311793, 1049311791, 1049311771, 1049311767, 1049311267, 1049311266, 1049311263, 1049311252, 1049311199, 1049311136, 1049311073, 1049311009, 1049311006, 1049310994, 1049310992, 1049310991, 1049310984, 1049310982, 1049310981, 1049310919, 1049310914, 1049310911, 1049310909, 1049310907, 1049310905, 1049310165, 1049310162, 1049310159, 1049310145, 1049310141, 1049310139, 1049310138, 1049310134, 1049310132, 1049309737, 1049309734, 1049309732, 1049309706, 1049309703, 1049309701, 1049309686, 1049309681, 1049309677, 1049309675, 1049309672, 1049309670, 1049309658, 1049309657, 1049309656, 1049309655, 1049309653, 1049309651, 1049309605, 1049309603, 1049309599, 1049309597, 1049309595, 1049309592, 1049309385, 1049309383, 1049309382, 1049309381, 1049309380, 1049309379, 1049309345, 1049308384, 1049308381, 1049308376, 1049308280, 1049308276, 1049308275, 1049308235, 1049307693, 1049306823, 1049306804, 1049306792, 1049306791, 1049306635, 1049306205, 1049304810, 1049303925, 1049296996, 1049296121, 1049294990, 1049293230] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 232 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3789', '4599398', '1049318362', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318360', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318358', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318356', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318342', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318339', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318337', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318311', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318310', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318309', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318294', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318293', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318291', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318289', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318288', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318287', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318279', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318276', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318273', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318271', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318268', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318265', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318260', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318257', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318253', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318250', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318247', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318246', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318222', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318219', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318216', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318214', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318213', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049318212', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317554', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317551', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317549', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317546', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317542', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317536', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317526', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317525', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317524', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317522', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317520', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317517', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317497', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317493', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317491', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317489', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317487', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317485', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317468', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317461', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317457', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317453', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317444', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317440', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317359', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317333', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317282', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317225', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317210', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049317197', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316790', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316785', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316782', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316778', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316752', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316749', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316610', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316600', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316597', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316594', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316588', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316582', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316545', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316543', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316540', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316537', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316534', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316520', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316338', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316336', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316332', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316331', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316257', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316255', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049316222', '[>, , , , , "\'NoneType\' object 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\'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049304810', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049303925', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049296996', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049296121', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049294990', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3789', '4599398', '1049293230', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.09911918640136719 save_final ERROR in last step split_time_score, 'NoneType' object has no attribute 'startswith' time spend for datou_step_exec : 0.07404756546020508 time spend to save output : 0.10570406913757324 total time spend for step 0 : 0.17975163459777832 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True ouput is None saving photo_ids in datou_result begin to insert list_values into mtr_datou_result : length of list_values in save_final : 232 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3789', '4599398', '1049318362', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318360', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318358', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318356', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318342', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318339', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318337', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318311', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318310', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318309', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318294', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318293', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318291', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318289', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318288', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318287', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318279', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318276', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318273', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318271', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318268', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318265', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318260', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318257', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318253', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318250', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318247', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318246', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318222', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318219', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049318216', '0', '0', '0', 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'0', '492764225', '0', None), ('3789', '4599398', '1049317359', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049317333', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049317282', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049317225', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049317210', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049317197', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316790', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316785', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316782', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316778', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316752', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316749', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049316610', '0', '0', '0', '492764225', '0', None), ('3789', 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'4599398', '1049311266', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311263', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311252', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311199', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311136', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311073', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311009', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049311006', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310994', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310992', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310991', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310984', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310982', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310981', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310919', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310914', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310911', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310909', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310907', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310905', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310165', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310162', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310159', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310145', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310141', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310139', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310138', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310134', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049310132', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309737', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309734', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309732', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309706', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309703', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309701', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309686', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309681', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309677', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309675', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309672', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309670', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309658', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309657', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309656', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309655', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309653', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309651', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309605', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309603', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309599', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309597', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309595', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309592', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309385', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309383', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309382', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309381', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309380', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309379', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049309345', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308384', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308381', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308376', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308280', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308276', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308275', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049308235', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049307693', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306823', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306804', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306792', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306791', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306635', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049306205', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049304810', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049303925', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049296996', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049296121', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049294990', '0', '0', '0', '492764225', '0', None), ('3789', '4599398', '1049293230', '0', '0', '0', '492764225', '0', None)] time used for this insertion : 0.04095149040222168 After save, about to update current ! Result test rubbia : None| Result context_with_local_rubbia.cache_model_config.map_io test rubbia : {'input': {}, 'output': {}}| got : None expected : {'4599398': ([[0, 7, 8, 9, 11, 12, 13, 14, 17, 18], [19, 20, 22, 23, 25, 26, 27, 38, 39, 40, 51, 52, 53, 55, 60, 61, 62, 63, 71, 76, 77, 81, 82, 83, 84], [85, 86, 91, 92], [93], [97, 98, 99, 100, 101], [102], [103, 104], [107, 108, 109, 110, 112, 113, 116, 117, 118, 121, 122, 123], [124, 126, 128, 129, 130, 131, 134, 135], [136, 137, 138, 147, 148, 149, 150, 151, 152, 153, 154, 157, 158, 161, 162, 167, 168], [173, 176, 177, 178, 182, 183, 187, 188], [189, 193], [198, 201, 202, 207, 208, 209, 210, 211, 212, 213, 214, 215], [216, 217, 218, 220], [221, 224, 225, 226, 227, 231]], {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}, {13545772: {'list_of_photos': [1049293230, 1049306791, 1049294990, 1049306792, 1049306823, 1049307693, 1049308235, 1049308275, 1049308376, 1049308381], 'hashtag': 'papier'}, 13545774: {'list_of_photos': [1049308384, 1049309345, 1049309380, 1049309381, 1049309383, 1049309385, 1049309592, 1049309658, 1049309670, 1049309672, 1049310132, 1049310134, 1049310138, 1049310141, 1049310905, 1049310907, 1049310909, 1049310911, 1049310994, 1049311199, 1049311252, 1049311767, 1049311771, 1049311791, 1049311793], 'hashtag': 'plastique_fonce'}, 13545777: {'list_of_photos': [1049311795, 1049311932, 1049311943, 1049311960], 'hashtag': 'papier'}, 5570414: {'list_of_photos': [1049311961], 'hashtag': 'plastique_fonce'}, 13545779: {'list_of_photos': [1049312208, 1049312363, 1049312404, 1049312406, 1049312409], 'hashtag': 'papier'}, 13545780: {'list_of_photos': [1049312420], 'hashtag': 'plastique_fonce'}, 13545783: {'list_of_photos': [1049312422, 1049312424], 'hashtag': 'papier'}, 13545785: {'list_of_photos': [1049312438, 1049312440, 1049312442, 1049312444, 1049312449, 1049312460, 1049312463, 1049312464, 1049312484, 1049312488, 1049312489, 1049312508], 'hashtag': 'plastique_fonce'}, 13545787: {'list_of_photos': [1049312556, 1049312566, 1049312571, 1049312573, 1049312574, 1049312579, 1049312588, 1049312803], 'hashtag': 'papier'}, 13545788: {'list_of_photos': [1049312984, 1049313025, 1049316209, 1049316332, 1049316336, 1049316338, 1049316520, 1049316534, 1049316537, 1049316540, 1049316543, 1049316588, 1049316594, 1049316610, 1049316749, 1049316790, 1049317197], 'hashtag': 'plastique_fonce'}, 13543473: {'list_of_photos': [1049317359, 1049317453, 1049317457, 1049317461, 1049317489, 1049317491, 1049317520, 1049317522], 'hashtag': 'aluminium'}, 13543474: {'list_of_photos': [1049317524, 1049317542], 'hashtag': 'tetrapak'}, 13543475: {'list_of_photos': [1049318212, 1049318216, 1049318219, 1049318253, 1049318257, 1049318260, 1049318265, 1049318268, 1049318271, 1049318273, 1049318276, 1049318279], 'hashtag': 'plastique_fonce'}, 13543476: {'list_of_photos': [1049318287, 1049318288, 1049318289, 1049318293], 'hashtag': 'papier'}, 13543477: {'list_of_photos': [1049318294, 1049318311, 1049318337, 1049318339, 1049318342, 1049318362], 'hashtag': 'plastique_fonce'}}, {2107751280: 8, 2107750907: 0, 2107750908: 33, 2107750909: 0, 2107750910: 0, 2107750911: 74, 2107750912: 0, 2107750913: 2}, {'amount_uploaded_and_tagged': {'07092021': {'nb_upload': 232, 'nb_taggue_class': 232, 'nb_taggue_densite': 232, 'nb_descriptors': 232, 'number_port': 15, 'count_photo_in_port': 117, 'nb_port_per_class': {'rungis_aluminium': {'nb_photos': 8, 'nb_portfolios': 1}, 'rungis_carton': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_papier': {'nb_photos': 33, 'nb_portfolios': 6}, 'rungis_plastique_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_dur': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_fonce': {'nb_photos': 74, 'nb_portfolios': 7}, 'rungis_tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_tetrapak': {'nb_photos': 2, 'nb_portfolios': 1}}}}, 'map_all_result_after_group_moy_exp': {'number_port': 15, 'count_photo_in_port': 117, 'nb_port_per_class': {'rungis_aluminium': {'nb_photos': 8, 'nb_portfolios': 1}, 'rungis_carton': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_papier': {'nb_photos': 33, 'nb_portfolios': 6}, 'rungis_plastique_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_dur': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_fonce': {'nb_photos': 74, 'nb_portfolios': 7}, 'rungis_tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_tetrapak': {'nb_photos': 2, 'nb_portfolios': 1}}}, 'map_info_after_moyenne_mobile': {'07092021': {'distrib_time_diff': {'nb': 207, 'mean': 12.512076641626404, 'stddev': 12.296218880583977, 'min': 0.0, 'max': 119.00011491775513, 'quantil_10': {'min': [8.999778032302856], 'max': [11.000291109085083]}, 'quantil_100': {'min': [8.999709129333496], 'max': [61.00024700164795]}, 'quantil_1000': {'min': [0.0], 'max': [119.00011491775513]}, 'quantil_5000': {'min': [0.0], 'max': [119.00011491775513]}, 'quantil_10000': {'min': [0.0], 'max': [119.00011491775513]}}, 'time_diff': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 80.99965000152588, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 49.000049114227295, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 11.000201940536499, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 534.9997780323029, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 31.000057697296143, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 564.0013737678528, '05102018_papier_non_papier_tres_peu_dense': 19.999656200408936}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 8.999944925308228, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 89.99986672401428, '05102018_papier_non_papier_tres_peu_dense': 9.999994993209839}}, 'time_diff_removed': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 11.000208854675293, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 158.99993062019348, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 101.00013995170593, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 18.999826192855835, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 168.99926328659058, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 21.00012707710266, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 489.9993727207184, '05102018_papier_non_papier_tres_peu_dense': 11.000169038772583}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 38.99988508224487, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 170.0003685951233, '05102018_papier_non_papier_tres_peu_dense': 0}}, 'nb_photos': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 8, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 6, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 28, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 2, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 40, '05102018_papier_non_papier_tres_peu_dense': 2}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 9, '05102018_papier_non_papier_tres_peu_dense': 1}}, 'nb_photos_removed': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 16, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 5, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 2, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 16, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 46, '05102018_papier_non_papier_tres_peu_dense': 1}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 4, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 17, '05102018_papier_non_papier_tres_peu_dense': 0}}}}, 'map_amount_per_hashtag': {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}, 'count': {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}})} ERROR rubbia FAILED ############################### TEST rubbia_split_dark ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3787 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3787 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3787 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3787 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score_with_photo list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4608689) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4608689) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1055013727, 'portfolio_id': 4608689}, {'photo_id': 1055013724, 'portfolio_id': 4608689}, {'photo_id': 1055013693, 'portfolio_id': 4608689}, {'photo_id': 1055012727, 'portfolio_id': 4608689}, {'photo_id': 1055012722, 'portfolio_id': 4608689}, {'photo_id': 1055012686, 'portfolio_id': 4608689}, {'photo_id': 1055012684, 'portfolio_id': 4608689}, {'photo_id': 1055011740, 'portfolio_id': 4608689}, {'photo_id': 1055011733, 'portfolio_id': 4608689}, {'photo_id': 1055011726, 'portfolio_id': 4608689}, {'photo_id': 1055011459, 'portfolio_id': 4608689}, {'photo_id': 1055011454, 'portfolio_id': 4608689}, {'photo_id': 1055011441, 'portfolio_id': 4608689}, {'photo_id': 1055011086, 'portfolio_id': 4608689}, {'photo_id': 1055011076, 'portfolio_id': 4608689}, {'photo_id': 1055011074, 'portfolio_id': 4608689}, {'photo_id': 1055011072, 'portfolio_id': 4608689}, {'photo_id': 1055010743, 'portfolio_id': 4608689}, {'photo_id': 1055010739, 'portfolio_id': 4608689}, {'photo_id': 1055010737, 'portfolio_id': 4608689}, {'photo_id': 1055010730, 'portfolio_id': 4608689}, {'photo_id': 1055010725, 'portfolio_id': 4608689}, {'photo_id': 1055010723, 'portfolio_id': 4608689}, {'photo_id': 1055010143, 'portfolio_id': 4608689}, {'photo_id': 1055008638, 'portfolio_id': 4608689}, {'photo_id': 1055008599, 'portfolio_id': 4608689}, {'photo_id': 1055008597, 'portfolio_id': 4608689}, {'photo_id': 1055008184, 'portfolio_id': 4608689}, {'photo_id': 1055008181, 'portfolio_id': 4608689}, {'photo_id': 1055007992, 'portfolio_id': 4608689}, {'photo_id': 1055007953, 'portfolio_id': 4608689}, {'photo_id': 1055007950, 'portfolio_id': 4608689}, {'photo_id': 1055004798, 'portfolio_id': 4608689}, {'photo_id': 1055004627, 'portfolio_id': 4608689}, {'photo_id': 1055004608, 'portfolio_id': 4608689}, {'photo_id': 1055004600, 'portfolio_id': 4608689}, {'photo_id': 1055004278, 'portfolio_id': 4608689}, {'photo_id': 1055004217, 'portfolio_id': 4608689}, {'photo_id': 1055003679, 'portfolio_id': 4608689}, {'photo_id': 1055003357, 'portfolio_id': 4608689}, {'photo_id': 1055003348, 'portfolio_id': 4608689}, {'photo_id': 1055003292, 'portfolio_id': 4608689}, {'photo_id': 1055003278, 'portfolio_id': 4608689}, {'photo_id': 1055003266, 'portfolio_id': 4608689}, {'photo_id': 1055003261, 'portfolio_id': 4608689}, {'photo_id': 1055003259, 'portfolio_id': 4608689}, {'photo_id': 1055003249, 'portfolio_id': 4608689}, {'photo_id': 1055003202, 'portfolio_id': 4608689}, {'photo_id': 1055003198, 'portfolio_id': 4608689}, {'photo_id': 1055003197, 'portfolio_id': 4608689}, {'photo_id': 1055003185, 'portfolio_id': 4608689}, {'photo_id': 1055003134, 'portfolio_id': 4608689}, {'photo_id': 1055003131, 'portfolio_id': 4608689}, {'photo_id': 1055002045, 'portfolio_id': 4608689}, {'photo_id': 1055001545, 'portfolio_id': 4608689}, {'photo_id': 1055001542, 'portfolio_id': 4608689}, {'photo_id': 1055001092, 'portfolio_id': 4608689}, {'photo_id': 1055001085, 'portfolio_id': 4608689}, {'photo_id': 1055000228, 'portfolio_id': 4608689}, {'photo_id': 1055000070, 'portfolio_id': 4608689}, {'photo_id': 1055000068, 'portfolio_id': 4608689}, {'photo_id': 1055000063, 'portfolio_id': 4608689}, {'photo_id': 1055000059, 'portfolio_id': 4608689}, {'photo_id': 1055000055, 'portfolio_id': 4608689}] map_portfolio_id_photo_id: {4608689: [1055013727, 1055013724, 1055013693, 1055012727, 1055012722, 1055012686, 1055012684, 1055011740, 1055011733, 1055011726, 1055011459, 1055011454, 1055011441, 1055011086, 1055011076, 1055011074, 1055011072, 1055010743, 1055010739, 1055010737, 1055010730, 1055010725, 1055010723, 1055010143, 1055008638, 1055008599, 1055008597, 1055008184, 1055008181, 1055007992, 1055007953, 1055007950, 1055004798, 1055004627, 1055004608, 1055004600, 1055004278, 1055004217, 1055003679, 1055003357, 1055003348, 1055003292, 1055003278, 1055003266, 1055003261, 1055003259, 1055003249, 1055003202, 1055003198, 1055003197, 1055003185, 1055003134, 1055003131, 1055002045, 1055001545, 1055001542, 1055001092, 1055001085, 1055000228, 1055000070, 1055000068, 1055000063, 1055000059, 1055000055]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1055013727 begin to download photo : 1055011086 begin to download photo : 1055008597 begin to download photo : 1055003357 begin to download photo : 1055003131 download finish for photo 1055011086 begin to download photo : 1055011076 download finish for photo 1055003357 begin to download photo : 1055003348 download finish for photo 1055013727 begin to download photo : 1055013724 download finish for photo 1055003131 begin to download photo : 1055002045 download finish for photo 1055008597 begin to download photo : 1055008184 download finish for photo 1055011076 begin to download photo : 1055011074 download finish for photo 1055013724 begin to download photo : 1055013693 download finish for photo 1055003348 begin to download photo : 1055003292 download finish for photo 1055002045 begin to download photo : 1055001545 download finish for photo 1055008184 begin to download photo : 1055008181 download finish for photo 1055011074 begin to download photo : 1055011072 download finish for photo 1055003292 begin to download photo : 1055003278 download finish for photo 1055013693 begin to download photo : 1055012727 download finish for photo 1055011072 begin to download photo : 1055010743 download finish for photo 1055008181 begin to download photo : 1055007992 download finish for photo 1055001545 begin to download photo : 1055001542 download finish for photo 1055003278 begin to download photo : 1055003266 download finish for photo 1055012727 begin to download photo : 1055012722 download finish for photo 1055010743 begin to download photo : 1055010739 download finish for photo 1055001542 begin to download photo : 1055001092 download finish for photo 1055012722 begin to download photo : 1055012686 download finish for photo 1055003266 begin to download photo : 1055003261 download finish for photo 1055007992 begin to download photo : 1055007953 download finish for photo 1055010739 begin to download photo : 1055010737 download finish for photo 1055001092 begin to download photo : 1055001085 download finish for photo 1055012686 begin to download photo : 1055012684 download finish for photo 1055003261 begin to download photo : 1055003259 download finish for photo 1055001085 begin to download photo : 1055000228 download finish for photo 1055007953 begin to download photo : 1055007950 download finish for photo 1055012684 begin to download photo : 1055011740 download finish for photo 1055010737 begin to download photo : 1055010730 download finish for photo 1055003259 begin to download photo : 1055003249 download finish for photo 1055010730 begin to download photo : 1055010725 download finish for photo 1055007950 begin to download photo : 1055004798 download finish for photo 1055011740 begin to download photo : 1055011733 download finish for photo 1055000228 begin to download photo : 1055000070 download finish for photo 1055003249 begin to download photo : 1055003202 download finish for photo 1055010725 begin to download photo : 1055010723 download finish for photo 1055011733 begin to download photo : 1055011726 download finish for photo 1055000070 begin to download photo : 1055000068 download finish for photo 1055003202 begin to download photo : 1055003198 download finish for photo 1055011726 begin to download photo : 1055011459 download finish for photo 1055010723 begin to download photo : 1055010143 download finish for photo 1055000068 begin to download photo : 1055000063 download finish for photo 1055003198 begin to download photo : 1055003197 download finish for photo 1055010143 begin to download photo : 1055008638 download finish for photo 1055011459 begin to download photo : 1055011454 download finish for photo 1055000063 begin to download photo : 1055000059 download finish for photo 1055003197 begin to download photo : 1055003185 download finish for photo 1055008638 begin to download photo : 1055008599 download finish for photo 1055011454 begin to download photo : 1055011441 download finish for photo 1055000059 begin to download photo : 1055000055 download finish for photo 1055003185 begin to download photo : 1055003134 download finish for photo 1055008599 download finish for photo 1055011441 download finish for photo 1055003134 download finish for photo 1055004798 begin to download photo : 1055004627 download finish for photo 1055000055 download finish for photo 1055004627 begin to download photo : 1055004608 download finish for photo 1055004608 begin to download photo : 1055004600 download finish for photo 1055004600 begin to download photo : 1055004278 download finish for photo 1055004278 begin to download photo : 1055004217 download finish for photo 1055004217 begin to download photo : 1055003679 download finish for photo 1055003679 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 64 ; length of list_pids : 64 ; length of list_args : 64 ##### After load_data_input time to download the photos : 5.460753679275513 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score_with_photo Thu Sep 25 17:06:04 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812759_3157952_1055011086_bdfadbfd9b854d0e57bff554442c9bcd.jpg': 1055011086, 'temp/1758812759_3157952_1055011076_8f47b07eac25de1c6c004fe4d3d508be.jpg': 1055011076, 'temp/1758812759_3157952_1055011074_af75a035dcd1829a43a1e1de711c1c5c.jpg': 1055011074, 'temp/1758812759_3157952_1055011072_37a292bbe61b6a71ca20b3b88d1105ca.jpg': 1055011072, 'temp/1758812759_3157952_1055010743_8e677a02379626daa3d4ee7356ad894e.jpg': 1055010743, 'temp/1758812759_3157952_1055010739_e4eec41f6a47dc3e97c189a1e5caa46f.jpg': 1055010739, 'temp/1758812759_3157952_1055010737_350522f4866a7dcde0258de8aa920041.jpg': 1055010737, 'temp/1758812759_3157952_1055010730_1cfbca5001cab6e5d12df6b4b06e86c5.jpg': 1055010730, 'temp/1758812759_3157952_1055010725_915c21ba8a484205e02874d398e0faef.jpg': 1055010725, 'temp/1758812759_3157952_1055010723_2601cc78c82bdb85cb92f991b4df99cb.jpg': 1055010723, 'temp/1758812759_3157952_1055010143_9d8ce5a6bcd913fe183d34bf4af34991.jpg': 1055010143, 'temp/1758812759_3157952_1055008638_3468359b1556541fe6baa375af06bd9a.jpg': 1055008638, 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'temp/1758812759_3157952_1055011459_76e96710774ab5e4a8e5f23142b2b45e.jpg': 1055011459, 'temp/1758812759_3157952_1055011454_46ec921f09112d298dcc47353d779d55.jpg': 1055011454, 'temp/1758812759_3157952_1055011441_d825f9623da221614af7ce7a13591d1a.jpg': 1055011441, 'temp/1758812759_3157952_1055003357_724bbfa472d57dcea0975679f4a393ff.jpg': 1055003357, 'temp/1758812759_3157952_1055003348_588ecea5e15961fe1292f72d4cf33b3c.jpg': 1055003348, 'temp/1758812759_3157952_1055003292_4ad5363c1776217234fa6acc8a9fbd85.jpg': 1055003292, 'temp/1758812759_3157952_1055003278_1e53f6abe2076619fbf0cb6255fca71b.jpg': 1055003278, 'temp/1758812759_3157952_1055003266_eae639e1ccc20bd1a6a2f69e66c41382.jpg': 1055003266, 'temp/1758812759_3157952_1055003261_fb67a67f6cc7a87b0af2a03906a24b7d.jpg': 1055003261, 'temp/1758812759_3157952_1055003259_cc27886462be43921344678712ff777f.jpg': 1055003259, 'temp/1758812759_3157952_1055003249_a3800e1944260107f11d988a743bd54f.jpg': 1055003249, 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[{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] select SUBSTRING(ph.text,16,2) as h, count(*) from MTRUser.mtr_portfolio_photos mpp inner join MTRBack.view_photos_with_urls_250912 ph on mpp.mtr_photo_id = ph.photo_id where mpp.mtr_portfolio_id = 4608689 group by h (('18', 4), ('19', 5), ('20', 5), ('24', 8), ('26', 6), ('17', 1), ('27', 9), ('51', 7), ('28', 2), ('21', 4), ('52', 2), ('25', 6), ('50', 3), ('22', 2)) SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4608689 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4608689) AND cps.thcl in (861) order by cps.score desc LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4608689) AND cps.thcl in (758) order by cps.score desc LIMIT 0, 100000 ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 06102021 4608689 Nombre de photos uploadées : 64 / 23040 (0%) 06102021 4608689 Nombre de photos taguées (types de déchets): 0 / 64 (0%) 06102021 4608689 Nombre de photos taguées (volume) : 0 / 64 (0%) [{'photo_id': 1055000228, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/10/7/6046bacdc732ec23020791db686fd31b.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20211006_101733.jpg', 'path': 'temp/1758812759_3157952_1055000228_6046bacdc732ec23020791db686fd31b.jpg', 'black': False}, {'photo_id': 1055007950, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/10/7/3aea8b8cb1f8c6e4b87714e0d17e12c5.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20211006_101843.jpg', 'path': 'temp/1758812759_3157952_1055007950_3aea8b8cb1f8c6e4b87714e0d17e12c5.jpg', 'black': False}, {'photo_id': 1055003348, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/10/7/588ecea5e15961fe1292f72d4cf33b3c.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20211006_101853.jpg', 'path': 'temp/1758812759_3157952_1055003348_588ecea5e15961fe1292f72d4cf33b3c.jpg', 'black': False}, {'photo_id': 1055000055, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/10/7/c9e450bd4b6e2cb9cfa8e540e915987c.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20211006_101804.jpg', 'path': 'temp/1758812759_3157952_1055000055_c9e450bd4b6e2cb9cfa8e540e915987c.jpg', 'black': False}] 0 [] elapsed_time : load_data_split_time_score 8.821487426757812e-06 elapsed_time : order_list_meta_photo_and_scores 9.298324584960938e-06 ???????????????????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0026810169219970703 INSERT INTO `MTRPhoto`.`dashboard_entry_day` (`dashboard_place_id`, `mtr_portfolio_id`, `date`) VALUES ( 41, 4608689, '2021-10-06' ) ON DUPLICATE KEY UPDATE mtr_portfolio_id=VALUES(mtr_portfolio_id), updated_at=NOW(); Catched exception ! Connect or reconnect ! INSERT INTO `MTRPhoto`.`dashboard_run_ids` (`dashboard_entry_day`, `mtr_user_id`, `misc_info`) VALUES (106232,739,"{}"); Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.2136681079864502 ***** BEGIN SPLIT BY DARK ***** To DO 08/10/21 Let s Iterate on Ds Object and set black attribute == > begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) first line : (1055001085, 492584841, 4330) ... last line : (1055001085, 492584841, 4330) time used for this insertion : 0.008045434951782227 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 2 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) first line : (1055001085, 492584841, 4330) ... last line : (1055008638, 492584841, 4330) time used for this insertion : 0.007886648178100586 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) first line : (1055001085, 492584841, 4330) ... last line : (1055010730, 492584841, 4330) time used for this insertion : 0.007986783981323242 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 4 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) first line : (1055001085, 492584841, 4330) ... last line : (1055011086, 492584841, 4330) time used for this insertion : 0.007873058319091797 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 5 insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) insert ignore into MTRBack.photo_hashtag_ids (photo_id, hashtag_id, type) values (%s,%s,%s) on DUPLICATE KEY UPDATE hashtag_id=VALUES(hashtag_id) first line : (1055001085, 492584841, 4330) ... last line : (1055012686, 492584841, 4330) time used for this insertion : 0.008026599884033203 elapsed_time : SPLIT_BY_DARK 0.04602622985839844 ***** END SPLIT BY DARK ***** ((1055001085,), (1055008638,), (1055010730,), (1055011086,), (1055012686,)) ***** BEGIN SPLIT TIME ***** [12, 20, 29, 38, 51] ````````````````````````````````````````````````````````````````list printed: [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]] forced_hashtag: jrm force hashtag to jrm elapsed_time : SPLIT_TIME 0.006724357604980469 ***** END SPLIT TIME ***** NUMBER BATCH : 7 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['refus', 'jrm'] Listed one port to create portfolio : jrm_diff_batch__06102021_10_17_33_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_10_17_33_000000 : 0 duration : 172.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 172.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_101733.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Listed one port to create portfolio : jrm_diff_batch__06102021_10_20_49_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_10_20_49_000000 : 0 duration : 72.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 72.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102049.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Listed one port to create portfolio : jrm_diff_batch__06102021_10_24_04_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_10_24_04_000000 : 0 duration : 52.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 52.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102404.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Listed one port to create portfolio : jrm_diff_batch__06102021_10_25_25_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_10_25_25_000000 : 0 duration : 53.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 53.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102525.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Listed one port to create portfolio : jrm_diff_batch__06102021_10_26_45_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_10_26_45_000000 : 0 duration : 81.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 81.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102645.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Empty batch, bug or could have been filtered ! Listed one port to create portfolio : jrm_diff_batch__06102021_14_50_39_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__06102021_14_50_39_000000 : 0 duration : 102.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 102.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_145039.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 6 list_same_port_ids : [4938484] find same portfolio which already exist 4938484 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4938484 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4938484 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4938485] find same portfolio which already exist 4938485 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4938485 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4938485 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4938486] find same portfolio which already exist 4938486 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4938486 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4938486 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4938487] find same portfolio which already exist 4938487 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4938487 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4938487 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4938488] find same portfolio which already exist 4938488 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4938488 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4938488 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4756245] find same portfolio which already exist 4756245 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4756245 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4756245 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938484 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938484 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4938484 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938484 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 10:17:33', '2021-10-06 10:20:25', 12, 4938484, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4938484_21-11-2024_00_58_17.pdf', 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4938531, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4938532, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4938533, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4938534, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4938535, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4938536, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4938537, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4938538, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4938539, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4938540, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938485 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938485 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4938485 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938485 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 10:20:49', '2021-10-06 10:22:01', 7, 4938485, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4938485_21-11-2024_01_05_11.pdf', 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4938520, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4938521, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4938522, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4938523, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4938524, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4938525, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4938526, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4938527, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4938528, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4938529, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938486 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938486 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4938486 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938486 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 10:24:04', '2021-10-06 10:24:56', 8, 4938486, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4938486_21-11-2024_01_17_15.pdf', 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4938542, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4938543, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4938544, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4938545, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4938546, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4938547, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4938548, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4938549, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4938550, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4938551, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938487 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938487 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4938487 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938487 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 10:25:25', '2021-10-06 10:26:18', 8, 4938487, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4938487_21-11-2024_01_27_52.pdf', 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4938552, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4938553, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4938554, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4938555, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4938556, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4938557, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4938558, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4938559, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4938560, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4938561, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938488 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4938488 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4938488 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938488 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 10:26:45', '2021-10-06 10:28:06', 12, 4938488, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4938488_21-11-2024_01_43_46.pdf', 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4938797, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4938798, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4938799, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4938800, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4938801, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4938802, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4938803, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4938804, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4938805, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4938806, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4756245 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4756245 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4756245 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4756245 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358485, '_______jrm', '2021-10-06 14:50:39', '2021-10-06 14:52:21', 12, 4756245, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4756245_21-11-2024_01_56_10.pdf', 'kraft': {'hashtag': 'kraft', 'sub_port_id': 4756351, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 4756352, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 4756353, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 4756354, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 4756355, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 4756356, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 4756357, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 4756358, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 4756359, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 4756360, 'pht': 4038}}" ); elapsed_time : count_nb_balles_and_create_portfolio 1.3099462985992432 # DISPLAY ALL COLLECTED DATA : {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} ------ Fin du Copier-Coller ------ ---------- ONE RESULT --------- ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}}) ---------- END de ONE RESULT ---------- Suppression des photos Telecharges After datou_step_exec type output : time spend for datou_step_exec : 6.743994474411011 time spend to save output : 8.559226989746094e-05 total time spend for step 1 : 6.744080066680908 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : split_time_score_with_photo we use saveGeneral [1055011086, 1055011076, 1055011074, 1055011072, 1055010743, 1055010739, 1055010737, 1055010730, 1055010725, 1055010723, 1055010143, 1055008638, 1055008599, 1055013727, 1055013724, 1055013693, 1055012727, 1055012722, 1055012686, 1055012684, 1055011740, 1055011733, 1055011726, 1055011459, 1055011454, 1055011441, 1055003357, 1055003348, 1055003292, 1055003278, 1055003266, 1055003261, 1055003259, 1055003249, 1055003202, 1055003198, 1055003197, 1055003185, 1055003134, 1055003131, 1055002045, 1055001545, 1055001542, 1055001092, 1055001085, 1055000228, 1055000070, 1055000068, 1055000063, 1055000059, 1055000055, 1055008597, 1055008184, 1055008181, 1055007992, 1055007953, 1055007950, 1055004798, 1055004627, 1055004608, 1055004600, 1055004278, 1055004217, 1055003679] map_info['map_portfolio_photo'] : {4608689: [1055013727, 1055013724, 1055013693, 1055012727, 1055012722, 1055012686, 1055012684, 1055011740, 1055011733, 1055011726, 1055011459, 1055011454, 1055011441, 1055011086, 1055011076, 1055011074, 1055011072, 1055010743, 1055010739, 1055010737, 1055010730, 1055010725, 1055010723, 1055010143, 1055008638, 1055008599, 1055008597, 1055008184, 1055008181, 1055007992, 1055007953, 1055007950, 1055004798, 1055004627, 1055004608, 1055004600, 1055004278, 1055004217, 1055003679, 1055003357, 1055003348, 1055003292, 1055003278, 1055003266, 1055003261, 1055003259, 1055003249, 1055003202, 1055003198, 1055003197, 1055003185, 1055003134, 1055003131, 1055002045, 1055001545, 1055001542, 1055001092, 1055001085, 1055000228, 1055000070, 1055000068, 1055000063, 1055000059, 1055000055]} final : True mtd_id 3787 list_pids : [1055011086, 1055011076, 1055011074, 1055011072, 1055010743, 1055010739, 1055010737, 1055010730, 1055010725, 1055010723, 1055010143, 1055008638, 1055008599, 1055013727, 1055013724, 1055013693, 1055012727, 1055012722, 1055012686, 1055012684, 1055011740, 1055011733, 1055011726, 1055011459, 1055011454, 1055011441, 1055003357, 1055003348, 1055003292, 1055003278, 1055003266, 1055003261, 1055003259, 1055003249, 1055003202, 1055003198, 1055003197, 1055003185, 1055003134, 1055003131, 1055002045, 1055001545, 1055001542, 1055001092, 1055001085, 1055000228, 1055000070, 1055000068, 1055000063, 1055000059, 1055000055, 1055008597, 1055008184, 1055008181, 1055007992, 1055007953, 1055007950, 1055004798, 1055004627, 1055004608, 1055004600, 1055004278, 1055004217, 1055003679] Looping around the photos to save general results len do output : 5 /[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]] /{'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]} /{4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}} /{2107757407: 59} /{'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}} before output type Managing all output in save final without adding information in the mtr_datou_result ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011086', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011076', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011074', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011072', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010743', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010739', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010737', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010730', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010725', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010723', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010143', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008638', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008599', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013727', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013724', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013693', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012727', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012722', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012686', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012684', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011740', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011733', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011726', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011459', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011454', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011441', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003357', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003348', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003292', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003278', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003266', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003261', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003259', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003249', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003202', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003198', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003197', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003185', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003134', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003131', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055002045', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001545', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001542', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001092', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001085', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000228', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000070', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000068', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000063', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000059', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000055', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008597', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008184', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008181', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007992', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007953', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007950', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004798', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004627', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004608', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004600', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004278', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004217', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003679', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 64 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3787', '4608689', '1055011086', None, None, None, None, None, None), ('3787', '4608689', '1055011076', None, None, None, None, None, None), ('3787', '4608689', '1055011074', None, None, None, None, None, None), ('3787', '4608689', '1055011072', None, None, None, None, None, None), ('3787', '4608689', '1055010743', None, None, None, None, None, None), ('3787', '4608689', '1055010739', None, None, None, None, None, None), ('3787', '4608689', '1055010737', None, None, None, None, None, None), ('3787', '4608689', '1055010730', None, None, None, None, None, None), ('3787', '4608689', '1055010725', None, None, None, None, None, None), ('3787', '4608689', '1055010723', None, None, None, None, None, None), ('3787', '4608689', '1055010143', None, None, None, None, None, None), ('3787', '4608689', '1055008638', None, None, None, None, None, None), ('3787', '4608689', '1055008599', None, None, None, None, None, None), ('3787', '4608689', '1055013727', None, None, None, None, None, None), ('3787', '4608689', '1055013724', None, None, None, None, None, None), ('3787', '4608689', '1055013693', None, None, None, None, None, None), ('3787', '4608689', '1055012727', None, None, None, None, None, None), ('3787', '4608689', '1055012722', None, None, None, None, None, None), ('3787', '4608689', '1055012686', None, None, None, None, None, None), ('3787', '4608689', '1055012684', None, None, None, None, None, None), ('3787', '4608689', '1055011740', None, None, None, None, None, None), ('3787', '4608689', '1055011733', None, None, None, None, None, None), ('3787', '4608689', '1055011726', None, None, None, None, None, None), ('3787', '4608689', '1055011459', None, None, None, None, None, None), ('3787', '4608689', '1055011454', None, None, None, None, None, None), ('3787', '4608689', '1055011441', None, None, None, None, None, None), ('3787', '4608689', '1055003357', None, None, None, None, None, None), ('3787', '4608689', '1055003348', None, None, None, None, None, None), ('3787', '4608689', '1055003292', None, None, None, None, None, None), ('3787', '4608689', '1055003278', None, None, None, None, None, None), ('3787', '4608689', '1055003266', None, None, None, None, None, None), ('3787', '4608689', '1055003261', None, None, None, None, None, None), ('3787', '4608689', '1055003259', None, None, None, None, None, None), ('3787', '4608689', '1055003249', None, None, None, None, None, None), ('3787', '4608689', '1055003202', None, None, None, None, None, None), ('3787', '4608689', '1055003198', None, None, None, None, None, None), ('3787', '4608689', '1055003197', None, None, None, None, None, None), ('3787', '4608689', '1055003185', None, None, None, None, None, None), ('3787', '4608689', '1055003134', None, None, None, None, None, None), ('3787', '4608689', '1055003131', None, None, None, None, None, None), ('3787', '4608689', '1055002045', None, None, None, None, None, None), ('3787', '4608689', '1055001545', None, None, None, None, None, None), ('3787', '4608689', '1055001542', None, None, None, None, None, None), ('3787', '4608689', '1055001092', None, None, None, None, None, None), ('3787', '4608689', '1055001085', None, None, None, None, None, None), ('3787', '4608689', '1055000228', None, None, None, None, None, None), ('3787', '4608689', '1055000070', None, None, None, None, None, None), ('3787', '4608689', '1055000068', None, None, None, None, None, None), ('3787', '4608689', '1055000063', None, None, None, None, None, None), ('3787', '4608689', '1055000059', None, None, None, None, None, None), ('3787', '4608689', '1055000055', None, None, None, None, None, None), ('3787', '4608689', '1055008597', None, None, None, None, None, None), ('3787', '4608689', '1055008184', None, None, None, None, None, None), ('3787', '4608689', '1055008181', None, None, None, None, None, None), ('3787', '4608689', '1055007992', None, None, None, None, None, None), ('3787', '4608689', '1055007953', None, None, None, None, None, None), ('3787', '4608689', '1055007950', None, None, None, None, None, None), ('3787', '4608689', '1055004798', None, None, None, None, None, None), ('3787', '4608689', '1055004627', None, None, None, None, None, None), ('3787', '4608689', '1055004608', None, None, None, None, None, None), ('3787', '4608689', '1055004600', None, None, None, None, None, None), ('3787', '4608689', '1055004278', None, None, None, None, None, None), ('3787', '4608689', '1055004217', None, None, None, None, None, None), ('3787', '4608689', '1055003679', None, None, None, None, None, None)] time used for this insertion : 0.019704103469848633 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}}) Result test split dark : ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}})| ############################### TEST rubbia_append ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3856 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3856 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3856 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3856 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4599006) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4505992) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4599006,4505992) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1054572537, 'portfolio_id': 4599006}, {'photo_id': 1054572534, 'portfolio_id': 4599006}, {'photo_id': 1054572532, 'portfolio_id': 4599006}, {'photo_id': 1051605195, 'portfolio_id': 4505992}] map_portfolio_id_photo_id: {4599006: [1054572537, 1054572534, 1054572532], 4505992: [1051605195]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.024831056594848633 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Thu Sep 25 17:06:11 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} SELECT app_name, token FROM MTRUser.mtr_app_api_token WHERE mtr_user_id=739 AND app_name="token_split_time_score" AND expire_at > NOW() TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] select SUBSTRING(ph.text,16,2) as h, count(*) from MTRUser.mtr_portfolio_photos mpp inner join MTRBack.view_photos_with_urls_250912 ph on mpp.mtr_photo_id = ph.photo_id where mpp.mtr_portfolio_id = 4599006 group by h ((None, 3),) SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4599006 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4599006) AND cps.thcl in (861) order by cps.score desc LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4599006) AND cps.thcl in (758) order by cps.score desc LIMIT 0, 100000 ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} ERROR in datou_step_exec, will save and exit ! 'NoneType' object has no attribute 'startswith' File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2523, in datou_step_exec return lib_process.datou_step_split_time_score(param, json_param, args, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 2295, in datou_step_split_time_score one_result = split_port_in_batch_balle( File "/home/admin/workarea/git/Velours/python/misc/split_time_score.py", line 336, in split_port_in_batch_balle meta_photos, scores, densite, result_taggue_densite = load_data_split_time_score(int(mtr_portfolio), thcl, thcl_volume, context, limit, File "/home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py", line 2604, in load_data_split_time_score current_datetime, mean_pixel = parse_text_to_date(meta_photos[0]["text"]) File "/home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py", line 74, in parse_text_to_date if text.startswith("image_"): [1054572537, 1054572534, 1054572532, 1051605195] map_info['map_portfolio_photo'] : {4599006: [1054572537, 1054572534, 1054572532], 4505992: [1051605195]} final : True mtd_id 3856 list_pids : [1054572537, 1054572534, 1054572532, 1051605195] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3856', '4599006', '1054572537', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3856', '4599006', '1054572534', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3856', '4599006', '1054572532', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None), ('3856', '4505992', '1051605195', '[>, , , , , "\'NoneType\' object has no attribute \'startswith\'"]', '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.024367570877075195 save_final ERROR in last step split_time_score, 'NoneType' object has no attribute 'startswith' time spend for datou_step_exec : 0.04293489456176758 time spend to save output : 0.024860858917236328 total time spend for step 0 : 0.0677957534790039 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True ouput is None saving photo_ids in datou_result begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3856', '4599006', '1054572537', '0', '0', '0', '492764225', '0', None), ('3856', '4599006', '1054572534', '0', '0', '0', '492764225', '0', None), ('3856', '4599006', '1054572532', '0', '0', '0', '492764225', '0', None), ('3856', '4505992', '1051605195', '0', '0', '0', '492764225', '0', None)] time used for this insertion : 0.01381230354309082 After save, about to update current ! SELECT dashboard_run_id FROM MTRPhoto.dashboard_results where mtr_portfolio_id = 4599006 ############################### TEST rubbia_horaire ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3181 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3181 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3181 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3181 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3609515) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3609515) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1014106095, 'portfolio_id': 3609515}, {'photo_id': 1014106094, 'portfolio_id': 3609515}, {'photo_id': 1014106093, 'portfolio_id': 3609515}, {'photo_id': 1014105800, 'portfolio_id': 3609515}, {'photo_id': 1014105799, 'portfolio_id': 3609515}, {'photo_id': 1014105798, 'portfolio_id': 3609515}, {'photo_id': 1014105797, 'portfolio_id': 3609515}, {'photo_id': 1014105796, 'portfolio_id': 3609515}, {'photo_id': 1014105795, 'portfolio_id': 3609515}, {'photo_id': 1014105791, 'portfolio_id': 3609515}, {'photo_id': 1014105790, 'portfolio_id': 3609515}, {'photo_id': 1014105786, 'portfolio_id': 3609515}, {'photo_id': 1014105785, 'portfolio_id': 3609515}, {'photo_id': 1014105784, 'portfolio_id': 3609515}, {'photo_id': 1014105783, 'portfolio_id': 3609515}, {'photo_id': 1014105782, 'portfolio_id': 3609515}, {'photo_id': 1014105781, 'portfolio_id': 3609515}, {'photo_id': 1014105778, 'portfolio_id': 3609515}, {'photo_id': 1014105777, 'portfolio_id': 3609515}, {'photo_id': 1014099035, 'portfolio_id': 3609515}, {'photo_id': 1014098602, 'portfolio_id': 3609515}, {'photo_id': 1014098236, 'portfolio_id': 3609515}, {'photo_id': 1014097924, 'portfolio_id': 3609515}, {'photo_id': 1014097580, 'portfolio_id': 3609515}, {'photo_id': 1014097499, 'portfolio_id': 3609515}, {'photo_id': 1014097497, 'portfolio_id': 3609515}, {'photo_id': 1014097492, 'portfolio_id': 3609515}, {'photo_id': 1014054235, 'portfolio_id': 3609515}, {'photo_id': 1014054234, 'portfolio_id': 3609515}, {'photo_id': 1014054233, 'portfolio_id': 3609515}, {'photo_id': 1014054232, 'portfolio_id': 3609515}, {'photo_id': 1014054231, 'portfolio_id': 3609515}, {'photo_id': 1014054230, 'portfolio_id': 3609515}] map_portfolio_id_photo_id: {3609515: [1014106095, 1014106094, 1014106093, 1014105800, 1014105799, 1014105798, 1014105797, 1014105796, 1014105795, 1014105791, 1014105790, 1014105786, 1014105785, 1014105784, 1014105783, 1014105782, 1014105781, 1014105778, 1014105777, 1014099035, 1014098602, 1014098236, 1014097924, 1014097580, 1014097499, 1014097497, 1014097492, 1014054235, 1014054234, 1014054233, 1014054232, 1014054231, 1014054230]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.014236688613891602 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Thu Sep 25 17:06:11 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} SELECT app_name, token FROM MTRUser.mtr_app_api_token WHERE mtr_user_id=739 AND app_name="token_split_time_score" AND expire_at > NOW() TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] select SUBSTRING(ph.text,16,2) as h, count(*) from MTRUser.mtr_portfolio_photos mpp inner join MTRBack.view_photos_with_urls_250912 ph on mpp.mtr_photo_id = ph.photo_id where mpp.mtr_portfolio_id = 3609515 group by h () SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=3609515 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (3609515) AND cps.thcl in (861) order by cps.score desc LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (3609515) AND cps.thcl in (758) order by cps.score desc LIMIT 0, 100000 ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} ERROR in datou_step_exec, will save and exit ! list index out of range File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2339, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2523, in datou_step_exec return lib_process.datou_step_split_time_score(param, json_param, args, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 2295, in datou_step_split_time_score one_result = split_port_in_batch_balle( File "/home/admin/workarea/git/Velours/python/misc/split_time_score.py", line 336, in split_port_in_batch_balle meta_photos, scores, densite, result_taggue_densite = load_data_split_time_score(int(mtr_portfolio), thcl, thcl_volume, context, limit, File "/home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py", line 2604, in load_data_split_time_score current_datetime, mean_pixel = parse_text_to_date(meta_photos[0]["text"]) [] map_info['map_portfolio_photo'] : {3609515: [1014106095, 1014106094, 1014106093, 1014105800, 1014105799, 1014105798, 1014105797, 1014105796, 1014105795, 1014105791, 1014105790, 1014105786, 1014105785, 1014105784, 1014105783, 1014105782, 1014105781, 1014105778, 1014105777, 1014099035, 1014098602, 1014098236, 1014097924, 1014097580, 1014097499, 1014097497, 1014097492, 1014054235, 1014054234, 1014054233, 1014054232, 1014054231, 1014054230]} final : True mtd_id 3181 list_pids : [] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [] time used for this insertion : 4.0531158447265625e-06 save_final ERROR in last step split_time_score, list index out of range time spend for datou_step_exec : 0.04501843452453613 time spend to save output : 0.0003058910369873047 total time spend for step 0 : 0.04532432556152344 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True ouput is None saving photo_ids in datou_result begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [] time used for this insertion : 2.86102294921875e-06 After save, about to update current ! None argument of type 'NoneType' is not iterable ERROR rubbia_horaire FAILED ############################### TEST rle_unique_nms_with_priority ################################ t SELECT id FROM MTRPhoto.crop_hashtag_ids WHERE photo_id=998957128 AND `type`=2805 DELETE FROM MTRPhoto.crop_hashtag_ids WHERE id IN (3975187725,3975187726,3975187727,3975187728,3975187729,3975187730,3975187731,3975187732,3975187733,3975187734) SELECT id FROM MTRPhoto.crop_hashtag_ids WHERE photo_id=996751167 AND `type`=2805 DELETE FROM MTRPhoto.crop_hashtag_ids WHERE id IN (3975187994,3975187967,3975187995,3975187974,3975187957,3975187971,3975187954,3975187985,3975187973,3975187964,3975187992,3975187976,3975187981,3975187982,3975187987,3975187984,3975187960,3975187989,3975187965,3975187968,3975187983,3975187991,3975187970,3975187975,3975187966,3975187956,3975187980,3975187986,3975187958,3975187953,3975187962,3975187955,3975187972,3975187990,3975187977,3975187963,3975187979,3975187978,3975187961,3975187988,3975187993,3975187959,3975187969,3975187952) DELETE FROM MTRPhoto.photo_carac_ratio WHERE hashtag_type=2805; Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2548 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2548 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2548 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2548 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (998957128) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 998957128 download finish for photo 998957128 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.1297438144683838 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:rle_unique_nms_with_priority Thu Sep 25 17:06:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812772_3157952_998957128_f45017ffedbd1f7cb33fed47ac33648c.jpg': 998957128} map_photo_id_path_extension : {998957128: {'path': 'temp/1758812772_3157952_998957128_f45017ffedbd1f7cb33fed47ac33648c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812772_3157952_998957128_f45017ffedbd1f7cb33fed47ac33648c.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 998957128) and `type` in (2804) and hashtag_id in (2107754127,2107755994) Loaded 10 chid ids of type : 2804 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1872612725,1872612726,1872612727,1872612728,1872612729,1872612730,1872612731,1872612732,1872612733,1872612734) ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612725. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612726. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612727. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612728. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612729. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612730. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612731. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612732. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612733. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now +WARNING : duplicated polygon, we should remove this data for chi_id : 1872612734. Ignored now SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1872612725,1872612726,1872612727,1872612728,1872612729,1872612730,1872612731,1872612732,1872612733,1872612734) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1872612725,1872612726,1872612727,1872612728,1872612729,1872612730,1872612731,1872612732,1872612733,1872612734) nb_obj : 10 nb_hashtags : 2 time to prepare the origin masks : 0.46437788009643555 time for calcul the mask position with numpy : 0.0038299560546875 nb_pixel_total : 217207 time to create 1 rle with new method : 0.03580069541931152 time for calcul the mask position with numpy : 0.0026700496673583984 nb_pixel_total : 1008 time to create 1 rle with old method : 0.0011506080627441406 time for calcul the mask position with numpy : 0.002672910690307617 nb_pixel_total : 751 time to create 1 rle with old method : 0.0009024143218994141 time for calcul the mask position with numpy : 0.002574920654296875 nb_pixel_total : 722 time to create 1 rle with old method : 0.0007660388946533203 time for calcul the mask position with numpy : 0.002619504928588867 nb_pixel_total : 2949 time to create 1 rle with old method : 0.003336191177368164 time for calcul the mask position with numpy : 0.0029790401458740234 nb_pixel_total : 497 time to create 1 rle with old method : 0.0006182193756103516 time for calcul the mask position with numpy : 0.0030922889709472656 nb_pixel_total : 1086 time to create 1 rle with old method : 0.00122833251953125 time for calcul the mask position with numpy : 0.002768278121948242 nb_pixel_total : 1924 time to create 1 rle with old method : 0.0023071765899658203 time for calcul the mask position with numpy : 0.002660512924194336 nb_pixel_total : 413 time to create 1 rle with old method : 0.0005271434783935547 time for calcul the mask position with numpy : 0.002546072006225586 nb_pixel_total : 526 time to create 1 rle with old method : 0.0006043910980224609 create new chi : 0.07595443725585938 proportion hashtag : balle_pet_clair 0.23568467881944444 proportion hashtag : contaminant_du_pet_clair 0.010716145833333333 time to delete rle : 0.014864444732666016 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 10 chid ids of type : 2805 Number RLEs to save : 1674 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975220837', '538', '174', '1') ... last line : ('3975220846', '691', '285', '1') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! save time : 0.14403915405273438 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {998957128: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 0.8392081260681152 time spend to save output : 7.319450378417969e-05 total time spend for step 1 : 0.8392813205718994 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {998957128: (0.0, 'Should be the crop_list due to order', 0)} Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2573 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2573 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2573 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2573 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (1066511071) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 1066511071 download finish for photo 1066511071 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.2385396957397461 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:rle_unique_nms_with_priority Thu Sep 25 17:06:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812773_3157952_1066511071_cca6b29b0253f105b76231d9c28fabe3.jpg': 1066511071} map_photo_id_path_extension : {1066511071: {'path': 'temp/1758812773_3157952_1066511071_cca6b29b0253f105b76231d9c28fabe3.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812773_3157952_1066511071_cca6b29b0253f105b76231d9c28fabe3.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1066511071) and `type` in (4169) and hashtag_id in (492774966,492668766,538914404) Loaded 10 chid ids of type : 4169 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2256126232,2256126224,2256126221,2256126220,2256126223,2256126225,2256126229,2256126228,2256126222,2256126218) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2256126232,2256126224,2256126221,2256126220,2256126223,2256126225,2256126229,2256126228,2256126222,2256126218) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2256126232,2256126224,2256126221,2256126220,2256126223,2256126225,2256126229,2256126228,2256126222,2256126218) seulement à utiliser dans la step consolidation insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 10 chid ids of type : 2805 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.028315067291259766 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {1066511071: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 0.3281595706939697 time spend to save output : 8.106231689453125e-05 total time spend for step 1 : 0.32824063301086426 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1066511071: (0.0, 'Should be the crop_list due to order', 0)} Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2574 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2574 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2574 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2574 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (996751167) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 996751167 download finish for photo 996751167 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.17918610572814941 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:rle_unique_nms_with_priority Thu Sep 25 17:06:14 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812773_3157952_996751167_a4a67aed9b2473876b59443347f3912e.jpg': 996751167} map_photo_id_path_extension : {996751167: {'path': 'temp/1758812773_3157952_996751167_a4a67aed9b2473876b59443347f3912e.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812773_3157952_996751167_a4a67aed9b2473876b59443347f3912e.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 996751167) and `type` in (2596) and score>0.5and hashtag_id in (492622729,501120777) Loaded 91 chid ids of type : 2596 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1855152024,1947270239,1947270255,1947270247,1855152035,1947270267,1947270236,1855152019,1855152044,1947270245,1855152040,1855152025,1947270251,1855152027,1947270250,1855152020,1947270237,1855152029,1947270241,1855152058,1947270274,1855152062,1855152061,1947270275,1947270277,1855152055,1855152052,1947270261,1855152046,1947270265,1855152021,1947270238,1947270269,1855152045,1947270276,1947270257,1855152054,1855152031,1947270263,1855152023,1855156849,1947270240,1855152042,1947270249,1855152047,1947270273,1947270258,1855152050,1947270270,1855152034,1855152039,1947270259,1855152063,1947270272,1855152038,1947270252,1855152026,1947270242,1855152049,1947270256,1855152048,1947270262,1855152056,1947270266,1947270271,1855152037,1855156850,1947270253,1855152033,1947270246,1855152030,1855152041,1947270260,1855152057,1855152036,1947270268,1855152043,1855152065,1855152064,1947270254,1855152060,1855152032,1947270243,1855152059,1855152051,1855152053,1947270264,1855152022,1947270248,1947270244,1855152028) +++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1855152024,1947270239,1947270255,1947270247,1855152035,1947270267,1947270236,1855152019,1855152044,1947270245,1855152040,1855152025,1947270251,1855152027,1947270250,1855152020,1947270237,1855152029,1947270241,1855152058,1947270274,1855152062,1855152061,1947270275,1947270277,1855152055,1855152052,1947270261,1855152046,1947270265,1855152021,1947270238,1947270269,1855152045,1947270276,1947270257,1855152054,1855152031,1947270263,1855152023,1855156849,1947270240,1855152042,1947270249,1855152047,1947270273,1947270258,1855152050,1947270270,1855152034,1855152039,1947270259,1855152063,1947270272,1855152038,1947270252,1855152026,1947270242,1855152049,1947270256,1855152048,1947270262,1855152056,1947270266,1947270271,1855152037,1855156850,1947270253,1855152033,1947270246,1855152030,1855152041,1947270260,1855152057,1855152036,1947270268,1855152043,1855152065,1855152064,1947270254,1855152060,1855152032,1947270243,1855152059,1855152051,1855152053,1947270264,1855152022,1947270248,1947270244,1855152028) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1855152024,1947270239,1947270255,1947270247,1855152035,1947270267,1947270236,1855152019,1855152044,1947270245,1855152040,1855152025,1947270251,1855152027,1947270250,1855152020,1947270237,1855152029,1947270241,1855152058,1947270274,1855152062,1855152061,1947270275,1947270277,1855152055,1855152052,1947270261,1855152046,1947270265,1855152021,1947270238,1947270269,1855152045,1947270276,1947270257,1855152054,1855152031,1947270263,1855152023,1855156849,1947270240,1855152042,1947270249,1855152047,1947270273,1947270258,1855152050,1947270270,1855152034,1855152039,1947270259,1855152063,1947270272,1855152038,1947270252,1855152026,1947270242,1855152049,1947270256,1855152048,1947270262,1855152056,1947270266,1947270271,1855152037,1855156850,1947270253,1855152033,1947270246,1855152030,1855152041,1947270260,1855152057,1855152036,1947270268,1855152043,1855152065,1855152064,1947270254,1855152060,1855152032,1947270243,1855152059,1855152051,1855152053,1947270264,1855152022,1947270248,1947270244,1855152028) nb_obj : 43 nb_hashtags : 2 time to prepare the origin masks : 13.943848848342896 time for calcul the mask position with numpy : 0.17674660682678223 nb_pixel_total : 5233657 time to create 1 rle with new method : 0.4577524662017822 time for calcul the mask position with numpy : 0.032739877700805664 nb_pixel_total : 11972 time to create 1 rle with old method : 0.013283967971801758 time for calcul the mask position with numpy : 0.033278465270996094 nb_pixel_total : 15054 time to create 1 rle with old method : 0.016370773315429688 time for calcul the mask position with numpy : 0.03298687934875488 nb_pixel_total : 13954 time to create 1 rle with old method : 0.014624834060668945 time for calcul the mask position with numpy : 0.03144955635070801 nb_pixel_total : 4888 time to create 1 rle with old method : 0.005282402038574219 time for calcul the mask position with numpy : 0.04124045372009277 nb_pixel_total : 1188492 time to create 1 rle with new method : 0.37564706802368164 time for calcul the mask position with numpy : 0.03650093078613281 nb_pixel_total : 184585 time to create 1 rle with new method : 0.40570831298828125 time for calcul the mask position with numpy : 0.03294777870178223 nb_pixel_total : 18620 time to create 1 rle with old method : 0.020593881607055664 time for calcul the mask position with numpy : 0.03297162055969238 nb_pixel_total : 62945 time to create 1 rle with old method : 0.06928396224975586 time for calcul the mask position with numpy : 0.03312969207763672 nb_pixel_total : 9427 time to create 1 rle with old method : 0.010277032852172852 time for calcul the mask position with numpy : 0.0325164794921875 nb_pixel_total : 9081 time to create 1 rle with old method : 0.009499549865722656 time for calcul the mask position with numpy : 0.03151226043701172 nb_pixel_total : 15987 time to create 1 rle with old method : 0.017339706420898438 time for calcul the mask position with numpy : 0.03375601768493652 nb_pixel_total : 33276 time to create 1 rle with old method : 0.03737068176269531 time for calcul the mask position with numpy : 0.03256034851074219 nb_pixel_total : 17533 time to create 1 rle with old method : 0.019031286239624023 time for calcul the mask position with numpy : 0.03148794174194336 nb_pixel_total : 4876 time to create 1 rle with old method : 0.005098104476928711 time for calcul the mask position with numpy : 0.030962467193603516 nb_pixel_total : 25226 time to create 1 rle with old method : 0.026032447814941406 time for calcul the mask position with numpy : 0.033499717712402344 nb_pixel_total : 30773 time to create 1 rle with old method : 0.032659053802490234 time for calcul the mask position with numpy : 0.031731605529785156 nb_pixel_total : 65671 time to create 1 rle with old method : 0.0676429271697998 time for calcul the mask position with numpy : 0.031595706939697266 nb_pixel_total : 12230 time to create 1 rle with old method : 0.013482809066772461 time for calcul the mask position with numpy : 0.03182482719421387 nb_pixel_total : 29560 time to create 1 rle with old method : 0.031751155853271484 time for calcul the mask position with numpy : 0.03199291229248047 nb_pixel_total : 14310 time to create 1 rle with old method : 0.0156252384185791 time for calcul the mask position with numpy : 0.03240156173706055 nb_pixel_total : 15117 time to create 1 rle with old method : 0.0164337158203125 time for calcul the mask position with numpy : 0.03565669059753418 nb_pixel_total : 301487 time to create 1 rle with new method : 0.42312073707580566 time for calcul the mask position with numpy : 0.035103559494018555 nb_pixel_total : 29821 time to create 1 rle with old method : 0.03255891799926758 time for calcul the mask position with numpy : 0.03181910514831543 nb_pixel_total : 40299 time to create 1 rle with old method : 0.04451251029968262 time for calcul the mask position with numpy : 0.032320499420166016 nb_pixel_total : 12680 time to create 1 rle with old method : 0.013971567153930664 time for calcul the mask position with numpy : 0.03183722496032715 nb_pixel_total : 9449 time to create 1 rle with old method : 0.010087013244628906 time for calcul the mask position with numpy : 0.03200125694274902 nb_pixel_total : 15168 time to create 1 rle with old method : 0.01598978042602539 time for calcul the mask position with numpy : 0.03136634826660156 nb_pixel_total : 11140 time to create 1 rle with old method : 0.012093544006347656 time for calcul the mask position with numpy : 0.032205820083618164 nb_pixel_total : 29065 time to create 1 rle with old method : 0.031392812728881836 time for calcul the mask position with numpy : 0.03289628028869629 nb_pixel_total : 22774 time to create 1 rle with old method : 0.023354768753051758 time for calcul the mask position with numpy : 0.03159070014953613 nb_pixel_total : 13880 time to create 1 rle with old method : 0.014715909957885742 time for calcul the mask position with numpy : 0.0334630012512207 nb_pixel_total : 155366 time to create 1 rle with new method : 0.4550163745880127 time for calcul the mask position with numpy : 0.032511234283447266 nb_pixel_total : 63941 time to create 1 rle with old method : 0.06885457038879395 time for calcul the mask position with numpy : 0.032347917556762695 nb_pixel_total : 7836 time to create 1 rle with old method : 0.008646011352539062 time for calcul the mask position with numpy : 0.0324556827545166 nb_pixel_total : 7460 time to create 1 rle with old method : 0.007840633392333984 time for calcul the mask position with numpy : 0.031504154205322266 nb_pixel_total : 44600 time to create 1 rle with old method : 0.04780745506286621 time for calcul the mask position with numpy : 0.03200984001159668 nb_pixel_total : 11879 time to create 1 rle with old method : 0.013005971908569336 time for calcul the mask position with numpy : 0.031717538833618164 nb_pixel_total : 44195 time to create 1 rle with old method : 0.04802966117858887 time for calcul the mask position with numpy : 0.03158092498779297 nb_pixel_total : 23652 time to create 1 rle with old method : 0.02537846565246582 time for calcul the mask position with numpy : 0.03165006637573242 nb_pixel_total : 30006 time to create 1 rle with old method : 0.03202509880065918 time for calcul the mask position with numpy : 0.03140711784362793 nb_pixel_total : 15880 time to create 1 rle with old method : 0.017596006393432617 time for calcul the mask position with numpy : 0.031646728515625 nb_pixel_total : 29845 time to create 1 rle with old method : 0.032141685485839844 time for calcul the mask position with numpy : 0.03174591064453125 nb_pixel_total : 144263 time to create 1 rle with old method : 0.15323829650878906 create new chi : 4.929987192153931 proportion hashtag : error 0.14340033061450744 proportion hashtag : environment 0.209023722085841 proportion hashtag : pet_fonce 0.6475759472996516 time to delete rle : 0.4828512668609619 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 44 chid ids of type : 2805 Number RLEs to save : 27884 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975220857', '0', '0', '3280') ... last line : ('3975220900', '2459', '2462', '1') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! save time : 1.523029088973999 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {996751167: (1.0, 'Should be the crop_list due to order', 1.0)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 21.119402647018433 time spend to save output : 0.00017189979553222656 total time spend for step 1 : 21.119574546813965 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {996751167: (1.0, 'Should be the crop_list due to order', 1.0)} batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 998957128,996751167) and `type` in (2805) Loaded 54 chid ids of type : 2805 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975220837,3975220838,3975220839,3975220840,3975220841,3975220842,3975220843,3975220844,3975220845,3975220846,3975220857,3975220858,3975220859,3975220860,3975220861,3975220862,3975220863,3975220864,3975220865,3975220866,3975220867,3975220868,3975220869,3975220870,3975220871,3975220872,3975220873,3975220874,3975220875,3975220876,3975220877,3975220878,3975220879,3975220880,3975220881,3975220882,3975220883,3975220884,3975220885,3975220886,3975220887,3975220888,3975220889,3975220890,3975220891,3975220892,3975220893,3975220894,3975220895,3975220896,3975220897,3975220898,3975220899,3975220900) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975220837,3975220838,3975220839,3975220840,3975220841,3975220842,3975220843,3975220844,3975220845,3975220846,3975220857,3975220858,3975220859,3975220860,3975220861,3975220862,3975220863,3975220864,3975220865,3975220866,3975220867,3975220868,3975220869,3975220870,3975220871,3975220872,3975220873,3975220874,3975220875,3975220876,3975220877,3975220878,3975220879,3975220880,3975220881,3975220882,3975220883,3975220884,3975220885,3975220886,3975220887,3975220888,3975220889,3975220890,3975220891,3975220892,3975220893,3975220894,3975220895,3975220896,3975220897,3975220898,3975220899,3975220900) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975220837,3975220838,3975220839,3975220840,3975220841,3975220842,3975220843,3975220844,3975220845,3975220846,3975220857,3975220858,3975220859,3975220860,3975220861,3975220862,3975220863,3975220864,3975220865,3975220866,3975220867,3975220868,3975220869,3975220870,3975220871,3975220872,3975220873,3975220874,3975220875,3975220876,3975220877,3975220878,3975220879,3975220880,3975220881,3975220882,3975220883,3975220884,3975220885,3975220886,3975220887,3975220888,3975220889,3975220890,3975220891,3975220892,3975220893,3975220894,3975220895,3975220896,3975220897,3975220898,3975220899,3975220900) SELECT * FROM MTRPhoto.photo_carac_ratio WHERE hashtag_type=2805; ############################### TEST random_deformation ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2896 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2896 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2896 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2896 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : random_deformation list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3288640) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3288640) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1006293201, 'portfolio_id': 3288640}] map_portfolio_id_photo_id: {3288640: [1006293201]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1006293201 download finish for photo 1006293201 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.125077486038208 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:random_deformation Thu Sep 25 17:06:35 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812795_3157952_1006293201_ac133c4479fdab9f9d690f3bcbac83df.jpg': 1006293201} map_photo_id_path_extension : {1006293201: {'path': 'temp/1758812795_3157952_1006293201_ac133c4479fdab9f9d690f3bcbac83df.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step random deformation get user info for portfolio 3288640 on traite la photo : 1006293201 About to upload 4 photos upload in portfolio : 3287159 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812797_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 4 photos in the portfolio 3287159 time of upload the photos Elapsed time : 1.674985647201538 After datou_step_exec type output : time spend for datou_step_exec : 3.6752421855926514 time spend to save output : 6.127357482910156e-05 total time spend for step 1 : 3.6753034591674805 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : random_deformation we use saveGeneral [1006293201] map_info['map_portfolio_photo'] : {3288640: [1006293201]} final : True mtd_id 2896 list_pids : [1006293201] Looping around the photos to save general results len do output : 4 /1386160540Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386160542Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386160543Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386160544Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('2896', None, None, None, None, None, None, None, None) ('2896', '3288640', '1006293201', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('2896', None, '1386160540', 'None', None, None, None, None, None), ('2896', None, '1386160542', 'None', None, None, None, None, None), ('2896', None, '1386160543', 'None', None, None, None, None, None), ('2896', None, '1386160544', 'None', None, None, None, None, None), ('2896', '3288640', '1006293201', None, None, None, None, None, None)] time used for this insertion : 0.011939525604248047 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1386160540: ['1006293201', 'temp/1006293201_random_deformation_0.png', []], 1386160542: ['1006293201', 'temp/1006293201_random_deformation_1.png', []], 1386160543: ['1006293201', 'temp/1006293201_random_deformation_2.png', []], 1386160544: ['1006293201', 'temp/1006293201_random_deformation_3.png', []]} name 'urllib' is not defined can't unload the photo : 1006293201 t ############################### TEST tile ################################ test tile avec chi rectangles, rles, polygones Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2985 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2985 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2985 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2985 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : tile list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3341855) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3341855) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1008283903, 'portfolio_id': 3341855}] map_portfolio_id_photo_id: {3341855: [1008283903]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1008283903 download finish for photo 1008283903 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.27605175971984863 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:tile Thu Sep 25 17:06:39 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg': 1008283903} map_photo_id_path_extension : {1008283903: {'path': 'temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} verbose : True param_json : {'ETA': 3600, 'new_width': 640, 'new_height': 640, 'token': '5d93a4b2b749464f208c339a1324b78f', 'stride': 0, 'stride_relative': 0, 'portfolio_name': 'results_test_tile', 'crop_hashtag_type_tiled': 3243, 'crop_hashtag_type': 3242, 'arg_aux_upload': {'type_upload': 'python'}, 'host': 'www.fotonower.com'} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {3242: 3243} TO DEPRECATE VR 14-6-18 map_filenames : {1008283903: 'temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 0 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1008283903,1008283903) and `type` in (3242) Loaded 2 chid ids of type : 3242 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1929991390,1929991392) ++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1929991390,1929991392) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1929991390,1929991392) created feed_id_new_photos : 27233734 with name results_test_tile feed_id_new_photos : 27233734 filename : temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg photo_id : 1008283903 height_image_input : 2464 width_image_input : 3280 new_width : 640 new_height : 640 stride : 0 stride_relative : 0 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 2 list_bib_to_crops : 24 [(0, 640, 0, 640, 0), (0, 640, 640, 1280, 1), (0, 640, 1280, 1920, 2), (0, 640, 1824, 2464, 3), (640, 1280, 0, 640, 4), (640, 1280, 640, 1280, 5), (640, 1280, 1280, 1920, 6), (640, 1280, 1824, 2464, 7), (1280, 1920, 0, 640, 8), (1280, 1920, 640, 1280, 9), (1280, 1920, 1280, 1920, 10), (1280, 1920, 1824, 2464, 11), (1920, 2560, 0, 640, 12), (1920, 2560, 640, 1280, 13), (1920, 2560, 1280, 1920, 14), (1920, 2560, 1824, 2464, 15), (2560, 3200, 0, 640, 16), (2560, 3200, 640, 1280, 17), (2560, 3200, 1280, 1920, 18), (2560, 3200, 1824, 2464, 19), (2640, 3280, 0, 640, 20), (2640, 3280, 640, 1280, 21), (2640, 3280, 1280, 1920, 22), (2640, 3280, 1824, 2464, 23)] calcul des nouveaux crops pour le tile x0:0,x1:640,y0:0,y1:640 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:0,x1:640,y0:640,y1:1280 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:0,x1:640,y0:1280,y1:1920 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:0,x1:640,y0:1824,y1:2464 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:640,x1:1280,y0:0,y1:640 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:640,x1:1280,y0:640,y1:1280 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:640,x1:1280,y0:1280,y1:1920 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:640,x1:1280,y0:1824,y1:2464 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1280,x1:1920,y0:0,y1:640 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1280,x1:1920,y0:640,y1:1280 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1280,x1:1920,y0:1280,y1:1920 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1280,x1:1920,y0:1824,y1:2464 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1920,x1:2560,y0:0,y1:640 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1920,x1:2560,y0:640,y1:1280 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1920,x1:2560,y0:1280,y1:1920 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:1920,x1:2560,y0:1824,y1:2464 calcul avec la methode originale chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2560,x1:3200,y0:0,y1:640 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2560,x1:3200,y0:640,y1:1280 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2560,x1:3200,y0:1280,y1:1920 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2560,x1:3200,y0:1824,y1:2464 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2640,x1:3280,y0:0,y1:640 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2640,x1:3280,y0:640,y1:1280 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2640,x1:3280,y0:1280,y1:1920 chi selectionnes : [] calcul des nouveaux crops pour le tile x0:2640,x1:3280,y0:1824,y1:2464 chi selectionnes : [] new_crops_tiles : 24 crop_transformed : 7 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) [(1008283903, 2090988864, 17, 0, 640, 0, 640, 1.0), (1008283903, 2090988864, 17, 0, 640, 640, 1280, 1.0), (1008283903, 2090988864, 17, 0, 640, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 0, 640, 1824, 2464, 1.0), (1008283903, 2090988864, 17, 640, 1280, 0, 640, 1.0), (1008283903, 2090988864, 17, 640, 1280, 640, 1280, 1.0), (1008283903, 2090988864, 17, 640, 1280, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 640, 1280, 1824, 2464, 1.0), (1008283903, 2090988864, 17, 1280, 1920, 0, 640, 1.0), (1008283903, 2090988864, 17, 1280, 1920, 640, 1280, 1.0), (1008283903, 2090988864, 17, 1280, 1920, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 1280, 1920, 1824, 2464, 1.0), (1008283903, 2090988864, 17, 1920, 2560, 0, 640, 1.0), (1008283903, 2090988864, 17, 1920, 2560, 640, 1280, 1.0), (1008283903, 2090988864, 17, 1920, 2560, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 1920, 2560, 1824, 2464, 1.0), (1008283903, 2090988864, 17, 2560, 3200, 0, 640, 1.0), (1008283903, 2090988864, 17, 2560, 3200, 640, 1280, 1.0), (1008283903, 2090988864, 17, 2560, 3200, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 2560, 3200, 1824, 2464, 1.0), (1008283903, 2090988864, 17, 2640, 3280, 0, 640, 1.0), (1008283903, 2090988864, 17, 2640, 3280, 640, 1280, 1.0), (1008283903, 2090988864, 17, 2640, 3280, 1280, 1920, 1.0), (1008283903, 2090988864, 17, 2640, 3280, 1824, 2464, 1.0)] list_photo_ids_cropped : [1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903, 1008283903] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903,1008283903) and `type` in (17) Loaded 24 chid ids of type : 17 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1930014930,1930014931,1930014932,1930014933,1930014934,1930014935,1930014936,1930014937,1930014938,1930014939,1930014940,1930014941,1930014942,1930014943,1930014944,1930014945,1930014946,1930014947,1930014948,1930014949,1930014950,1930014951,1930014952,1930014953) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1930014930,1930014931,1930014932,1930014933,1930014934,1930014935,1930014936,1930014937,1930014938,1930014939,1930014940,1930014941,1930014942,1930014943,1930014944,1930014945,1930014946,1930014947,1930014948,1930014949,1930014950,1930014951,1930014952,1930014953) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1930014930,1930014931,1930014932,1930014933,1930014934,1930014935,1930014936,1930014937,1930014938,1930014939,1930014940,1930014941,1930014942,1930014943,1930014944,1930014945,1930014946,1930014947,1930014948,1930014949,1930014950,1930014951,1930014952,1930014953) treat the image : temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg , 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 before upload mediasElapsed time : 0.3037586212158203 on upload les photos avec python init cache_photo without model_param we have 24 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812807_3157952 batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 157268, 1386160641, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 30453291, 'jpg', UNHEX('d16cfbf93a6864f1bc03962e0e23bcb1')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 148520, 1386160643, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 81717181, 'jpg', UNHEX('ce2c4f782965b063d46e106986f3b2e4')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 150434, 1386160644, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 98588006, 'jpg', UNHEX('6dc06165a42b8d0c0252ddaf88e7e6cb')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 159038, 1386160645, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 73501486, 'jpg', UNHEX('9fc09702addb3a343c682f2f2b2db5c4')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 140881, 1386160647, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 94637820, 'jpg', UNHEX('38c52b81ea7fbfc09f7a9fe92cb6c8cc')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 132017, 1386160648, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 18332974, 'jpg', UNHEX('8d019051d3be58f0374749fb06f24661')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 133779, 1386160649, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 43336960, 'jpg', UNHEX('9238291edac074dfa5e770261348ab94')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 142456, 1386160651, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 47772107, 'jpg', UNHEX('2e93baee3662924b59de631afb8c583f')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 138689, 1386160652, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 36073918, 'jpg', UNHEX('ea4002f70a9c5306758d8bd738566106')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 133572, 1386160653, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 50666743, 'jpg', UNHEX('12a46bd6865754d684eab42f2de71630')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 128714, 1386160654, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 43556728, 'jpg', UNHEX('a9e59570c3d2a739997b39ea79a20dc6')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 146231, 1386160656, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 91830827, 'jpg', UNHEX('6514ae9377f60a30175ac1f0b8e66126')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 148032, 1386160657, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 2001971, 'jpg', UNHEX('c76ce19692a6b6bb66fc05b5e85bb261')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 140830, 1386160658, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 82859387, 'jpg', UNHEX('8a1ab3fedcce7d87a2e088800cd3a285')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 127080, 1386160660, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 75445632, 'jpg', UNHEX('a322678f502639c33ff5067f95cf955d')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 151617, 1386160661, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 72928702, 'jpg', UNHEX('2f0a311219a9488a7480b85a9d340d3b')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 155573, 1386160662, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 99264506, 'jpg', UNHEX('5771dfcd856014c9506f9ed2ed99a1ad')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 150612, 1386160664, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 51994065, 'jpg', UNHEX('8f67fbe0b2aebab34cb80ea267c77ca5')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 154183, 1386160665, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 60051715, 'jpg', UNHEX('95c8a4d815fadce72770e6dd1f261950')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 160790, 1386160666, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 80516021, 'jpg', UNHEX('334a2ce960b42e11129b215fddfe668c')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 158111, 1386160668, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 19682820, 'jpg', UNHEX('f8f501b9dd4a98e0a17c364a01b2d488')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 152143, 1386160669, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 9586857, 'jpg', UNHEX('4d2b7affdc9bdce256bfa64a0655054d')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 155690, 1386160670, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 27133512, 'jpg', UNHEX('33307fc437c37b583118e7a65c073e4d')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! batch_size : 0, verbose : True, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg INSERT IGNORE INTO MTRUser.mtr_fotonower_photos_opt (`height`, `width`, `size_object`, `photo_id`, `base_url`, `date`, `chi_id`, `type_extension`, `hash`) VALUES (640, 640, 162499, 1386160672, 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com', '2025/9/25', 76233815, 'jpg', UNHEX('695cb643e5515ce4e7575a2c0a2454b9')) ON DUPLICATE KEY UPDATE `height`=values(`height`), `width`=values(`width`), `size_object`=values(`size_object`), `photo_id`=values(`photo_id`), `base_url`=values(`base_url`), `date`=values(`date`), `chi_id`=values(`chi_id`), `type_extension`=values(`type_extension`), `hash`=values(`hash`) This is a hack ! INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `mtr_user_id`, `created_at`) VALUES (27233734, 1386160641, 0, NOW()),(27233734, 1386160643, 0, NOW()),(27233734, 1386160644, 0, NOW()),(27233734, 1386160645, 0, NOW()),(27233734, 1386160647, 0, NOW()),(27233734, 1386160648, 0, NOW()),(27233734, 1386160649, 0, NOW()),(27233734, 1386160651, 0, NOW()),(27233734, 1386160652, 0, NOW()),(27233734, 1386160653, 0, NOW()),(27233734, 1386160654, 0, NOW()),(27233734, 1386160656, 0, NOW()),(27233734, 1386160657, 0, NOW()),(27233734, 1386160658, 0, NOW()),(27233734, 1386160660, 0, NOW()),(27233734, 1386160661, 0, NOW()),(27233734, 1386160662, 0, NOW()),(27233734, 1386160664, 0, NOW()),(27233734, 1386160665, 0, NOW()),(27233734, 1386160666, 0, NOW()),(27233734, 1386160668, 0, NOW()),(27233734, 1386160669, 0, NOW()),(27233734, 1386160670, 0, NOW()),(27233734, 1386160672, 0, NOW()) 24 we have uploaded 24 photos in the portfolio 27233734 Importing ! upload mediasElapsed time : 7.935831785202026 , 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [(1930014930, 1386160641, 0), (1930014931, 1386160643, 0), (1930014932, 1386160644, 0), (1930014933, 1386160645, 0), (1930014934, 1386160647, 0), (1930014935, 1386160648, 0), (1930014936, 1386160649, 0), (1930014937, 1386160651, 0), (1930014938, 1386160652, 0), (1930014939, 1386160653, 0), (1930014940, 1386160654, 0), (1930014941, 1386160656, 0), (1930014942, 1386160657, 0), (1930014943, 1386160658, 0), (1930014944, 1386160660, 0), (1930014945, 1386160661, 0), (1930014946, 1386160662, 0), (1930014947, 1386160664, 0), (1930014948, 1386160665, 0), (1930014949, 1386160666, 0), (1930014950, 1386160668, 0), (1930014951, 1386160669, 0), (1930014952, 1386160670, 0), (1930014953, 1386160672, 0)] Saving 7 CHIs. list_chi_tile : [": {'photo_id': 1386160653, 'hashtag_id': 511548407, 'type': 3243, 'x0': 180, 'x1': 640, 'y0': 611, 'y1': 640, 'score': 1.0, 'id': 0, 'points': ['311,640,292,640,268,640,240,640,229,640,223,640,188,640,181,640,180,640,186,640,211,640,216,640,211,640,211,640,244,640,242,640,261,640,275,640,298,640,357,640,380,640,409,640,548,640,557,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,635,640,628,640,628,576,621,543,612,490,611,424,621,352,640', '311,640,292,640,268,640,240,640,229,640,223,640,188,640,181,640,180,640,186,640,211,640,216,640,211,640,211,640,244,640,242,640,261,640,275,640,298,640,357,640,380,640,409,640,548,640,557,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,635,640,628,640,628,576,621,543,612,490,611,424,621,352,640'], 'sub_photo_id': 0, 'rles': [[1929991390, 487, 611, 30], [1929991390, 481, 612, 64], [1929991390, 474, 613, 75], [1929991390, 467, 614, 86], [1929991390, 461, 615, 95], [1929991390, 454, 616, 106], [1929991390, 448, 617, 116], [1929991390, 441, 618, 126], [1929991390, 434, 619, 137], [1929991390, 428, 620, 147], [1929991390, 423, 621, 158], [1929991390, 419, 622, 171], [1929991390, 415, 623, 185], [1929991390, 411, 624, 198], [1929991390, 408, 625, 210], [1929991390, 404, 626, 224], [1929991390, 400, 627, 237], [1929991390, 396, 628, 244], [1929991390, 392, 629, 248], [1929991390, 389, 630, 251], [1929991390, 385, 631, 255], [1929991390, 381, 632, 259], [1929991390, 377, 633, 263], [1929991390, 374, 634, 266], [1929991390, 370, 635, 270], [1929991390, 366, 636, 274], [1929991390, 362, 637, 278], [1929991390, 359, 638, 281], [1929991390, 355, 639, 285]], 'hashtag': '', 'sum_segment': 0}", ": {'photo_id': 1386160654, 'hashtag_id': 511548407, 'type': 3243, 'x0': 180, 'x1': 640, 'y0': 0, 'y1': 640, 'score': 1.0, 'id': 0, 'points': ['311,11,292,25,268,58,240,82,229,100,223,127,188,148,181,171,180,226,186,327,211,393,216,463,211,472,211,487,238,640,244,640,242,640,261,640,275,640,298,640,357,640,380,640,409,640,548,640,557,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,625,640,566,640,542,640,454,640,388,640,346,640,295,640,246,640,125,640,99,640,63,640,28,640,27,640,17,640,8,640,9,640,0,640,0,640,0,640,0,576,0,543,0,490,0,424,0,352,0', '311,11,292,25,268,58,240,82,229,100,223,127,188,148,181,171,180,226,186,327,211,393,216,463,211,472,211,487,238,640,244,640,242,640,261,640,275,640,298,640,357,640,380,640,409,640,548,640,557,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,640,625,640,566,640,542,640,454,640,388,640,346,640,295,640,246,640,125,640,99,640,63,640,28,640,27,640,17,640,8,640,9,640,0,640,0,640,0,640,0,576,0,543,0,490,0,424,0,352,0'], 'sub_photo_id': 0, 'rles': [[1929991390, 351, 0, 289], [1929991390, 347, 1, 293], [1929991390, 344, 2, 296], [1929991390, 340, 3, 300], [1929991390, 336, 4, 304], [1929991390, 332, 5, 308], [1929991390, 328, 6, 312], [1929991390, 325, 7, 315], [1929991390, 321, 8, 319], [1929991390, 317, 9, 323], [1929991390, 313, 10, 327], [1929991390, 311, 11, 329], [1929991390, 309, 12, 331], [1929991390, 308, 13, 332], [1929991390, 307, 14, 333], [1929991390, 305, 15, 335], 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[1929991390, 0, 432, 253], [1929991390, 0, 433, 253], [1929991390, 0, 434, 253], [1929991390, 0, 435, 253], [1929991390, 0, 436, 253], [1929991390, 0, 437, 253], [1929991390, 0, 438, 253], [1929991390, 0, 439, 253], [1929991390, 0, 440, 253], [1929991390, 0, 441, 253], [1929991390, 0, 442, 253], [1929991390, 0, 443, 253], [1929991390, 0, 444, 253], [1929991390, 0, 445, 253], [1929991390, 0, 446, 253], [1929991390, 0, 447, 252], [1929991390, 0, 448, 252], [1929991390, 0, 449, 252], [1929991390, 0, 450, 252], [1929991390, 0, 451, 252], [1929991390, 0, 452, 251], [1929991390, 0, 453, 251], [1929991390, 0, 454, 251], [1929991390, 0, 455, 251], [1929991390, 0, 456, 251], [1929991390, 0, 457, 250], [1929991390, 0, 458, 250], [1929991390, 0, 459, 250], [1929991390, 0, 460, 250], [1929991390, 0, 461, 250], [1929991390, 0, 462, 249], [1929991390, 0, 463, 249], [1929991390, 0, 464, 249], [1929991390, 0, 465, 249], [1929991390, 0, 466, 249], [1929991390, 0, 467, 248], [1929991390, 0, 468, 248], [1929991390, 0, 469, 248], [1929991390, 0, 470, 248], [1929991390, 0, 471, 248], [1929991390, 0, 472, 247], [1929991390, 0, 473, 247], [1929991390, 0, 474, 247], [1929991390, 0, 475, 247], [1929991390, 0, 476, 247], [1929991390, 0, 477, 246], [1929991390, 0, 478, 246], [1929991390, 0, 479, 246], [1929991390, 0, 480, 246], [1929991390, 0, 481, 246], [1929991390, 0, 482, 245], [1929991390, 0, 483, 245], [1929991390, 0, 484, 245], [1929991390, 0, 485, 245], [1929991390, 0, 486, 245], [1929991390, 0, 487, 245], [1929991390, 0, 488, 245], [1929991390, 0, 489, 245], [1929991390, 0, 490, 245], [1929991390, 0, 491, 245], [1929991390, 0, 492, 245], [1929991390, 0, 493, 245], [1929991390, 0, 494, 245], [1929991390, 0, 495, 245], [1929991390, 0, 496, 245], [1929991390, 0, 497, 245], [1929991390, 0, 498, 245], [1929991390, 0, 499, 245], [1929991390, 0, 500, 245], [1929991390, 0, 501, 245], [1929991390, 0, 502, 246], [1929991390, 0, 503, 246], [1929991390, 0, 504, 246], [1929991390, 0, 505, 246], [1929991390, 0, 506, 246], [1929991390, 0, 507, 246], [1929991390, 0, 508, 246], [1929991390, 0, 509, 246], [1929991390, 0, 510, 246], [1929991390, 0, 511, 246], [1929991390, 0, 512, 246], [1929991390, 0, 513, 246], [1929991390, 0, 514, 246], [1929991390, 0, 515, 246], [1929991390, 0, 516, 246], [1929991390, 0, 517, 246], [1929991390, 0, 518, 246], [1929991390, 0, 519, 245], [1929991390, 0, 520, 245], [1929991390, 0, 521, 244], [1929991390, 16, 522, 228], [1929991390, 44, 523, 152], [1929991390, 202, 523, 41], [1929991390, 62, 524, 124], [1929991390, 205, 524, 38], [1929991390, 68, 525, 108], [1929991390, 209, 525, 33], [1929991390, 75, 526, 91], [1929991390, 212, 526, 30], [1929991390, 82, 527, 74], [1929991390, 215, 527, 26], [1929991390, 88, 528, 58], [1929991390, 218, 528, 23], [1929991390, 95, 529, 41], [1929991390, 222, 529, 18], [1929991390, 102, 530, 24], [1929991390, 225, 530, 8], [1929991390, 108, 531, 8]], 'hashtag': '', 'sum_segment': 0}"] insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 7 chid ids of type : 3243 INSERT IGNORE INTO MTRPhoto.crop_polygon_points (`crop_hashtag_id`, `points`) VALUES (%s, %s) Number RLEs to save : 2937 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975221086', '487', '611', '30') ... last line : ('3975221092', '108', '531', '8') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! end of tileElapsed time : 8.172931432723999 map_pid_results : {'1386160641': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_0.jpg'], '1386160643': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_1.jpg'], '1386160644': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_2.jpg'], '1386160645': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_3.jpg'], '1386160647': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_4.jpg'], '1386160648': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_5.jpg'], '1386160649': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_6.jpg'], '1386160651': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_7.jpg'], '1386160652': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_8.jpg'], '1386160653': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_9.jpg'], '1386160654': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_10.jpg'], '1386160656': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_11.jpg'], '1386160657': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_12.jpg'], '1386160658': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_13.jpg'], '1386160660': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_14.jpg'], '1386160661': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_15.jpg'], '1386160662': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_16.jpg'], '1386160664': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_17.jpg'], '1386160665': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_18.jpg'], '1386160666': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_19.jpg'], '1386160668': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_20.jpg'], '1386160669': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_21.jpg'], '1386160670': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_22.jpg'], '1386160672': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_23.jpg']} After datou_step_exec type output : time spend for datou_step_exec : 15.222333908081055 time spend to save output : 7.557868957519531e-05 total time spend for step 1 : 15.22240948677063 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1386160641': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_0.jpg'], '1386160643': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_1.jpg'], '1386160644': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_2.jpg'], '1386160645': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_3.jpg'], '1386160647': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_4.jpg'], '1386160648': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_5.jpg'], '1386160649': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_6.jpg'], '1386160651': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_7.jpg'], '1386160652': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_8.jpg'], '1386160653': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_9.jpg'], '1386160654': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_10.jpg'], '1386160656': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_11.jpg'], '1386160657': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_12.jpg'], '1386160658': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_13.jpg'], '1386160660': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_14.jpg'], '1386160661': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_15.jpg'], '1386160662': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_16.jpg'], '1386160664': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_17.jpg'], '1386160665': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_18.jpg'], '1386160666': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_19.jpg'], '1386160668': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_20.jpg'], '1386160669': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_21.jpg'], '1386160670': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_22.jpg'], '1386160672': ['temp/1758812799_3157952_1008283903_6d008d31a1477b2e98cbafa96bd48e53_23.jpg']} batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1386160641,1386160643,1386160644,1386160645,1386160647,1386160648,1386160649,1386160651,1386160652,1386160653,1386160654,1386160656,1386160657,1386160658,1386160660,1386160661,1386160662,1386160664,1386160665,1386160666,1386160668,1386160669,1386160670,1386160672) and `type` in (3243) Loaded 7 chid ids of type : 3243 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975221086,3975221087,3975221088,3975221089,3975221090,3975221091,3975221092) ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221086. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221087. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221088. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221089. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221090. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221091. Ignored now ++WARNING : duplicated polygon, we should remove this data for chi_id : 3975221092. Ignored now SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975221086,3975221087,3975221088,3975221089,3975221090,3975221091,3975221092) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975221086,3975221087,3975221088,3975221089,3975221090,3975221091,3975221092) fin du test de tile ############################### TEST rotate_chi ################################ test rotate avec chi rectangles, rles, polygones Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2970 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2970 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2970 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2970 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : rotate list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3337029) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3337029) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1003369118, 'portfolio_id': 3337029}] map_portfolio_id_photo_id: {3337029: [1003369118]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1003369118 download finish for photo 1003369118 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.28951120376586914 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:rotate Thu Sep 25 17:06:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg': 1003369118} map_photo_id_path_extension : {1003369118: {'path': 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step_rotate ! Warning, new_feed_id is empty ! We are in a linear step without datou_depend ! rotate photos of 0,90,180,270 degres batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1003369118) and `type` in (3086) Loaded 16 chid ids of type : 3086 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1928951187,1928951188,1928951189,1928951190,1928951191,1928951192,1928951193,1928951194,1928951195,1928951196,1928951197,1928951198,1928951199,1928951200,1928951201,1928951202) ++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1928951187,1928951188,1928951189,1928951190,1928951191,1928951192,1928951193,1928951194,1928951195,1928951196,1928951197,1928951198,1928951199,1928951200,1928951201,1928951202) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1928951187,1928951188,1928951189,1928951190,1928951191,1928951192,1928951193,1928951194,1928951195,1928951196,1928951197,1928951198,1928951199,1928951200,1928951201,1928951202) map_chi : {1003369118: [, , , , , , , , , , , , , , , ]} feed_id_new_photos : 27233741 photo_id in download_rotate_and_save : 1003369118 list_chi_loc : 16 Use all angle ! Rotation of photo 1003369118 of 0 degree temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg [, , , , , , , , , , , , , , , ] 0 remove_crop_border : False version de PIL : 9.5.0 [[ 1. 0.] [-0. 1.]] 0 [[ 1. 0.] [-0. 1.]] shrink_image : False len(list_crops) : 16 time for calcul the mask position with numpy : 0.010157108306884766 nb_pixel_total : 110633 time to create 1 rle with old method : 0.11504364013671875 .time for calcul the mask position with numpy : 0.00878763198852539 nb_pixel_total : 15826 time to create 1 rle with old method : 0.016336679458618164 .time for calcul the mask position with numpy : 0.008332967758178711 nb_pixel_total : 5286 time to create 1 rle with old method : 0.005640745162963867 .time for calcul the mask position with numpy : 0.00890660285949707 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0017414093017578125 .time for calcul the mask position with numpy : 0.009184598922729492 nb_pixel_total : 105533 time to create 1 rle with old method : 0.10984206199645996 .time for calcul the mask position with numpy : 0.008381128311157227 nb_pixel_total : 4393 time to create 1 rle with old method : 0.004672050476074219 .time for calcul the mask position with numpy : 0.008412361145019531 nb_pixel_total : 632 time to create 1 rle with old method : 0.0007677078247070312 .time for calcul the mask position with numpy : 0.009151220321655273 nb_pixel_total : 62627 time to create 1 rle with old method : 0.06501054763793945 .time for calcul the mask position with numpy : 0.008668661117553711 nb_pixel_total : 33681 time to create 1 rle with old method : 0.034982919692993164 .time for calcul the mask position with numpy : 0.00867605209350586 nb_pixel_total : 37724 time to create 1 rle with old method : 0.03974175453186035 .time for calcul the mask position with numpy : 0.008968591690063477 nb_pixel_total : 48775 time to create 1 rle with old method : 0.05254483222961426 .time for calcul the mask position with numpy : 0.042901039123535156 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.4928121566772461 .time for calcul the mask position with numpy : 0.009499549865722656 nb_pixel_total : 2310 time to create 1 rle with old method : 0.0027060508728027344 .time for calcul the mask position with numpy : 0.008899211883544922 nb_pixel_total : 2256 time to create 1 rle with old method : 0.002591371536254883 .time for calcul the mask position with numpy : 0.010580301284790039 nb_pixel_total : 3112 time to create 1 rle with old method : 0.005177974700927734 .time for calcul the mask position with numpy : 0.008814334869384766 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0019893646240234375 .len(list_crops_rotate) : 16 list_crops_rotate : : {'photo_id': 0, 'hashtag_id': 493012381, 'type': 3230, 'x0': 0, 'x1': 574, 'y0': 1038, 'y1': 1438, 'score': 1.0, 'id': None, 'points': ['1,1038,97,1108,179,1182,245,1230,274,1204,337,1245,310,1279,313,1288,577,1440,-1,1438'], 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'hashtag': '', 'sum_segment': 0},: {'photo_id': 0, 'hashtag_id': 2107752406, 'type': 3230, 'x0': 538, 'x1': 671, 'y0': 13, 'y1': 46, 'score': 1.0, 'id': None, 'points': ['538,13,671,21,661,46,643,46,625,42,578,27'], 'sub_photo_id': 0, 'rles': [(-1, 538, 13, 9), (-1, 540, 14, 23), (-1, 543, 15, 37), (-1, 546, 16, 51), (-1, 549, 17, 64), (-1, 551, 18, 79), (-1, 554, 19, 93), (-1, 557, 20, 106), (-1, 560, 21, 112), (-1, 563, 22, 109), (-1, 566, 23, 105), (-1, 569, 24, 102), (-1, 571, 25, 99), (-1, 574, 26, 96), (-1, 577, 27, 93), (-1, 580, 28, 89), (-1, 583, 29, 86), (-1, 586, 30, 82), (-1, 589, 31, 79), (-1, 593, 32, 75), (-1, 596, 33, 71), (-1, 599, 34, 68), (-1, 602, 35, 64), (-1, 605, 36, 61), (-1, 608, 37, 58), (-1, 611, 38, 54), (-1, 615, 39, 50), (-1, 618, 40, 46), (-1, 621, 41, 43), (-1, 624, 42, 40), (-1, 628, 43, 35), (-1, 632, 44, 31), (-1, 637, 45, 25), (-1, 641, 46, 21)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': 0, 'hashtag_id': 2107752406, 'type': 3230, 'x0': 1112, 'x1': 1199, 'y0': 1234, 'y1': 1299, 'score': 1.0, 'id': None, 'points': ['1112,1257,1123,1261,1127,1279,1144,1279,1153,1279,1172,1290,1184,1299,1198,1296,1199,1282,1196,1273,1192,1266,1178,1255,1151,1234,1145,1234,1135,1239,1126,1242,1118,1248'], 'sub_photo_id': 0, 'rles': [(-1, 1145, 1234, 7), (-1, 1143, 1235, 10), (-1, 1141, 1236, 14), (-1, 1139, 1237, 17), (-1, 1137, 1238, 20), (-1, 1134, 1239, 25), (-1, 1131, 1240, 29), (-1, 1128, 1241, 33), (-1, 1126, 1242, 36), (-1, 1125, 1243, 39), (-1, 1123, 1244, 42), (-1, 1122, 1245, 44), (-1, 1121, 1246, 47), (-1, 1119, 1247, 50), (-1, 1118, 1248, 52), (-1, 1117, 1249, 54), (-1, 1117, 1250, 56), (-1, 1116, 1251, 58), (-1, 1115, 1252, 60), (-1, 1115, 1253, 62), (-1, 1114, 1254, 64), (-1, 1113, 1255, 66), (-1, 1113, 1256, 67), (-1, 1112, 1257, 70), (-1, 1114, 1258, 69), (-1, 1117, 1259, 67), (-1, 1119, 1260, 67), (-1, 1122, 1261, 65), (-1, 1123, 1262, 65), (-1, 1123, 1263, 66), (-1, 1124, 1264, 67), (-1, 1124, 1265, 68), (-1, 1124, 1266, 69), (-1, 1124, 1267, 70), (-1, 1125, 1268, 69), (-1, 1125, 1269, 70), (-1, 1125, 1270, 70), (-1, 1125, 1271, 71), (-1, 1125, 1272, 71), (-1, 1126, 1273, 71), (-1, 1126, 1274, 71), (-1, 1126, 1275, 72), (-1, 1126, 1276, 72), (-1, 1127, 1277, 71), (-1, 1127, 1278, 72), (-1, 1127, 1279, 72), (-1, 1154, 1280, 45), (-1, 1156, 1281, 44), (-1, 1158, 1282, 42), (-1, 1160, 1283, 40), (-1, 1161, 1284, 39), (-1, 1163, 1285, 37), (-1, 1165, 1286, 35), (-1, 1166, 1287, 34), (-1, 1168, 1288, 32), (-1, 1170, 1289, 29), (-1, 1172, 1290, 27), (-1, 1173, 1291, 26), (-1, 1175, 1292, 24), (-1, 1176, 1293, 23), (-1, 1177, 1294, 22), (-1, 1179, 1295, 20), (-1, 1180, 1296, 19), (-1, 1181, 1297, 15), (-1, 1183, 1298, 9), (-1, 1184, 1299, 3)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': 0, 'hashtag_id': 493012381, 'type': 3230, 'x0': 311, 'x1': 371, 'y0': 832, 'y1': 907, 'score': 1.0, 'id': None, 'points': ['311,841,362,907,371,901,347,864,356,855,352,841,346,832,328,837'], 'sub_photo_id': 0, 'rles': [(-1, 345, 832, 2), (-1, 341, 833, 7), (-1, 338, 834, 10), (-1, 334, 835, 15), (-1, 330, 836, 20), (-1, 326, 837, 24), (-1, 322, 838, 29), (-1, 318, 839, 34), (-1, 314, 840, 38), (-1, 311, 841, 42), (-1, 312, 842, 41), (-1, 313, 843, 41), (-1, 313, 844, 41), (-1, 314, 845, 40), (-1, 315, 846, 39), (-1, 316, 847, 39), (-1, 316, 848, 39), (-1, 317, 849, 38), (-1, 318, 850, 38), (-1, 319, 851, 37), (-1, 319, 852, 37), (-1, 320, 853, 36), (-1, 321, 854, 36), (-1, 322, 855, 35), (-1, 323, 856, 33), (-1, 323, 857, 32), (-1, 324, 858, 30), (-1, 325, 859, 28), (-1, 326, 860, 26), (-1, 326, 861, 25), (-1, 327, 862, 23), (-1, 328, 863, 21), (-1, 329, 864, 19), (-1, 330, 865, 19), (-1, 330, 866, 19), (-1, 331, 867, 19), (-1, 332, 868, 19), (-1, 333, 869, 18), (-1, 333, 870, 19), (-1, 334, 871, 19), (-1, 335, 872, 18), (-1, 336, 873, 18), (-1, 336, 874, 18), (-1, 337, 875, 18), (-1, 338, 876, 18), (-1, 339, 877, 17), (-1, 340, 878, 17), (-1, 340, 879, 18), (-1, 341, 880, 17), (-1, 342, 881, 17), (-1, 343, 882, 17), (-1, 343, 883, 17), (-1, 344, 884, 17), (-1, 345, 885, 17), (-1, 346, 886, 16), (-1, 347, 887, 16), (-1, 347, 888, 17), (-1, 348, 889, 16), (-1, 349, 890, 16), (-1, 350, 891, 16), (-1, 350, 892, 16), (-1, 351, 893, 16), (-1, 352, 894, 15), (-1, 353, 895, 15), (-1, 353, 896, 16), (-1, 354, 897, 15), (-1, 355, 898, 15), (-1, 356, 899, 15), (-1, 357, 900, 14), (-1, 357, 901, 15), (-1, 358, 902, 13), (-1, 359, 903, 10), (-1, 360, 904, 8), (-1, 360, 905, 6), (-1, 361, 906, 4), (-1, 362, 907, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1003369118 of 90 degree temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg [, , , , , , , , , , , , , , , ] 90 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] 90 [[ 6.123234e-17 1.000000e+00] [-1.000000e+00 6.123234e-17]] shrink_image : False len(list_crops) : 16 time for calcul the mask position with numpy : 0.009850025177001953 nb_pixel_total : 110633 time to create 1 rle with old method : 0.11346030235290527 .time for calcul the mask position with numpy : 0.008420944213867188 nb_pixel_total : 15826 time to create 1 rle with old method : 0.016798019409179688 .time for calcul the mask position with numpy : 0.010158300399780273 nb_pixel_total : 5286 time to create 1 rle with old method : 0.0057528018951416016 .time for calcul the mask position with numpy : 0.009120464324951172 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0018417835235595703 .time for calcul the mask position with numpy : 0.009090900421142578 nb_pixel_total : 105533 time to create 1 rle with old method : 0.11069464683532715 .time for calcul the mask position with numpy : 0.009022712707519531 nb_pixel_total : 4393 time to create 1 rle with old method : 0.0047948360443115234 .time for calcul the mask position with numpy : 0.009177923202514648 nb_pixel_total : 632 time to create 1 rle with old method : 0.0007221698760986328 .time for calcul the mask position with numpy : 0.011652708053588867 nb_pixel_total : 62627 time to create 1 rle with old method : 0.0741128921508789 .time for calcul the mask position with numpy : 0.00918889045715332 nb_pixel_total : 33681 time to create 1 rle with old method : 0.034745216369628906 .time for calcul the mask position with numpy : 0.008541107177734375 nb_pixel_total : 37724 time to create 1 rle with old method : 0.04134321212768555 .time for calcul the mask position with numpy : 0.013329744338989258 nb_pixel_total : 48775 time to create 1 rle with old method : 0.05016207695007324 .time for calcul the mask position with numpy : 0.11505866050720215 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.18504786491394043 .time for calcul the mask position with numpy : 0.008254766464233398 nb_pixel_total : 2310 time to create 1 rle with old method : 0.002466440200805664 .time for calcul the mask position with numpy : 0.009424924850463867 nb_pixel_total : 2256 time to create 1 rle with old method : 0.002382993698120117 .time for calcul the mask position with numpy : 0.008671760559082031 nb_pixel_total : 3112 time to create 1 rle with old method : 0.0034589767456054688 .time for calcul the mask position with numpy : 0.008499860763549805 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0019795894622802734 .len(list_crops_rotate) : 16 list_crops_rotate : : {'photo_id': -1, 'hashtag_id': 493012381, 'type': 3230, 'x0': 1038, 'x1': 1438, 'y0': 1584, 'y1': 2158, 'score': 1.0, 'id': None, 'points': ['1038,2157,1108,2061,1182,1979,1230,1913,1204,1884,1245,1821,1279,1848,1288,1845,1440,1581,1438,2159'], 'sub_photo_id': 0, 'rles': [(-1, 1438, 1584, 1), (-1, 1437, 1585, 2), (-1, 1437, 1586, 2), (-1, 1436, 1587, 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'score': 1.0, 'id': None, 'points': ['13,1620,21,1487,46,1497,46,1515,42,1533,27,1580'], 'sub_photo_id': 0, 'rles': [(-1, 21, 1487, 2), (-1, 21, 1488, 4), (-1, 21, 1489, 7), (-1, 21, 1490, 9), (-1, 21, 1491, 12), (-1, 21, 1492, 14), (-1, 21, 1493, 17), (-1, 21, 1494, 19), (-1, 21, 1495, 22), (-1, 20, 1496, 25), (-1, 20, 1497, 27), (-1, 20, 1498, 27), (-1, 20, 1499, 27), (-1, 20, 1500, 27), (-1, 20, 1501, 27), (-1, 20, 1502, 27), (-1, 20, 1503, 27), (-1, 20, 1504, 27), (-1, 20, 1505, 27), (-1, 20, 1506, 27), (-1, 20, 1507, 27), (-1, 20, 1508, 27), (-1, 20, 1509, 27), (-1, 20, 1510, 27), (-1, 20, 1511, 27), (-1, 19, 1512, 28), (-1, 19, 1513, 28), (-1, 19, 1514, 28), (-1, 19, 1515, 28), (-1, 19, 1516, 28), (-1, 19, 1517, 28), (-1, 19, 1518, 27), (-1, 19, 1519, 27), (-1, 19, 1520, 27), (-1, 19, 1521, 27), (-1, 19, 1522, 26), (-1, 19, 1523, 26), (-1, 19, 1524, 26), (-1, 19, 1525, 26), (-1, 19, 1526, 26), (-1, 19, 1527, 25), (-1, 19, 1528, 25), (-1, 18, 1529, 26), (-1, 18, 1530, 26), (-1, 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8), (-1, 1252, 1043, 7), (-1, 1254, 1044, 5), (-1, 1255, 1045, 3), (-1, 1257, 1046, 1)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -1, 'hashtag_id': 493012381, 'type': 3230, 'x0': 832, 'x1': 907, 'y0': 1787, 'y1': 1847, 'score': 1.0, 'id': None, 'points': ['841,1847,907,1796,901,1787,864,1811,855,1802,841,1806,832,1812,837,1830'], 'sub_photo_id': 0, 'rles': [(-1, 901, 1787, 1), (-1, 899, 1788, 4), (-1, 898, 1789, 5), (-1, 896, 1790, 8), (-1, 895, 1791, 10), (-1, 893, 1792, 12), (-1, 891, 1793, 15), (-1, 890, 1794, 17), (-1, 888, 1795, 19), (-1, 887, 1796, 21), (-1, 885, 1797, 22), (-1, 884, 1798, 22), (-1, 882, 1799, 22), (-1, 881, 1800, 22), (-1, 879, 1801, 23), (-1, 854, 1802, 2), (-1, 878, 1802, 22), (-1, 850, 1803, 7), (-1, 876, 1803, 23), (-1, 847, 1804, 11), (-1, 875, 1804, 23), (-1, 843, 1805, 16), (-1, 873, 1805, 24), (-1, 841, 1806, 19), (-1, 871, 1806, 24), (-1, 839, 1807, 22), (-1, 870, 1807, 24), (-1, 838, 1808, 24), (-1, 868, 1808, 25), (-1, 836, 1809, 27), (-1, 867, 1809, 24), (-1, 835, 1810, 29), (-1, 865, 1810, 25), (-1, 833, 1811, 56), (-1, 832, 1812, 55), (-1, 832, 1813, 54), (-1, 833, 1814, 52), (-1, 833, 1815, 51), (-1, 833, 1816, 49), (-1, 833, 1817, 48), (-1, 834, 1818, 46), (-1, 834, 1819, 44), (-1, 834, 1820, 43), (-1, 835, 1821, 41), (-1, 835, 1822, 40), (-1, 835, 1823, 38), (-1, 835, 1824, 37), (-1, 836, 1825, 35), (-1, 836, 1826, 33), (-1, 836, 1827, 32), (-1, 836, 1828, 31), (-1, 837, 1829, 28), (-1, 837, 1830, 27), (-1, 837, 1831, 26), (-1, 837, 1832, 25), (-1, 838, 1833, 22), (-1, 838, 1834, 21), (-1, 838, 1835, 20), (-1, 838, 1836, 18), (-1, 839, 1837, 16), (-1, 839, 1838, 15), (-1, 839, 1839, 14), (-1, 839, 1840, 12), (-1, 840, 1841, 10), (-1, 840, 1842, 9), (-1, 840, 1843, 7), (-1, 840, 1844, 6), (-1, 841, 1845, 4), (-1, 841, 1846, 2), (-1, 841, 1847, 1)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1003369118 of 180 degree temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg [, , , , , , , , , , , , , , , ] 180 remove_crop_border : False version de PIL : 9.5.0 [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] 180 [[-1.0000000e+00 1.2246468e-16] [-1.2246468e-16 -1.0000000e+00]] shrink_image : False len(list_crops) : 16 time for calcul the mask position with numpy : 0.009753227233886719 nb_pixel_total : 110633 time to create 1 rle with old method : 0.1169745922088623 .time for calcul the mask position with numpy : 0.008522510528564453 nb_pixel_total : 15826 time to create 1 rle with old method : 0.016773462295532227 .time for calcul the mask position with numpy : 0.00867009162902832 nb_pixel_total : 5286 time to create 1 rle with old method : 0.005774497985839844 .time for calcul the mask position with numpy : 0.00882101058959961 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0018754005432128906 .time for calcul the mask position with numpy : 0.009386539459228516 nb_pixel_total : 105533 time to create 1 rle with old method : 0.11550045013427734 .time for calcul the mask position with numpy : 0.00892782211303711 nb_pixel_total : 4393 time to create 1 rle with old method : 0.0048944950103759766 .time for calcul the mask position with numpy : 0.008613109588623047 nb_pixel_total : 632 time to create 1 rle with old method : 0.0007092952728271484 .time for calcul the mask position with numpy : 0.008707523345947266 nb_pixel_total : 62627 time to create 1 rle with old method : 0.06558799743652344 .time for calcul the mask position with numpy : 0.008989334106445312 nb_pixel_total : 33681 time to create 1 rle with old method : 0.037197113037109375 .time for calcul the mask position with numpy : 0.0089111328125 nb_pixel_total : 37724 time to create 1 rle with old method : 0.04149651527404785 .time for calcul the mask position with numpy : 0.00876760482788086 nb_pixel_total : 48775 time to create 1 rle with old method : 0.051923274993896484 .time for calcul the mask position with numpy : 0.13480806350708008 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.19996404647827148 .time for calcul the mask position with numpy : 0.008297920227050781 nb_pixel_total : 2310 time to create 1 rle with old method : 0.002434253692626953 .time for calcul the mask position with numpy : 0.008476495742797852 nb_pixel_total : 2256 time to create 1 rle with old method : 0.002474546432495117 .time for calcul the mask position with numpy : 0.008481979370117188 nb_pixel_total : 3112 time to create 1 rle with old method : 0.003283262252807617 .time for calcul the mask position with numpy : 0.008808612823486328 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0017926692962646484 .len(list_crops_rotate) : 16 list_crops_rotate : : {'photo_id': -2, 'hashtag_id': 493012381, 'type': 3230, 'x0': 1584, 'x1': 2158, 'y0': 0, 'y1': 400, 'score': 1.0, 'id': None, 'points': ['2157,400,2061,330,1979,256,1913,208,1884,234,1821,193,1848,159,1845,150,1581,-2,2159,0'], 'sub_photo_id': 0, 'rles': [(-1, 1584, 0, 575), (-1, 1585, 1, 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(-1, 223, 263, 19), (-1, 222, 264, 21), (-1, 222, 265, 21), (-1, 221, 266, 23), (-1, 221, 267, 23), (-1, 220, 268, 25), (-1, 220, 269, 25), (-1, 219, 270, 27), (-1, 220, 271, 26), (-1, 222, 272, 25), (-1, 224, 273, 23), (-1, 226, 274, 22), (-1, 228, 275, 20), (-1, 230, 276, 19), (-1, 231, 277, 18), (-1, 232, 278, 18), (-1, 234, 279, 16), (-1, 235, 280, 16), (-1, 236, 281, 15), (-1, 237, 282, 14), (-1, 238, 283, 14), (-1, 240, 284, 12), (-1, 241, 285, 12), (-1, 242, 286, 11), (-1, 243, 287, 11), (-1, 245, 288, 9), (-1, 246, 289, 8), (-1, 247, 290, 8), (-1, 248, 291, 7), (-1, 250, 292, 6), (-1, 251, 293, 5), (-1, 252, 294, 4), (-1, 253, 295, 4), (-1, 254, 296, 3), (-1, 256, 297, 2), (-1, 257, 298, 1)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -2, 'hashtag_id': 2107752406, 'type': 3230, 'x0': 1487, 'x1': 1620, 'y0': 1392, 'y1': 1425, 'score': 1.0, 'id': None, 'points': ['1620,1425,1487,1417,1497,1392,1515,1392,1533,1396,1580,1411'], 'sub_photo_id': 0, 'rles': [(-1, 1497, 1392, 21), (-1, 1497, 1393, 25), (-1, 1496, 1394, 31), (-1, 1496, 1395, 35), (-1, 1495, 1396, 40), (-1, 1495, 1397, 43), (-1, 1495, 1398, 46), (-1, 1494, 1399, 50), (-1, 1494, 1400, 54), (-1, 1493, 1401, 58), (-1, 1493, 1402, 61), (-1, 1493, 1403, 64), (-1, 1492, 1404, 68), (-1, 1492, 1405, 71), (-1, 1491, 1406, 75), (-1, 1491, 1407, 79), (-1, 1491, 1408, 82), (-1, 1490, 1409, 86), (-1, 1490, 1410, 89), (-1, 1489, 1411, 93), (-1, 1489, 1412, 96), (-1, 1489, 1413, 99), (-1, 1488, 1414, 102), (-1, 1488, 1415, 105), (-1, 1487, 1416, 109), (-1, 1487, 1417, 112), (-1, 1496, 1418, 106), (-1, 1512, 1419, 93), (-1, 1529, 1420, 79), (-1, 1546, 1421, 64), (-1, 1562, 1422, 51), (-1, 1579, 1423, 37), (-1, 1596, 1424, 23), (-1, 1612, 1425, 9)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -2, 'hashtag_id': 2107752406, 'type': 3230, 'x0': 959, 'x1': 1046, 'y0': 139, 'y1': 204, 'score': 1.0, 'id': None, 'points': ['1046,180,1035,176,1031,158,1014,158,1005,158,986,147,974,138,960,141,959,155,962,164,966,171,980,182,1007,203,1013,203,1023,198,1032,195,1040,189'], 'sub_photo_id': 0, 'rles': [(-1, 972, 139, 3), (-1, 967, 140, 9), (-1, 963, 141, 15), (-1, 960, 142, 19), (-1, 960, 143, 20), (-1, 960, 144, 22), (-1, 960, 145, 23), (-1, 960, 146, 24), (-1, 960, 147, 26), (-1, 960, 148, 27), (-1, 960, 149, 29), (-1, 959, 150, 32), (-1, 959, 151, 34), (-1, 959, 152, 35), (-1, 959, 153, 37), (-1, 959, 154, 39), (-1, 959, 155, 40), (-1, 959, 156, 42), (-1, 959, 157, 44), (-1, 960, 158, 45), (-1, 960, 159, 72), (-1, 960, 160, 72), (-1, 961, 161, 71), (-1, 961, 162, 72), (-1, 961, 163, 72), (-1, 962, 164, 71), (-1, 962, 165, 71), (-1, 963, 166, 71), (-1, 963, 167, 71), (-1, 964, 168, 70), (-1, 964, 169, 70), (-1, 965, 170, 69), (-1, 965, 171, 70), (-1, 966, 172, 69), (-1, 967, 173, 68), (-1, 968, 174, 67), (-1, 970, 175, 66), (-1, 971, 176, 65), (-1, 972, 177, 65), (-1, 973, 178, 67), (-1, 975, 179, 67), (-1, 976, 180, 69), (-1, 977, 181, 70), (-1, 979, 182, 67), (-1, 980, 183, 66), (-1, 981, 184, 64), (-1, 982, 185, 62), (-1, 984, 186, 60), (-1, 985, 187, 58), (-1, 986, 188, 56), (-1, 988, 189, 54), (-1, 989, 190, 52), (-1, 990, 191, 50), (-1, 991, 192, 47), (-1, 993, 193, 44), (-1, 994, 194, 42), (-1, 995, 195, 39), (-1, 997, 196, 36), (-1, 998, 197, 33), (-1, 999, 198, 29), (-1, 1000, 199, 25), (-1, 1002, 200, 20), (-1, 1003, 201, 17), (-1, 1004, 202, 14), (-1, 1006, 203, 10), (-1, 1007, 204, 7)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -2, 'hashtag_id': 493012381, 'type': 3230, 'x0': 1787, 'x1': 1847, 'y0': 531, 'y1': 606, 'score': 1.0, 'id': None, 'points': ['1847,597,1796,531,1787,537,1811,574,1802,583,1806,597,1812,606,1830,601'], 'sub_photo_id': 0, 'rles': [(-1, 1796, 531, 1), (-1, 1794, 532, 4), (-1, 1793, 533, 6), (-1, 1791, 534, 8), (-1, 1790, 535, 10), (-1, 1788, 536, 13), (-1, 1787, 537, 15), (-1, 1788, 538, 14), (-1, 1788, 539, 15), (-1, 1789, 540, 15), (-1, 1790, 541, 15), (-1, 1790, 542, 16), (-1, 1791, 543, 15), (-1, 1792, 544, 15), (-1, 1792, 545, 16), (-1, 1793, 546, 16), (-1, 1793, 547, 16), (-1, 1794, 548, 16), (-1, 1795, 549, 16), (-1, 1795, 550, 17), (-1, 1796, 551, 16), (-1, 1797, 552, 16), (-1, 1797, 553, 17), (-1, 1798, 554, 17), (-1, 1799, 555, 17), (-1, 1799, 556, 17), (-1, 1800, 557, 17), (-1, 1801, 558, 17), (-1, 1801, 559, 18), (-1, 1802, 560, 17), (-1, 1803, 561, 17), (-1, 1803, 562, 18), (-1, 1804, 563, 18), (-1, 1805, 564, 18), (-1, 1805, 565, 18), (-1, 1806, 566, 18), (-1, 1806, 567, 19), (-1, 1807, 568, 19), (-1, 1808, 569, 18), (-1, 1808, 570, 19), (-1, 1809, 571, 19), (-1, 1810, 572, 19), (-1, 1810, 573, 19), (-1, 1811, 574, 19), (-1, 1810, 575, 21), (-1, 1809, 576, 23), (-1, 1808, 577, 25), (-1, 1807, 578, 26), (-1, 1806, 579, 28), (-1, 1805, 580, 30), (-1, 1804, 581, 32), (-1, 1803, 582, 33), (-1, 1802, 583, 35), (-1, 1802, 584, 36), (-1, 1803, 585, 36), (-1, 1803, 586, 37), (-1, 1803, 587, 37), (-1, 1803, 588, 38), (-1, 1804, 589, 38), (-1, 1804, 590, 39), (-1, 1804, 591, 39), (-1, 1805, 592, 39), (-1, 1805, 593, 40), (-1, 1805, 594, 41), (-1, 1805, 595, 41), (-1, 1806, 596, 41), (-1, 1806, 597, 42), (-1, 1807, 598, 38), (-1, 1807, 599, 34), (-1, 1808, 600, 29), (-1, 1809, 601, 24), (-1, 1809, 602, 20), (-1, 1810, 603, 15), (-1, 1811, 604, 10), (-1, 1811, 605, 7), (-1, 1812, 606, 2)], 'hashtag': '', 'sum_segment': 0} Rotation of photo 1003369118 of 270 degree temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg [, , , , , , , , , , , , , , , ] 270 remove_crop_border : False version de PIL : 9.5.0 Needs to change image size ! [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] 270 [[-1.8369702e-16 -1.0000000e+00] [ 1.0000000e+00 -1.8369702e-16]] shrink_image : False len(list_crops) : 16 time for calcul the mask position with numpy : 0.008809089660644531 nb_pixel_total : 110633 time to create 1 rle with old method : 0.11621856689453125 .time for calcul the mask position with numpy : 0.008760690689086914 nb_pixel_total : 15826 time to create 1 rle with old method : 0.016765356063842773 .time for calcul the mask position with numpy : 0.008469581604003906 nb_pixel_total : 5286 time to create 1 rle with old method : 0.005687713623046875 .time for calcul the mask position with numpy : 0.00863504409790039 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0017733573913574219 .time for calcul the mask position with numpy : 0.008959054946899414 nb_pixel_total : 105533 time to create 1 rle with old method : 0.11111044883728027 .time for calcul the mask position with numpy : 0.008818387985229492 nb_pixel_total : 4393 time to create 1 rle with old method : 0.004799604415893555 .time for calcul the mask position with numpy : 0.008431673049926758 nb_pixel_total : 632 time to create 1 rle with old method : 0.0007507801055908203 .time for calcul the mask position with numpy : 0.008651256561279297 nb_pixel_total : 62627 time to create 1 rle with old method : 0.06938409805297852 .time for calcul the mask position with numpy : 0.00923013687133789 nb_pixel_total : 33681 time to create 1 rle with old method : 0.03792738914489746 .time for calcul the mask position with numpy : 0.008744478225708008 nb_pixel_total : 37724 time to create 1 rle with old method : 0.04073834419250488 .time for calcul the mask position with numpy : 0.008886098861694336 nb_pixel_total : 48775 time to create 1 rle with old method : 0.05327177047729492 .time for calcul the mask position with numpy : 0.039670467376708984 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.11956167221069336 .time for calcul the mask position with numpy : 0.008654594421386719 nb_pixel_total : 2310 time to create 1 rle with old method : 0.002508878707885742 .time for calcul the mask position with numpy : 0.009644508361816406 nb_pixel_total : 2256 time to create 1 rle with old method : 0.002502918243408203 .time for calcul the mask position with numpy : 0.009317159652709961 nb_pixel_total : 3112 time to create 1 rle with old method : 0.0033609867095947266 .time for calcul the mask position with numpy : 0.009629487991333008 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0018477439880371094 .len(list_crops_rotate) : 16 list_crops_rotate : : {'photo_id': -3, 'hashtag_id': 493012381, 'type': 3230, 'x0': 0, 'x1': 400, 'y0': 0, 'y1': 574, 'score': 1.0, 'id': None, 'points': ['400,0,330,96,256,178,208,244,234,273,193,336,159,309,150,312,-2,576,0,-1'], 'sub_photo_id': 0, 'rles': [(-1, 0, 0, 301), (-1, 0, 1, 401), (-1, 0, 2, 400), (-1, 0, 3, 400), (-1, 0, 4, 399), 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1196, 24), (-1, 142, 1197, 22), (-1, 142, 1198, 19), (-1, 150, 1199, 8)], 'hashtag': '', 'sum_segment': 0},: {'photo_id': -3, 'hashtag_id': 493012381, 'type': 3230, 'x0': 531, 'x1': 606, 'y0': 311, 'y1': 371, 'score': 1.0, 'id': None, 'points': ['596,310,530,361,536,370,573,346,582,355,596,351,605,345,600,327'], 'sub_photo_id': 0, 'rles': [(-1, 597, 311, 1), (-1, 596, 312, 2), (-1, 594, 313, 4), (-1, 593, 314, 6), (-1, 592, 315, 7), (-1, 590, 316, 9), (-1, 589, 317, 10), (-1, 588, 318, 12), (-1, 586, 319, 14), (-1, 585, 320, 15), (-1, 584, 321, 16), (-1, 583, 322, 18), (-1, 581, 323, 20), (-1, 580, 324, 21), (-1, 579, 325, 22), (-1, 577, 326, 25), (-1, 576, 327, 26), (-1, 575, 328, 27), (-1, 574, 329, 28), (-1, 572, 330, 31), (-1, 571, 331, 32), (-1, 570, 332, 33), (-1, 568, 333, 35), (-1, 567, 334, 37), (-1, 566, 335, 38), (-1, 564, 336, 40), (-1, 563, 337, 41), (-1, 562, 338, 43), (-1, 561, 339, 44), (-1, 559, 340, 46), (-1, 558, 341, 48), (-1, 557, 342, 49), (-1, 555, 343, 51), (-1, 554, 344, 52), (-1, 553, 345, 54), (-1, 552, 346, 55), (-1, 550, 347, 56), (-1, 549, 348, 25), (-1, 575, 348, 29), (-1, 548, 349, 24), (-1, 576, 349, 27), (-1, 546, 350, 25), (-1, 577, 350, 24), (-1, 545, 351, 24), (-1, 578, 351, 22), (-1, 544, 352, 24), (-1, 579, 352, 19), (-1, 542, 353, 24), (-1, 580, 353, 16), (-1, 541, 354, 23), (-1, 581, 354, 11), (-1, 540, 355, 23), (-1, 582, 355, 7), (-1, 539, 356, 22), (-1, 583, 356, 2), (-1, 537, 357, 23), (-1, 536, 358, 22), (-1, 535, 359, 22), (-1, 533, 360, 22), (-1, 532, 361, 22), (-1, 531, 362, 21), (-1, 532, 363, 19), (-1, 532, 364, 17), (-1, 533, 365, 15), (-1, 534, 366, 12), (-1, 534, 367, 10), (-1, 535, 368, 8), (-1, 536, 369, 5), (-1, 536, 370, 4), (-1, 537, 371, 1)], 'hashtag': '', 'sum_segment': 0} About to upload 4 photos upload in portfolio : 27233741 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812829_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 4 photos in the portfolio 27233741 time of upload the photos Elapsed time : 1.8275599479675293 map_filename_photo_id : 4 map_filename_photo_id : {'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_658263370.jpg': 1386160827, 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_6582633790.jpg': 1386160829, 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337180.jpg': 1386160831, 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337270.jpg': 1386160832} Len new_chis : 4 Len list_new_chi_with_photo_id : 64 of type : 3230 list_new_chi_with_photo_id : [, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ] batch 1 Loaded 64 chid ids of type : 3230 Number RLEs to save : 24654 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 17.799214839935303 time spend to save output : 0.00020503997802734375 total time spend for step 1 : 17.79941987991333 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1386160827: ['1003369118', 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_658263370.jpg', [, , , , , , , , , , , , , , , ]], 1386160829: ['1003369118', 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_6582633790.jpg', [, , , , , , , , , , , , , , , ]], 1386160831: ['1003369118', 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337180.jpg', [, , , , , , , , , , , , , , , ]], 1386160832: ['1003369118', 'temp/1758812814_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337270.jpg', [, , , , , , , , , , , , , , , ]]} batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1386160827,1386160829,1386160831,1386160832) and `type` in (3230) Loaded 64 chid ids of type : 3230 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (3975221103,3975221107,3975221104,3975221118,3975221105,3975221106,3975221114,3975221110,3975221108,3975221112,3975221109,3975221113,3975221111,3975221116,3975221117,3975221115,3975221123,3975221130,3975221120,3975221121,3975221129,3975221134,3975221126,3975221122,3975221119,3975221128,3975221125,3975221124,3975221127,3975221132,3975221131,3975221133,3975221146,3975221145,3975221144,3975221141,3975221142,3975221140,3975221139,3975221137,3975221135,3975221138,3975221150,3975221136,3975221143,3975221147,3975221149,3975221148,3975221151,3975221158,3975221162,3975221160,3975221156,3975221157,3975221161,3975221154,3975221166,3975221152,3975221153,3975221155,3975221159,3975221165,3975221163,3975221164) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (3975221103,3975221107,3975221104,3975221118,3975221105,3975221106,3975221114,3975221110,3975221108,3975221112,3975221109,3975221113,3975221111,3975221116,3975221117,3975221115,3975221123,3975221130,3975221120,3975221121,3975221129,3975221134,3975221126,3975221122,3975221119,3975221128,3975221125,3975221124,3975221127,3975221132,3975221131,3975221133,3975221146,3975221145,3975221144,3975221141,3975221142,3975221140,3975221139,3975221137,3975221135,3975221138,3975221150,3975221136,3975221143,3975221147,3975221149,3975221148,3975221151,3975221158,3975221162,3975221160,3975221156,3975221157,3975221161,3975221154,3975221166,3975221152,3975221153,3975221155,3975221159,3975221165,3975221163,3975221164) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (3975221103,3975221107,3975221104,3975221118,3975221105,3975221106,3975221114,3975221110,3975221108,3975221112,3975221109,3975221113,3975221111,3975221116,3975221117,3975221115,3975221123,3975221130,3975221120,3975221121,3975221129,3975221134,3975221126,3975221122,3975221119,3975221128,3975221125,3975221124,3975221127,3975221132,3975221131,3975221133,3975221146,3975221145,3975221144,3975221141,3975221142,3975221140,3975221139,3975221137,3975221135,3975221138,3975221150,3975221136,3975221143,3975221147,3975221149,3975221148,3975221151,3975221158,3975221162,3975221160,3975221156,3975221157,3975221161,3975221154,3975221166,3975221152,3975221153,3975221155,3975221159,3975221165,3975221163,3975221164) fin du test de rotate_chi Ayatollah of tests excluded it ! (Bon le prochain developpeur qui passe ici peut enlever ayatollah VR 11-2-21) name : rubbia_carac_pet_clair_0121 not run because too long ############################### TEST rubbia_carac_pet_clair_0121_no_cnn ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=2719 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=2719 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 2719 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=2719 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 6479 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 6480 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7445 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 6509 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 6479 doesn't seem to be define in the database( WARNING : type of input 1 of step 6480 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 6479 doesn't seem to be define in the database( WARNING : type of input 1 of step 7445 doesn't seem to be define in the database( WARNING : type of output 1 of step 7445 doesn't seem to be define in the database( WARNING : type of input 3 of step 6509 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : merge_mask_thcl_custom, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3373196) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3373196) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1009068724, 'portfolio_id': 3373196}, {'photo_id': 1009068683, 'portfolio_id': 3373196}] map_portfolio_id_photo_id: {3373196: [1009068724, 1009068683]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1009068724 begin to download photo : 1009068683 download finish for photo 1009068683 download finish for photo 1009068724 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 ##### After load_data_input time to download the photos : 0.29747462272644043 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 4 step1:merge_mask_thcl_custom Thu Sep 25 17:07:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg': 1009068683, 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg': 1009068724} map_photo_id_path_extension : {1009068683: {'path': 'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'extension': 'jpg'}, 1009068724: {'path': 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step merge_mask_thcl_custom args ['temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg'] processing picture : temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg processing picture : temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg map_subphoto_result {} batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1009068683,1009068724) and `type` in (2800) Loaded 82 chid ids of type : 2800 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1941272807,1941272792,1941272797,1941272801,1941272788,1941272813,1941272802,1941272799,1941272815,1941272809,1941272786,1941272808,1941272791,1941272816,1941272796,1941272811,1941272817,1941272810,1941272814,1941272793,1941272803,1941272804,1941272805,1941272781,1941272789,1941272798,1941272812,1941272800,1941272784,1941272782,1941272794,1941272795,1941272806,1941272785,1941272790,1941272783,1941272787,1941270022,1941270015,1941270036,1941270021,1941270029,1941270018,1941270017,1941270025,1941607383,1941270019,1941270038,1941270040,1941270014,1941270039,1941270020,1941270030,1941270033,1941270028,1941270027,1941270026,1941270032,1941270031,1941270035,1941270037,1941270041,1941270012,1941270013,1941607380,1941607381,2202875936,1941270008,1941270016,1941607382,1941270034,2202875937,1941270010,1941270005,1941270007,1941270024,1941270011,2202875938,1941270023,1941607379,1941270006,1941270009) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1941272807,1941272792,1941272797,1941272801,1941272788,1941272813,1941272802,1941272799,1941272815,1941272809,1941272786,1941272808,1941272791,1941272816,1941272796,1941272811,1941272817,1941272810,1941272814,1941272793,1941272803,1941272804,1941272805,1941272781,1941272789,1941272798,1941272812,1941272800,1941272784,1941272782,1941272794,1941272795,1941272806,1941272785,1941272790,1941272783,1941272787,1941270022,1941270015,1941270036,1941270021,1941270029,1941270018,1941270017,1941270025,1941607383,1941270019,1941270038,1941270040,1941270014,1941270039,1941270020,1941270030,1941270033,1941270028,1941270027,1941270026,1941270032,1941270031,1941270035,1941270037,1941270041,1941270012,1941270013,1941607380,1941607381,2202875936,1941270008,1941270016,1941607382,1941270034,2202875937,1941270010,1941270005,1941270007,1941270024,1941270011,2202875938,1941270023,1941607379,1941270006,1941270009) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1941272807,1941272792,1941272797,1941272801,1941272788,1941272813,1941272802,1941272799,1941272815,1941272809,1941272786,1941272808,1941272791,1941272816,1941272796,1941272811,1941272817,1941272810,1941272814,1941272793,1941272803,1941272804,1941272805,1941272781,1941272789,1941272798,1941272812,1941272800,1941272784,1941272782,1941272794,1941272795,1941272806,1941272785,1941272790,1941272783,1941272787,1941270022,1941270015,1941270036,1941270021,1941270029,1941270018,1941270017,1941270025,1941607383,1941270019,1941270038,1941270040,1941270014,1941270039,1941270020,1941270030,1941270033,1941270028,1941270027,1941270026,1941270032,1941270031,1941270035,1941270037,1941270041,1941270012,1941270013,1941607380,1941607381,2202875936,1941270008,1941270016,1941607382,1941270034,2202875937,1941270010,1941270005,1941270007,1941270024,1941270011,2202875938,1941270023,1941607379,1941270006,1941270009) As expected we have just one thcl present processing picture : 1009068683 begin to find the sub_photo_id : select crop_hashtag_id , sub_photo_id from MTRPhoto.crop_sub_photo_ids where crop_hashtag_id in (1941272807,1941272792,1941272797,1941272801,1941272788,1941272813,1941272802,1941272799,1941272815,1941272809,1941272786,1941272808,1941272791,1941272816,1941272796,1941272811,1941272817,1941272810,1941272814,1941272793,1941272803,1941272804,1941272805,1941272781,1941272789,1941272798,1941272812,1941272800,1941272784,1941272782,1941272794,1941272795,1941272806,1941272785,1941272790,1941272783,1941272787) ; chi 1941272807 saved with no changes chi 1941272792 saved with no changes chi 1941272797 saved with no changes chi 1941272801 saved with no changes chi 1941272788 saved with no changes chi 1941272813 saved with no changes chi 1941272802 saved with no changes chi 1941272799 saved with no changes chi 1941272815 saved with no changes chi 1941272809 saved with no changes chi 1941272786 saved with no changes chi 1941272808 saved with no changes chi 1941272791 saved with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009071263,1009221813,1009235446,1009235446,1009279340,1009279356,1009280654,1009282603,1009285753,1009285765,1009287138,1009288503,1009288546,1009289519,1009290969,1009291015,1009292124,1009293463,1009293494,1009302642,1009302924,1009314298,1009325392,1009325685,1009331808,1009337442,1009343208,1009348717,1009360426,1009360710,1009366170,1009370139,1009378373,1009378413,1009382207,1009387316,1009387465,1009397637,1009397719,1009407253,1009418244,1009418926,1009427413,1009430107,1009431383,1009433078,1009433144,1009434053,1009434384,1009434694,1009435681,1009436481,1009436964,1009437043,1009437239,1009438334,1009438590,1009440272,1009440278,1009442464,1009442509,1009442528,1009444076,1009444130,1009445413,1009445538,1009446902,1009448266,1009448396,1009449789,1009451629,1009451631,1009451750,1009452461,1009452961,1009452979,1009454196,1009454247,1009454337,1009455534,1009457025,1009457032,1009457228,1009460750,1009460967,1009466377,1009466452,1009467101,1009471967,1009472268,1009477695,1009478118,1009481722,1009482987,1009487453,1009487657,1009487950,1009489088,1009489218,1009489308,1009490315,1009490479,1009495060,1009495488,1009498944,1009500499,1009500766,1009506264,1009506270,1009506275,1009506746,1009509720,1009510178,1009511663,1009517339,1009517535,1009517849,1009521436,1009521607,1009525340,1009525354,1009525617,1009528261,1009529525,1009533039,1009533043,1009533518,1009536205,1009540619,1009540774,1009541035,1009543634,1009544885,1009545316,1009549107,1009549847,1009551213,1009552745,1009553914,1009557764,1009558260,1009560600,1009562085,1009566563,1009567165,1009570167,1009571289,1009576217,1009576836,1009579452,1009580609,1009585073,1009585473,1009587840,1009589122,1009593908,1009596967,1009597989,1009602701,1009603252,1009605651,1009606591,1009610545,1009610907,1009612085,1009612622,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,1009612733,100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1067690191, 1067717414, 1067747138, 1067774112, 1067802800, 1067861249, 1067911431, 1067941478, 1067982047, 1068035445, 1068088471, 1068111526, 1068135668, 1068160646, 1068189419, 1068212313, 1068237225, 1068269603, 1068303914, 1068329046, 1068346739, 1068348691, 1068386857, 1068425048, 1068452884, 1068458893, 1068468412, 1068469245, 1068469819, 1068470401, 1068471258, 1068471943, 1068474409, 1068506226, 1068541458, 1068570957, 1068623505, 1068682678, 1068719359, 1068741809, 1068773096, 1068806813, 1068837184, 1068851168, 1068855957, 1068875459, 1068897957, 1068917463, 1068943961, 1068968310, 1068982664, 1069002726, 1069020498, 1069057620, 1069125044, 1069205888, 1069239240, 1069260806, 1069283981, 1069310062, 1069337746, 1069359153, 1069378206, 1069385923, 1069408085, 1069454244, 1069505570, 1069547704, 1069590740, 1069703344, 1069823740, 1069863127, 1069957904, 1069991320, 1070012155, 1070039929, 1070071215, 1070086447, 1070096250, 1070099003, 1070109608, 1070151842, 1070176007, 1070188630, 1070229602, 1070274897, 1070325003, 1070371824, 1070420338, 1070483036, 1070525074, 1070555663, 1070594548, 1070637083, 1070680464, 1070724015, 1070790695, 1070943047, 1071200711, 1071239808, 1071464242, 1071636096, 1071703689, 1071767893, 1071811888, 1071860806, 1071928107, 1072017177, 1072118440, 1072207679, 1072297360, 1072393940, 1072508113, 1072582572, 1072632150, 1072728396, 1072839511, 1072917093, 1072972612, 1073027774, 1073056959, 1073111357, 1073142087, 1073196806, 1073244301, 1073366400, 1073503492, 1073644965, 1073725121, 1073807926, 1073882317, 1073948836, 1074028102], saving chi 1941272796 with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009071264,1009221814,1009235447,1009235447,1009279341,1009279357,1009280655,1009282604,1009285754,1009285766,1009287139,1009288504,1009288547,1009289520,1009290970,1009291016,1009292125,1009293464,1009293495,1009302643,1009302925,1009314299,1009325393,1009325686,1009331809,1009337443,1009343209,1009348718,1009360428,1009360711,1009366171,1009370140,1009378374,1009378414,1009382208,1009387317,1009387466,1009397639,1009397720,1009407254,1009418245,1009418927,1009427414,1009430108,1009431384,1009433079,1009433145,1009434054,1009434385,1009434695,1009435682,1009436482,1009436965,1009437044,1009437240,1009438336,1009438591,1009440273,1009440279,1009442465,1009442510,1009442529,1009444077,1009444131,1009445414,1009445539,1009446903,1009448267,1009448397,1009449790,1009451630,1009451632,1009451751,1009452462,1009452962,1009452980,1009454197,1009454248,1009454338,1009455535,1009457026,1009457033,1009457229,1009460751,1009460968,1009466378,1009466453,1009467102,1009471968,1009472269,1009477696,1009478120,1009481723,1009482988,1009487454,1009487658,1009487951,1009489089,1009489219,1009489309,1009490316,1009490480,1009495061,1009495489,1009498945,1009500500,1009500767,1009506265,1009506271,1009506276,1009506747,1009509721,1009510179,1009511664,1009517341,1009517536,1009517850,1009521437,1009521608,1009525341,1009525355,1009525618,1009528262,1009529526,1009533040,1009533045,1009533519,1009536206,1009540620,1009540775,1009541036,1009543635,1009544886,1009545317,1009549108,1009549848,1009551214,1009552746,1009553915,1009557765,1009558261,1009560601,1009562086,1009566564,1009567166,1009570168,1009571290,1009576219,1009576837,1009579453,1009580610,1009585074,1009585474,1009587841,1009589123,1009593909,1009596968,1009597990,1009602702,1009603253,1009605652,1009606592,1009610546,1009610908,1009612086,1009612623,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,1009612734,100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1067690192, 1067717415, 1067747139, 1067774113, 1067802801, 1067861252, 1067911432, 1067941479, 1067982048, 1068035446, 1068088472, 1068111527, 1068135669, 1068160647, 1068189420, 1068212314, 1068237226, 1068269604, 1068303915, 1068329047, 1068346740, 1068348692, 1068386858, 1068425049, 1068452885, 1068458894, 1068468413, 1068469246, 1068469820, 1068470402, 1068471259, 1068471944, 1068474410, 1068506227, 1068541459, 1068570958, 1068623506, 1068682679, 1068719360, 1068741810, 1068773097, 1068806814, 1068837185, 1068851169, 1068855958, 1068875460, 1068897958, 1068917464, 1068943962, 1068968311, 1068982665, 1069002727, 1069020499, 1069057621, 1069125045, 1069205889, 1069239241, 1069260807, 1069283982, 1069310063, 1069337747, 1069359154, 1069378207, 1069385924, 1069408086, 1069454245, 1069505571, 1069547705, 1069590741, 1069703345, 1069823741, 1069863128, 1069957905, 1069991321, 1070012156, 1070039930, 1070071216, 1070086448, 1070096251, 1070099004, 1070109609, 1070151843, 1070176008, 1070188631, 1070229603, 1070274898, 1070325005, 1070371825, 1070420339, 1070483037, 1070525075, 1070555664, 1070594549, 1070637084, 1070680465, 1070724016, 1070790696, 1070943048, 1071200712, 1071239809, 1071464244, 1071636097, 1071703690, 1071767894, 1071811889, 1071860807, 1071928108, 1072017178, 1072118442, 1072207680, 1072297361, 1072393941, 1072508114, 1072582573, 1072632151, 1072728397, 1072839512, 1072917094, 1072972613, 1073027775, 1073056960, 1073111358, 1073142089, 1073196807, 1073244303, 1073366401, 1073503493, 1073644966, 1073725122, 1073807927, 1073882318, 1073948837, 1074028103], saving chi 1941272793 with no changes chi 1941272803 saved with no changes chi 1941272804 saved with no changes chi 1941272805 saved with no changes chi 1941272781 saved with no changes chi 1941272789 saved with no changes chi 1941272798 saved with no changes chi 1941272812 saved with no changes chi 1941272800 saved with no changes chi 1941272784 saved with no changes chi 1941272782 saved with no changes chi 1941272794 saved with no changes chi 1941272795 saved with no changes chi 1941272806 saved with no changes chi 1941272785 saved with no changes chi 1941272790 saved with no changes chi 1941272783 saved with no changes chi 1941272787 saved with no changes processing picture : 1009068724 begin to find the sub_photo_id : select crop_hashtag_id , sub_photo_id from MTRPhoto.crop_sub_photo_ids where crop_hashtag_id in (1941270022,1941270015,1941270036,1941270021,1941270029,1941270018,1941270017,1941270025,1941607383,1941270019,1941270038,1941270040,1941270014,1941270039,1941270020,1941270030,1941270033,1941270028,1941270027,1941270026,1941270032,1941270031,1941270035,1941270037,1941270041,1941270012,1941270013,1941607380,1941607381,2202875936,1941270008,1941270016,1941607382,1941270034,2202875937,1941270010,1941270005,1941270007,1941270024,1941270011,2202875938,1941270023,1941607379,1941270006,1941270009) ; chi 1941270022 saved with no changes chi 1941270015 saved with no changes chi 1941270036 saved with no changes chi 1941270021 saved with no changes chi 1941270029 saved with no changes chi 1941270018 saved with no changes chi 1941270017 saved with no changes chi 1941270025 saved with no changes chi 1941607383 saved with no changes chi 1941270019 saved with no changes chi 1941270038 saved with no changes chi 1941270040 saved with no changes chi 1941270014 saved with no changes chi 1941270039 saved with no changes chi 1941270020 saved with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009070856,1009221556,1009235000,1009235000,1009235000,1009279342,1009279352,1009280656,1009282608,1009285758,1009285767,1009287134,1009288505,1009288551,1009289512,1009290974,1009291020,1009292129,1009293459,1009293499,1009302644,1009302926,1009314291,1009325388,1009325687,1009331813,1009337444,1009343213,1009348719,1009360418,1009360712,1009366172,1009370141,1009378378,1009378418,1009382212,1009387309,1009387467,1009397623,1009397721,1009407255,1009418249,1009418931,1009427415,1009430103,1009431388,1009433083,1009433140,1009434049,1009434049,1009434049,1009434377,1009434377,1009434377,1009434690,1009434690,1009434690,1009435683,1009436483,1009436969,1009436969,1009436969,1009437039,1009437244,1009438330,1009438586,1009438586,1009438586,1009440274,1009440283,1009440274,1009440274,1009442466,1009442502,1009442533,1009442533,1009442533,1009444071,1009444126,1009444126,1009444126,1009445418,1009445543,1009446898,1009446898,1009446898,1009448271,1009448392,1009448392,1009448392,1009449794,1009449794,1009449794,1009451625,1009451636,1009451746,1009451746,1009451746,1009452466,1009452466,1009452466,1009452957,1009452957,1009452957,1009452981,1009454192,1009454249,1009454339,1009454339,1009454339,1009455527,1009457021,1009457034,1009457224,1009457224,1009457224,1009460746,1009460746,1009460746,1009460963,1009466379,1009466448,1009467103,1009467103,1009467103,1009471963,1009471963,1009471963,1009472264,1009477697,1009478110,1009478110,1009478110,1009481715,1009481715,1009481715,1009482983,1009482983,1009482983,1009487455,1009487650,1009487952,1009487952,1009487952,1009489081,1009489223,1009489310,1009489310,1009489310,1009490311,1009490311,1009490311,1009490481,1009495056,1009495484,1009495484,1009495484,1009498949,1009498949,1009498949,1009500504,1009500504,1009500504,1009500755,1009506260,1009506266,1009506266,1009506280,1009506742,1009506742,1009506742,1009509716,1009510174,1009510174,1009510174,1009511665,1009511665,1009511665,1009517335,1009517537,1009517845,1009517845,1009517845,1009521429,1009521429,1009521429,1009521603,1009525336,1009525350,1009525619,1009525619,1009525619,1009528263,1009529518,1009529518,1009529518,1009533041,1009533047,1009533520,1009533520,1009533520,1009536210,1009536210,1009536210,1009540621,1009540767,1009541040,1009541040,1009541040,1009543630,1009543630,1009543630,1009544881,1009545318,1009545318,1009545318,1009549109,1009549843,1009549843,1009549843,1009551218,1009551218,1009551218,1009552741,1009553916,1009553916,1009553916,1009557766,1009558262,1009558262,1009558262,1009560602,1009560602,1009560602,1009562081,1009562081,1009562081,1009566559,1009567161,1009567161,1009567161,1009570163,1009571294,1009571294,1009571294,1009576213,1009576838,1009576838,1009576838,1009579448,1009579448,1009579448,1009580611,1009580611,1009580611,1009585078,1009585478,1009585478,1009585478,1009587842,1009589124,1009589124,1009589124,1009593904,1009596963,1009597982,1009597982,1009597982,1009602703,1009603248,1009603248,1009603248,1009605647,1009605647,1009605647,1009606587,1009606587,1009606587,1009610541,1009610909,1009610909,1009610909,1009612090,1009612090,1009612090,1009612624,1009612624,1009612624,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,1009612726,100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1057041127, 1057088056, 1057121108, 1057151342, 1057220555, 1057280511, 1057341345, 1057404843, 1057405392, 1057407765, 1057472509, 1057500269, 1057540058, 1057593125, 1057647547, 1057687876, 1057710264, 1057732747, 1057755507, 1057764773, 1057772052, 1057778725, 1057785413, 1057793600, 1057801258, 1057807128, 1057813937, 1057816041, 1057829285, 1057848916, 1057892837, 1057897018, 1057932756, 1058003322, 1058069206, 1058128310, 1058168237, 1058218996, 1058252309, 1058301784, 1058344216, 1058356999, 1058360843, 1058373424, 1058397929, 1058419185, 1058452269, 1058454545, 1058497063, 1058498205, 1058498417, 1058498764, 1058521788, 1058551449, 1058552620, 1058555676, 1058558897, 1058563075, 1058588012, 1058598159, 1058621589, 1058654999, 1058676192, 1058707465, 1058970476, 1059006626, 1059046568, 1059191650, 1059236200, 1059303265, 1059358501, 1059421116, 1059465154, 1059519819, 1059570908, 1059621386, 1059666506, 1059721385, 1059764181, 1059769187, 1059785226, 1059879567, 1059945487, 1060020931, 1060078213, 1060220735, 1060379659, 1060464895, 1060518322, 1060593804, 1060658652, 1060713776, 1060747605, 1060788850, 1060803884, 1060857833, 1060887244, 1060936296, 1060966195, 1061000350, 1061056458, 1061100120, 1061192542, 1061226353, 1061229430, 1061238744, 1061286705, 1061337835, 1061360119, 1061417199, 1061498968, 1061555744, 1061610191, 1061671176, 1061719302, 1061763996, 1061784988, 1061817864, 1061883306, 1061935813, 1062011814, 1062066023, 1062133123, 1062316229, 1062405206, 1062458587, 1062503689, 1062550076, 1062590641, 1062648863, 1062695431, 1062723340, 1062756111, 1062784493, 1062812432, 1062854624, 1062915394, 1062972085, 1063010690, 1063064214, 1063123898, 1063221076, 1063265472, 1063308568, 1063509639, 1063558457, 1063625398, 1063754710, 1063792623, 1063859377, 1064104830, 1064194323, 1064238850, 1064271159, 1064300597, 1064328040, 1064355809, 1064384227, 1064413859, 1064442495, 1064475865, 1064569993, 1064629410, 1064679939, 1064718118, 1064843968, 1064885496, 1064925688, 1064980977, 1065025219, 1065066417, 1065122252, 1065166127, 1065199556, 1065231168, 1065248304, 1065277476, 1065295444, 1065311550, 1065327180, 1065338944, 1065347318, 1065358526, 1065423046, 1065464746, 1065551062, 1065640479, 1065683379, 1065752108, 1065853210, 1065872620, 1065886163, 1065906993, 1065929860, 1065949954, 1065970145, 1065989087, 1066036677, 1066082794, 1066127200, 1066177816, 1066234446, 1066280971, 1066333750, 1066370057, 1066403949, 1066434333, 1066459556, 1066470977, 1066476566, 1066483565, 1066495991, 1066526111, 1066576204, 1066628889, 1066688040, 1066748033, 1066802946, 1066855083, 1066901150, 1066957297, 1067018956, 1067077303, 1067126795, 1067176860, 1067220038, 1067242687, 1067290902, 1067350628, 1067420132, 1067481997, 1067541098, 1067577643, 1067619694, 1067661437, 1067690193, 1067717416, 1067747134, 1067774114, 1067802802, 1067861254, 1067911433, 1067941480, 1067982049, 1068035447, 1068088467, 1068111528, 1068135670, 1068160642, 1068189421, 1068212315, 1068237221, 1068269605, 1068303916, 1068329048, 1068346741, 1068348693, 1068386853, 1068425050, 1068452880, 1068458889, 1068468408, 1068469247, 1068469815, 1068470403, 1068471260, 1068471939, 1068474411, 1068506228, 1068541460, 1068570953, 1068623507, 1068682680, 1068719361, 1068741811, 1068773098, 1068806809, 1068837180, 1068851164, 1068855953, 1068875461, 1068897959, 1068917459, 1068943957, 1068968306, 1068982666, 1069002722, 1069020494, 1069057622, 1069125046, 1069205890, 1069239242, 1069260808, 1069283977, 1069310064, 1069337748, 1069359149, 1069378202, 1069385925, 1069408081, 1069454239, 1069505572, 1069547700, 1069590742, 1069703347, 1069823742, 1069863123, 1069957906, 1069991316, 1070012151, 1070039925, 1070071217, 1070086449, 1070096252, 1070099005, 1070109604, 1070151838, 1070176003, 1070188632, 1070229598, 1070274893, 1070325007, 1070371826, 1070420333, 1070483038, 1070525070, 1070555659, 1070594550, 1070637079, 1070680460, 1070724011, 1070790691, 1070943043, 1071200713, 1071239804, 1071464238, 1071636092, 1071703685, 1071767895, 1071811890, 1071860802, 1071928103, 1072017179, 1072118435, 1072207681, 1072297362, 1072393936, 1072508115, 1072582574, 1072632152, 1072728392, 1072839513, 1072917095, 1072972614, 1073027776, 1073056961, 1073111353, 1073142090, 1073196802, 1073244304, 1073366396, 1073503488, 1073644967, 1073725123, 1073807928, 1073882319, 1073948832, 1074028105], saving chi 1941270030 with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009070857,1009221557,1009235001,1009235001,1009235001,1009279343,1009279353,1009280657,1009282609,1009285759,1009285768,1009287135,1009288506,1009288552,1009289513,1009290975,1009291021,1009292130,1009293460,1009293500,1009302645,1009302927,1009314292,1009325389,1009325688,1009331814,1009337445,1009343214,1009348720,1009360419,1009360713,1009366173,1009370142,1009378379,1009378419,1009382213,1009387310,1009387468,1009397625,1009397722,1009407256,1009418250,1009418932,1009427416,1009430104,1009431389,1009433084,1009433141,1009434050,1009434050,1009434050,1009434378,1009434378,1009434378,1009434691,1009434691,1009434691,1009435684,1009436484,1009436970,1009436970,1009436970,1009437040,1009437245,1009438331,1009438587,1009438587,1009438587,1009440275,1009440284,1009440275,1009440275,1009442467,1009442503,1009442534,1009442534,1009442534,1009444072,1009444127,1009444127,1009444127,1009445419,1009445544,1009446899,1009446899,1009446899,1009448272,1009448393,1009448393,1009448393,1009449795,1009449795,1009449795,1009451626,1009451637,1009451747,1009451747,1009451747,1009452467,1009452467,1009452467,1009452958,1009452958,1009452958,1009452982,1009454193,1009454250,1009454340,1009454340,1009454340,1009455528,1009457022,1009457035,1009457225,1009457225,1009457225,1009460747,1009460747,1009460747,1009460964,1009466380,1009466449,1009467104,1009467104,1009467104,1009471964,1009471964,1009471964,1009472265,1009477698,1009478112,1009478112,1009478112,1009481716,1009481716,1009481716,1009482984,1009482984,1009482984,1009487456,1009487651,1009487953,1009487953,1009487953,1009489082,1009489224,1009489311,1009489311,1009489311,1009490312,1009490312,1009490312,1009490482,1009495057,1009495485,1009495485,1009495485,1009498950,1009498950,1009498950,1009500505,1009500505,1009500505,1009500757,1009506261,1009506267,1009506267,1009506281,1009506743,1009506743,1009506743,1009509717,1009510175,1009510175,1009510175,1009511666,1009511666,1009511666,1009517336,1009517538,1009517846,1009517846,1009517846,1009521430,1009521430,1009521430,1009521604,1009525337,1009525351,1009525620,1009525620,1009525620,1009528264,1009529519,1009529519,1009529519,1009533042,1009533049,1009533521,1009533521,1009533521,1009536211,1009536211,1009536211,1009540622,1009540768,1009541041,1009541041,1009541041,1009543631,1009543631,1009543631,1009544882,1009545319,1009545319,1009545319,1009549110,1009549844,1009549844,1009549844,1009551219,1009551219,1009551219,1009552742,1009553917,1009553917,1009553917,1009557767,1009558263,1009558263,1009558263,1009560603,1009560603,1009560603,1009562082,1009562082,1009562082,1009566560,1009567162,1009567162,1009567162,1009570164,1009571295,1009571295,1009571295,1009576214,1009576839,1009576839,1009576839,1009579449,1009579449,1009579449,1009580612,1009580612,1009580612,1009585079,1009585479,1009585479,1009585479,1009587843,1009589125,1009589125,1009589125,1009593905,1009596964,1009597983,1009597983,1009597983,1009602704,1009603249,1009603249,1009603249,1009605648,1009605648,1009605648,1009606588,1009606588,1009606588,1009610542,1009610910,1009610910,1009610910,1009612091,1009612091,1009612091,1009612625,1009612625,1009612625,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,1009612727,100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1012707034, 1012743153, 1012781185, 1012813609, 1012833330, 1012850055, 1012869005, 1012888268, 1012906669, 1012936416, 1012962399, 1012994408, 1013020654, 1013050400, 1013079707, 1013109511, 1013134905, 1013164469, 1013191884, 1013222539, 1013249569, 1013282218, 1013324567, 1013355530, 1013384427, 1013419591, 1013448994, 1013485946, 1013512103, 1013537853, 1013559471, 1013586245, 1013611681, 1013640152, 1013670300, 1013697353, 1013725228, 1013753988, 1013783572, 1013815407, 1013840139, 1013868396, 1013894815, 1013925418, 1013949394, 1013978228, 1014004246, 1014031969, 1014060884, 1014089826, 1014119981, 1014151371, 1014181978, 1014218099, 1014249258, 1014284653, 1014318638, 1014358906, 1014399309, 1014444630, 1014481397, 1014495905, 1014509025, 1014535928, 1014563940, 1014589265, 1014610195, 1014629932, 1014653255, 1014670098, 1014686438, 1014702097, 1014722032, 1014741619, 1014798043, 1014814532, 1014852877, 1014876918, 1014904380, 1014932039, 1014973929, 1014997287, 1015026125, 1015061974, 1015087309, 1015113510, 1015135852, 1015159056, 1015185819, 1015228379, 1015250488, 1015271017, 1015289450, 1015309872, 1015328272, 1015341936, 1015364707, 1015387465, 1015408731, 1015431750, 1015447245, 1015472221, 1015491228, 1015505918, 1015524801, 1015545383, 1015569540, 1015593871, 1015618664, 1015640099, 1015678515, 1015699350, 1015725535, 1015785030, 1015803327, 1015824159, 1015858645, 1015891609, 1015922239, 1015951183, 1015979955, 1016008978, 1016031641, 1016057740, 1016079043, 1016104694, 1016129811, 1016151052, 1016165407, 1016177373, 1016191022, 1016200472, 1016250151, 1056228407, 1056230992, 1056231392, 1056270611, 1056338908, 1056384133, 1056391587, 1056418910, 1056453291, 1056513346, 1056583093, 1056651954, 1056690748, 1056711160, 1056736179, 1056748730, 1056756880, 1056764897, 1056772435, 1056784481, 1056800788, 1056808378, 1056818149, 1056830024, 1056830674, 1056830948, 1056831077, 1056831557, 1056831855, 1056837634, 1056856210, 1056920476, 1056980405, 1057041128, 1057088057, 1057121109, 1057151343, 1057220556, 1057280512, 1057341346, 1057404844, 1057405393, 1057407766, 1057472510, 1057500270, 1057540059, 1057593126, 1057647548, 1057687877, 1057710265, 1057732748, 1057755508, 1057764774, 1057772053, 1057778726, 1057785414, 1057793601, 1057801259, 1057807129, 1057813938, 1057816042, 1057829286, 1057848917, 1057892838, 1057897019, 1057932757, 1058003323, 1058069207, 1058128311, 1058168238, 1058218998, 1058252311, 1058301785, 1058344218, 1058357000, 1058360844, 1058373425, 1058397930, 1058419186, 1058452270, 1058454546, 1058497064, 1058498206, 1058498418, 1058498765, 1058521789, 1058551450, 1058552621, 1058555677, 1058558898, 1058563076, 1058588013, 1058598160, 1058621590, 1058655000, 1058676193, 1058707466, 1058970477, 1059006627, 1059046569, 1059191651, 1059236201, 1059303266, 1059358502, 1059421117, 1059465155, 1059519820, 1059570910, 1059621387, 1059666507, 1059721386, 1059764182, 1059769188, 1059785227, 1059879568, 1059945488, 1060020932, 1060078214, 1060220736, 1060379660, 1060464896, 1060518323, 1060593805, 1060658653, 1060713777, 1060747606, 1060788851, 1060803885, 1060857834, 1060887245, 1060936297, 1060966196, 1061000351, 1061056459, 1061100121, 1061192543, 1061226354, 1061229431, 1061238745, 1061286706, 1061337836, 1061360120, 1061417200, 1061498969, 1061555745, 1061610192, 1061671177, 1061719303, 1061763997, 1061784989, 1061817865, 1061883307, 1061935814, 1062011815, 1062066024, 1062133124, 1062316231, 1062405207, 1062458588, 1062503690, 1062550078, 1062590642, 1062648864, 1062695432, 1062723341, 1062756112, 1062784494, 1062812433, 1062854625, 1062915395, 1062972086, 1063010691, 1063064215, 1063123899, 1063221077, 1063265473, 1063308569, 1063509640, 1063558458, 1063625399, 1063754711, 1063792624, 1063859378, 1064104831, 1064194324, 1064238851, 1064271160, 1064300598, 1064328041, 1064355810, 1064384228, 1064413860, 1064442496, 1064475866, 1064569994, 1064629411, 1064679940, 1064718119, 1064843969, 1064885497, 1064925689, 1064980978, 1065025220, 1065066418, 1065122253, 1065166128, 1065199557, 1065231169, 1065248305, 1065277478, 1065295445, 1065311551, 1065327181, 1065338945, 1065347319, 1065358527, 1065423047, 1065464747, 1065551063, 1065640480, 1065683380, 1065752109, 1065853211, 1065872621, 1065886164, 1065906994, 1065929861, 1065949955, 1065970146, 1065989088, 1066036678, 1066082795, 1066127201, 1066177817, 1066234447, 1066280972, 1066333751, 1066370058, 1066403950, 1066434334, 1066459557, 1066470978, 1066476567, 1066483566, 1066495992, 1066526112, 1066576205, 1066628890, 1066688041, 1066748034, 1066802947, 1066855084, 1066901151, 1066957298, 1067018957, 1067077304, 1067126796, 1067176861, 1067220040, 1067242688, 1067290903, 1067350629, 1067420133, 1067481998, 1067541099, 1067577644, 1067619695, 1067661438, 1067690194, 1067717417, 1067747135, 1067774115, 1067802803, 1067861256, 1067911434, 1067941481, 1067982050, 1068035448, 1068088468, 1068111529, 1068135671, 1068160643, 1068189422, 1068212316, 1068237222, 1068269606, 1068303917, 1068329049, 1068346742, 1068348694, 1068386854, 1068425051, 1068452881, 1068458890, 1068468409, 1068469248, 1068469816, 1068470404, 1068471261, 1068471940, 1068474412, 1068506229, 1068541461, 1068570954, 1068623508, 1068682681, 1068719362, 1068741812, 1068773099, 1068806810, 1068837181, 1068851165, 1068855954, 1068875462, 1068897960, 1068917460, 1068943958, 1068968307, 1068982667, 1069002723, 1069020495, 1069057623, 1069125047, 1069205891, 1069239243, 1069260809, 1069283978, 1069310065, 1069337749, 1069359150, 1069378203, 1069385926, 1069408082, 1069454240, 1069505573, 1069547701, 1069590743, 1069703349, 1069823743, 1069863124, 1069957907, 1069991317, 1070012152, 1070039926, 1070071218, 1070086450, 1070096253, 1070099006, 1070109605, 1070151839, 1070176004, 1070188633, 1070229599, 1070274894, 1070325009, 1070371827, 1070420334, 1070483039, 1070525071, 1070555660, 1070594551, 1070637080, 1070680461, 1070724012, 1070790692, 1070943044, 1071200714, 1071239805, 1071464239, 1071636093, 1071703686, 1071767896, 1071811891, 1071860803, 1071928104, 1072017180, 1072118436, 1072207682, 1072297363, 1072393937, 1072508116, 1072582575, 1072632153, 1072728393, 1072839514, 1072917096, 1072972615, 1073027777, 1073056962, 1073111354, 1073142092, 1073196803, 1073244305, 1073366397, 1073503489, 1073644968, 1073725124, 1073807929, 1073882320, 1073948833, 1074028106], saving chi 1941270028 with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009070858,1009221558,1009235002,1009235002,1009235002,1009279344,1009279354,1009280658,1009282610,1009285760,1009285769,1009287136,1009288507,1009288553,1009289514,1009290976,1009291022,1009292131,1009293461,1009293501,1009302646,1009302928,1009314293,1009325390,1009325689,1009331815,1009337446,1009343215,1009348721,1009360422,1009360714,1009366174,1009370143,1009378380,1009378420,1009382214,1009387311,1009387469,1009397627,1009397723,1009407257,1009418251,1009418933,1009427417,1009430105,1009431390,1009433085,1009433142,1009434051,1009434051,1009434051,1009434379,1009434379,1009434379,1009434692,1009434692,1009434692,1009435685,1009436485,1009436971,1009436971,1009436971,1009437041,1009437246,1009438332,1009438588,1009438588,1009438588,1009440276,1009440285,1009440276,1009440276,1009442468,1009442504,1009442535,1009442535,1009442535,1009444074,1009444128,1009444128,1009444128,1009445420,1009445545,1009446900,1009446900,1009446900,1009448273,1009448394,1009448394,1009448394,1009449796,1009449796,1009449796,1009451627,1009451638,1009451748,1009451748,1009451748,1009452468,1009452468,1009452468,1009452959,1009452959,1009452959,1009452983,1009454194,1009454251,1009454341,1009454341,1009454341,1009455529,1009457023,1009457036,1009457226,1009457226,1009457226,1009460748,1009460748,1009460748,1009460965,1009466381,1009466450,1009467105,1009467105,1009467105,1009471965,1009471965,1009471965,1009472266,1009477701,1009478114,1009478114,1009478114,1009481717,1009481717,1009481717,1009482985,1009482985,1009482985,1009487457,1009487652,1009487954,1009487954,1009487954,1009489083,1009489225,1009489312,1009489312,1009489312,1009490313,1009490313,1009490313,1009490483,1009495058,1009495486,1009495486,1009495486,1009498951,1009498951,1009498951,1009500506,1009500506,1009500506,1009500759,1009506262,1009506268,1009506268,1009506282,1009506744,1009506744,1009506744,1009509718,1009510176,1009510176,1009510176,1009511667,1009511667,1009511667,1009517337,1009517539,1009517847,1009517847,1009517847,1009521431,1009521431,1009521431,1009521605,1009525338,1009525352,1009525621,1009525621,1009525621,1009528265,1009529520,1009529520,1009529520,1009533044,1009533051,1009533522,1009533522,1009533522,1009536212,1009536212,1009536212,1009540623,1009540769,1009541042,1009541042,1009541042,1009543632,1009543632,1009543632,1009544883,1009545320,1009545320,1009545320,1009549111,1009549845,1009549845,1009549845,1009551220,1009551220,1009551220,1009552743,1009553918,1009553918,1009553918,1009557768,1009558264,1009558264,1009558264,1009560604,1009560604,1009560604,1009562083,1009562083,1009562083,1009566561,1009567163,1009567163,1009567163,1009570165,1009571296,1009571296,1009571296,1009576215,1009576840,1009576840,1009576840,1009579450,1009579450,1009579450,1009580613,1009580613,1009580613,1009585080,1009585480,1009585480,1009585480,1009587844,1009589126,1009589126,1009589126,1009593906,1009596965,1009597984,1009597984,1009597984,1009602705,1009603250,1009603250,1009603250,1009605649,1009605649,1009605649,1009606589,1009606589,1009606589,1009610543,1009610911,1009610911,1009610911,1009612092,1009612092,1009612092,1009612626,1009612626,1009612626,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,1009612728,100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1057041129, 1057088058, 1057121110, 1057151344, 1057220557, 1057280513, 1057341347, 1057404845, 1057405394, 1057407767, 1057472512, 1057500271, 1057540060, 1057593130, 1057647549, 1057687878, 1057710266, 1057732749, 1057755509, 1057764775, 1057772055, 1057778727, 1057785415, 1057793602, 1057801260, 1057807130, 1057813939, 1057816043, 1057829287, 1057848918, 1057892839, 1057897020, 1057932758, 1058003324, 1058069208, 1058128312, 1058168239, 1058218999, 1058252313, 1058301786, 1058344219, 1058357001, 1058360845, 1058373426, 1058397931, 1058419187, 1058452271, 1058454547, 1058497065, 1058498207, 1058498419, 1058498766, 1058521790, 1058551451, 1058552622, 1058555678, 1058558899, 1058563077, 1058588014, 1058598161, 1058621591, 1058655001, 1058676194, 1058707467, 1058970478, 1059006628, 1059046570, 1059191652, 1059236202, 1059303267, 1059358503, 1059421118, 1059465156, 1059519821, 1059570911, 1059621388, 1059666508, 1059721387, 1059764183, 1059769189, 1059785228, 1059879569, 1059945489, 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1068189423, 1068212317, 1068237223, 1068269607, 1068303918, 1068329050, 1068346743, 1068348695, 1068386855, 1068425052, 1068452882, 1068458891, 1068468410, 1068469249, 1068469817, 1068470405, 1068471262, 1068471941, 1068474413, 1068506230, 1068541462, 1068570955, 1068623509, 1068682682, 1068719363, 1068741813, 1068773100, 1068806811, 1068837182, 1068851166, 1068855955, 1068875463, 1068897961, 1068917461, 1068943959, 1068968308, 1068982668, 1069002724, 1069020496, 1069057624, 1069125048, 1069205892, 1069239244, 1069260810, 1069283979, 1069310066, 1069337750, 1069359151, 1069378204, 1069385927, 1069408083, 1069454241, 1069505574, 1069547702, 1069590744, 1069703351, 1069823744, 1069863125, 1069957908, 1069991318, 1070012153, 1070039927, 1070071219, 1070086451, 1070096254, 1070099007, 1070109606, 1070151840, 1070176005, 1070188634, 1070229600, 1070274895, 1070325011, 1070371828, 1070420335, 1070483040, 1070525072, 1070555661, 1070594552, 1070637081, 1070680462, 1070724013, 1070790693, 1070943045, 1071200715, 1071239806, 1071464240, 1071636094, 1071703687, 1071767897, 1071811892, 1071860804, 1071928105, 1072017181, 1072118437, 1072207683, 1072297364, 1072393938, 1072508117, 1072582576, 1072632154, 1072728394, 1072839515, 1072917097, 1072972616, 1073027778, 1073056963, 1073111355, 1073142093, 1073196804, 1073244307, 1073366398, 1073503490, 1073644969, 1073725125, 1073807930, 1073882321, 1073948834, 1074028107], saving chi 1941270027 with no changes select cps.photo_id, cps.thcl, h.hashtag, avg(cps.score), p.text,cps.hashtag_id FROM MTRPhoto.class_photo_score cps inner join MTRBack.hashtags h on h.hashtag_id = cps.hashtag_id inner join MTRBack.view_photos_with_urls_250912 p on cps.photo_id = p.photo_id where cps.photo_id in(1009070859,1009221559,1009235003,1009235003,1009235003,1009279345,1009279355,1009280659,1009282611,1009285761,1009285770,1009287137,1009288508,1009288554,1009289515,1009290977,1009291023,1009292132,1009293462,1009293502,1009302647,1009302929,1009314294,1009325391,1009325690,1009331816,1009337447,1009343216,1009348722,1009360424,1009360715,1009366175,1009370144,1009378381,1009378421,1009382215,1009387312,1009387470,1009397629,1009397724,1009407258,1009418252,1009418934,1009427418,1009430106,1009431391,1009433086,1009433143,1009434052,1009434052,1009434052,1009434380,1009434380,1009434380,1009434693,1009434693,1009434693,1009435686,1009436486,1009436972,1009436972,1009436972,1009437042,1009437247,1009438333,1009438589,1009438589,1009438589,1009440277,1009440286,1009440277,1009440277,1009442469,1009442505,1009442536,1009442536,1009442536,1009444075,1009444129,1009444129,1009444129,1009445421,1009445547,1009446901,1009446901,1009446901,1009448274,1009448395,1009448395,1009448395,1009449797,1009449797,1009449797,1009451628,1009451639,1009451749,1009451749,1009451749,1009452469,1009452469,1009452469,1009452960,1009452960,1009452960,1009452984,1009454195,1009454252,1009454342,1009454342,1009454342,1009455530,1009457024,1009457037,1009457227,1009457227,1009457227,1009460749,1009460749,1009460749,1009460966,1009466382,1009466451,1009467106,1009467106,1009467106,1009471966,1009471966,1009471966,1009472267,1009477703,1009478116,1009478116,1009478116,1009481718,1009481718,1009481718,1009482986,1009482986,1009482986,1009487458,1009487653,1009487955,1009487955,1009487955,1009489084,1009489226,1009489313,1009489313,1009489313,1009490314,1009490314,1009490314,1009490484,1009495059,1009495487,1009495487,1009495487,1009498952,1009498952,1009498952,1009500507,1009500507,1009500507,1009500761,1009506263,1009506269,1009506269,1009506283,1009506745,1009506745,1009506745,1009509719,1009510177,1009510177,1009510177,1009511668,1009511668,1009511668,1009517338,1009517540,1009517848,1009517848,1009517848,1009521432,1009521432,1009521432,1009521606,1009525339,1009525353,1009525622,1009525622,1009525622,1009528266,1009529521,1009529521,1009529521,1009533046,1009533053,1009533523,1009533523,1009533523,1009536213,1009536213,1009536213,1009540624,1009540770,1009541043,1009541043,1009541043,1009543633,1009543633,1009543633,1009544884,1009545321,1009545321,1009545321,1009549112,1009549846,1009549846,1009549846,1009551221,1009551221,1009551221,1009552744,1009553919,1009553919,1009553919,1009557769,1009558265,1009558265,1009558265,1009560605,1009560605,1009560605,1009562084,1009562084,1009562084,1009566562,1009567164,1009567164,1009567164,1009570166,1009571297,1009571297,1009571297,1009576216,1009576841,1009576841,1009576841,1009579451,1009579451,1009579451,1009580614,1009580614,1009580614,1009585081,1009585481,1009585481,1009585481,1009587845,1009589127,1009589127,1009589127,1009593907,1009596966,1009597985,1009597985,1009597985,1009602706,1009603251,1009603251,1009603251,1009605650,1009605650,1009605650,1009606590,1009606590,1009606590,1009610544,1009610912,1009610912,1009610912,1009612093,1009612093,1009612093,1009612627,1009612627,1009612627,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,1009612729,100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1012707036, 1012743155, 1012781187, 1012813611, 1012833332, 1012850057, 1012869007, 1012888272, 1012906671, 1012936418, 1012962401, 1012994410, 1013020656, 1013050402, 1013079709, 1013109513, 1013134907, 1013164471, 1013191886, 1013222541, 1013249571, 1013282220, 1013324569, 1013355532, 1013384429, 1013419593, 1013448996, 1013485948, 1013512107, 1013537855, 1013559473, 1013586247, 1013611683, 1013640154, 1013670302, 1013697355, 1013725230, 1013753990, 1013783574, 1013815409, 1013840141, 1013868398, 1013894817, 1013925420, 1013949396, 1013978230, 1014004248, 1014031971, 1014060886, 1014089828, 1014119983, 1014151374, 1014181980, 1014218101, 1014249260, 1014284655, 1014318640, 1014358908, 1014399311, 1014444632, 1014481399, 1014495907, 1014509027, 1014535930, 1014563942, 1014589267, 1014610197, 1014629934, 1014653257, 1014670100, 1014686440, 1014702099, 1014722034, 1014741621, 1014798045, 1014814534, 1014852879, 1014876920, 1014904382, 1014932041, 1014973931, 1014997290, 1015026127, 1015061976, 1015087311, 1015113512, 1015135854, 1015159058, 1015185821, 1015228381, 1015250490, 1015271019, 1015289452, 1015309874, 1015328274, 1015341940, 1015364709, 1015387467, 1015408733, 1015431752, 1015447247, 1015472223, 1015491230, 1015505920, 1015524803, 1015545385, 1015569542, 1015593873, 1015618668, 1015640101, 1015678517, 1015699352, 1015725537, 1015785032, 1015803329, 1015824161, 1015858647, 1015891611, 1015922241, 1015951185, 1015979957, 1016008980, 1016031643, 1016057742, 1016079045, 1016104696, 1016129813, 1016151054, 1016165409, 1016177375, 1016191024, 1016200474, 1016250153, 1056228409, 1056230994, 1056231395, 1056270613, 1056338910, 1056384135, 1056391589, 1056418912, 1056453293, 1056513348, 1056583095, 1056651956, 1056690750, 1056711162, 1056736181, 1056748732, 1056756882, 1056764899, 1056772437, 1056784483, 1056800790, 1056808380, 1056818151, 1056830026, 1056830676, 1056830950, 1056831079, 1056831559, 1056831857, 1056837636, 1056856212, 1056920478, 1056980407, 1057041130, 1057088059, 1057121111, 1057151345, 1057220558, 1057280514, 1057341348, 1057404846, 1057405395, 1057407768, 1057472514, 1057500272, 1057540061, 1057593131, 1057647550, 1057687879, 1057710267, 1057732750, 1057755510, 1057764776, 1057772056, 1057778728, 1057785416, 1057793603, 1057801261, 1057807131, 1057813940, 1057816044, 1057829288, 1057848919, 1057892840, 1057897021, 1057932759, 1058003325, 1058069209, 1058128313, 1058168240, 1058219000, 1058252316, 1058301787, 1058344220, 1058357002, 1058360846, 1058373427, 1058397932, 1058419188, 1058452272, 1058454548, 1058497066, 1058498208, 1058498420, 1058498767, 1058521791, 1058551452, 1058552623, 1058555679, 1058558900, 1058563078, 1058588015, 1058598162, 1058621592, 1058655002, 1058676195, 1058707468, 1058970479, 1059006629, 1059046571, 1059191653, 1059236204, 1059303268, 1059358504, 1059421119, 1059465157, 1059519822, 1059570912, 1059621389, 1059666509, 1059721388, 1059764184, 1059769190, 1059785229, 1059879570, 1059945490, 1060020934, 1060078216, 1060220738, 1060379662, 1060464898, 1060518325, 1060593807, 1060658655, 1060713779, 1060747608, 1060788853, 1060803887, 1060857836, 1060887247, 1060936299, 1060966198, 1061000354, 1061056461, 1061100123, 1061192545, 1061226356, 1061229433, 1061238747, 1061286708, 1061337838, 1061360122, 1061417202, 1061498971, 1061555747, 1061610194, 1061671179, 1061719305, 1061763999, 1061784991, 1061817867, 1061883309, 1061935816, 1062011817, 1062066026, 1062133126, 1062316233, 1062405209, 1062458590, 1062503692, 1062550081, 1062590644, 1062648866, 1062695434, 1062723343, 1062756114, 1062784496, 1062812435, 1062854627, 1062915397, 1062972088, 1063010693, 1063064217, 1063123901, 1063221080, 1063265475, 1063308571, 1063509642, 1063558460, 1063625401, 1063754713, 1063792626, 1063859380, 1064104833, 1064194326, 1064238853, 1064271162, 1064300600, 1064328043, 1064355812, 1064384230, 1064413862, 1064442498, 1064475869, 1064569997, 1064629413, 1064679942, 1064718121, 1064843971, 1064885499, 1064925691, 1064980980, 1065025222, 1065066420, 1065122255, 1065166130, 1065199559, 1065231171, 1065248307, 1065277480, 1065295447, 1065311553, 1065327183, 1065338948, 1065347321, 1065358529, 1065423049, 1065464749, 1065551065, 1065640482, 1065683382, 1065752113, 1065853213, 1065872623, 1065886166, 1065906996, 1065929863, 1065949957, 1065970148, 1065989090, 1066036680, 1066082797, 1066127203, 1066177820, 1066234449, 1066280974, 1066333753, 1066370060, 1066403952, 1066434336, 1066459559, 1066470980, 1066476569, 1066483568, 1066495994, 1066526114, 1066576207, 1066628892, 1066688043, 1066748036, 1066802949, 1066855086, 1066901153, 1066957300, 1067018959, 1067077306, 1067126798, 1067176863, 1067220042, 1067242690, 1067290905, 1067350631, 1067420135, 1067482000, 1067541101, 1067577646, 1067619697, 1067661440, 1067690196, 1067717419, 1067747137, 1067774117, 1067802805, 1067861260, 1067911436, 1067941483, 1067982052, 1068035450, 1068088470, 1068111531, 1068135673, 1068160645, 1068189424, 1068212318, 1068237224, 1068269608, 1068303919, 1068329051, 1068346744, 1068348696, 1068386856, 1068425053, 1068452883, 1068458892, 1068468411, 1068469250, 1068469818, 1068470406, 1068471263, 1068471942, 1068474414, 1068506231, 1068541463, 1068570956, 1068623510, 1068682683, 1068719364, 1068741814, 1068773101, 1068806812, 1068837183, 1068851167, 1068855956, 1068875464, 1068897962, 1068917462, 1068943960, 1068968309, 1068982669, 1069002725, 1069020497, 1069057625, 1069125049, 1069205893, 1069239245, 1069260811, 1069283980, 1069310067, 1069337751, 1069359152, 1069378205, 1069385928, 1069408084, 1069454243, 1069505575, 1069547703, 1069590745, 1069703352, 1069823745, 1069863126, 1069957909, 1069991319, 1070012154, 1070039928, 1070071220, 1070086452, 1070096255, 1070099008, 1070109607, 1070151841, 1070176006, 1070188635, 1070229601, 1070274896, 1070325013, 1070371829, 1070420336, 1070483041, 1070525073, 1070555662, 1070594553, 1070637082, 1070680463, 1070724014, 1070790694, 1070943046, 1071200716, 1071239807, 1071464241, 1071636095, 1071703688, 1071767898, 1071811893, 1071860805, 1071928106, 1072017182, 1072118439, 1072207684, 1072297365, 1072393939, 1072508118, 1072582577, 1072632155, 1072728395, 1072839516, 1072917098, 1072972617, 1073027779, 1073056964, 1073111356, 1073142094, 1073196805, 1073244308, 1073366399, 1073503491, 1073644970, 1073725126, 1073807931, 1073882322, 1073948835, 1074028108], saving chi 1941270026 with no changes chi 1941270032 saved with no changes chi 1941270031 saved with no changes chi 1941270035 saved with no changes chi 1941270037 saved with no changes chi 1941270041 saved with no changes chi 1941270012 saved with no changes chi 1941270013 saved with no changes chi 1941607380 saved with no changes chi 1941607381 saved with no changes chi 2202875936 saved with no changes chi 1941270008 saved with no changes chi 1941270016 saved with no changes chi 1941607382 saved with no changes chi 1941270034 saved with no changes chi 2202875937 saved with no changes chi 1941270010 saved with no changes chi 1941270005 saved with no changes chi 1941270007 saved with no changes chi 1941270024 saved with no changes chi 1941270011 saved with no changes chi 2202875938 saved with no changes chi 1941270023 saved with no changes chi 1941607379 saved with no changes chi 1941270006 saved with no changes chi 1941270009 saved with no changes 76 crops to save insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 82 chid ids of type : 2913 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1009068683,1009068724) and `type` in (2913) Loaded 82 chid ids of type : 2913 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2099910103,2099910104,2099910105,2099910106,2099910107,2099910108,2099910109,2099910110,2099910111,2099910112,2099910113,2099910114,2099910115,3974615162,3974615163,2099910116,2099910117,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910135,2099910136,2099910137,2099910138,2099910139,2099910140,2099910141,2099910142,2099910143,2099910144,2099910145,2099910146,2099910147,2099910148,2099910149,3974615164,3974615165,3974615166,3974615167,2099910150,2099910151,2099910152,2099910153,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2099910103,2099910104,2099910105,2099910106,2099910107,2099910108,2099910109,2099910110,2099910111,2099910112,2099910113,2099910114,2099910115,3974615162,3974615163,2099910116,2099910117,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910135,2099910136,2099910137,2099910138,2099910139,2099910140,2099910141,2099910142,2099910143,2099910144,2099910145,2099910146,2099910147,2099910148,2099910149,3974615164,3974615165,3974615166,3974615167,2099910150,2099910151,2099910152,2099910153,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2099910103,2099910104,2099910105,2099910106,2099910107,2099910108,2099910109,2099910110,2099910111,2099910112,2099910113,2099910114,2099910115,3974615162,3974615163,2099910116,2099910117,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910135,2099910136,2099910137,2099910138,2099910139,2099910140,2099910141,2099910142,2099910143,2099910144,2099910145,2099910146,2099910147,2099910148,2099910149,3974615164,3974615165,3974615166,3974615167,2099910150,2099910151,2099910152,2099910153,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] End of step merge_mask_thcl_custom After datou_step_exec type output : time spend for datou_step_exec : 0.2777998447418213 time spend to save output : 4.982948303222656e-05 total time spend for step 1 : 0.2778496742248535 step2:rle_unique_nms_with_priority Thu Sep 25 17:07:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : ['temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg'] We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : ['temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg'] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg': 1009068683, 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg': 1009068724} map_photo_id_path_extension : {1009068683: {'path': 'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'extension': 'jpg'}, 1009068724: {'path': 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg on traite la photo : temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1009068683,1009068724) and `type` in (2913) and hashtag_id in (2107755846,492636447,492645504,681467679) Loaded 43 chid ids of type : 2913 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2099910116,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) +++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2099910116,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2099910116,2099910118,2099910119,2099910120,2099910121,2099910122,2099910123,2099910124,2099910125,2099910126,2099910127,2099910128,2099910129,2099910130,2099910131,2099910132,2099910133,2099910134,2099910154,2099910155,2099910156,2099910157,2099910158,2099910159,2099910160,2099910161,2099910162,2202876163,2099910163,2099910164,2099910165,2099910166,2202876164,2099910167,2099910168,2099910169,2099910170,2099910171,2202876165,2099910172,2099910173,2099910174,2099910175) nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 2.170149803161621 create new chi : 2.9325485229492188e-05 proportion hashtag : pet_clair 0.5317132844650205 proportion hashtag : contaminant 0.002766525205761317 time to delete rle : 0.03200721740722656 save time : 2.193450927734375e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 2.448253631591797 create new chi : 3.123283386230469e-05 proportion hashtag : pet_clair 0.5582751414609054 time to delete rle : 0.013484477996826172 save time : 9.298324584960938e-06 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {1009068683: (0.002588053987919006, 'Should be the crop_list due to order', 0.005176107975838012), 1009068724: (0.002588053987919006, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 4.838374853134155 time spend to save output : 0.00022220611572265625 total time spend for step 2 : 4.838597059249878 step3:ventilate_hashtags_in_portfolio Thu Sep 25 17:07:18 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg': 1009068683, 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg': 1009068724} map_photo_id_path_extension : {1009068683: {'path': 'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'extension': 'jpg'}, 1009068724: {'path': 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 3373196 get user id for portfolio 3373196 get sub ptf for main ptf 3373196, type 2913 and hashtags [] SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3373196 AND mptpi.`type`=2913 AND mptpi.`min_score`=0.7 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3373196 AND mptpi.`type`=2913 AND mptpi.`min_score`=0.7 To do returned map {'bouchon': {'main_port_id': 3373196, 'sub_port_id': 3373210, 'hashtag': 'bouchon', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 408, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'contaminant': {'main_port_id': 3373196, 'sub_port_id': 3373211, 'hashtag': 'contaminant', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 409, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'environement': {'main_port_id': 3373196, 'sub_port_id': 3373212, 'hashtag': 'environement', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 410, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'etiquette': {'main_port_id': 3373196, 'sub_port_id': 3373213, 'hashtag': 'etiquette', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 411, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'mal_croppe': {'main_port_id': 3373196, 'sub_port_id': 3373214, 'hashtag': 'mal_croppe', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 412, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'multiple_objets': {'main_port_id': 3373196, 'sub_port_id': 3373215, 'hashtag': 'multiple_objets', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 413, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}, 'pet_clair': {'main_port_id': 3373196, 'sub_port_id': 3373216, 'hashtag': 'pet_clair', 'pht': 2913, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 414, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 10), 'last_updated_at_asc': datetime.datetime(2021, 1, 26, 13, 9, 50)}} insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373210 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='bouchon' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373211 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='contaminant' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373212 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='environement' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373213 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='etiquette' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373214 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='mal_croppe' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373215 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='multiple_objets' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3373216 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3373196 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=2913 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='pet_clair' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; To do ! Use context local managing function ! After datou_step_exec type output : time spend for datou_step_exec : 0.4949378967285156 time spend to save output : 6.842613220214844e-05 total time spend for step 3 : 0.4950063228607178 step4:final Thu Sep 25 17:07:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 : {1009068683: (0.002588053987919006, 'Should be the crop_list due to order', 0.005176107975838012), 1009068724: (0.002588053987919006, 'Should be the crop_list due to order', 0.0)} input_args_next_step : {1009068683: ()} output_args : {1009068683: (0.002588053987919006, 'Should be the crop_list due to order', 0.005176107975838012), 1009068724: (0.002588053987919006, 'Should be the crop_list due to order', 0.0)} args : 1009068683 depend.output_id : 0 input_args_next_step : {1009068683: (0.002588053987919006,), 1009068724: ()} output_args : {1009068683: (0.002588053987919006, 'Should be the crop_list due to order', 0.005176107975838012), 1009068724: (0.002588053987919006, 'Should be the crop_list due to order', 0.0)} args : 1009068724 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : (0.002588053987919006,) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg': 1009068683, 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg': 1009068724} map_photo_id_path_extension : {1009068683: {'path': 'temp/1758812833_3157952_1009068683_4beb092fd180a8b620f754bb89015722.jpg', 'extension': 'jpg'}, 1009068724: {'path': 'temp/1758812833_3157952_1009068724_3e705379f97632c4a2fd676e348a335d.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step final ! query to retrieve results for portfolio 3373196 : SELECT photo_id, hashtag_id, ratio from MTRPhoto.photo_carac_ratio where hashtag_type = 2914 and photo_id in (1009068683,1009068724); insert ignore into MTRUser.portfolio_carac_ratio (portfolio_id, hashtag_type, hashtag_id, value) values (%s,%s,%s,%s) on DUPLICATE KEY UPDATE value=VALUES(value) After datou_step_exec type output : time spend for datou_step_exec : 0.05513477325439453 time spend to save output : 7.128715515136719e-05 total time spend for step 4 : 0.0552060604095459 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True original output for save of step final : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} new output for save of step final : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} [1009068683, 1009068724] map_info['map_portfolio_photo'] : {3373196: [1009068724, 1009068683]} final : True mtd_id 2719 list_pids : [1009068683, 1009068724] Looping around the photos to save general results len do output : 2 /1009068683.Didn't retrieve data . /1009068724.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('2719', None, None, None, None, None, None, None, None) ('2719', '3373196', '1009068683', None, None, None, None, None, None) ('2719', None, None, None, None, None, None, None, None) ('2719', '3373196', '1009068724', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('2719', '3373196', '1009068683', '0.0025316977085267163', None, None, None, None, None), ('2719', '3373196', '1009068724', '0.0025316977085267163', None, None, None, None, None)] time used for this insertion : 0.018393993377685547 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 4 output : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} ############################### TEST rubbia_carac_jrm_no_mask_detect ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3164 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3164 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3164 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3164 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Step 7557 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 7556 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 7561 merge_mask_and_thcl is not consistent : 3 used against 1 in the step definition ! WARNING : number of inputs for step 7558 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7560 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7559 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7560 doesn't seem to be define in the database( WARNING : type of input 3 of step 7559 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7556 have datatype=6 whereas input 0 of step 7561 have datatype=20 WARNING : type of output 1 of step 7561 doesn't seem to be define in the database( WARNING : type of input 1 of step 7558 doesn't seem to be define in the database( WARNING : type of output 2 of step 7561 doesn't seem to be define in the database( WARNING : type of input 1 of step 7560 doesn't seem to be define in the database( DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : crop_condition, thcl, argmax, merge_mask_and_thcl, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3364276) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3364276) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1008922130, 'portfolio_id': 3364276}, {'photo_id': 1008922101, 'portfolio_id': 3364276}, {'photo_id': 1008922097, 'portfolio_id': 3364276}, {'photo_id': 1008922095, 'portfolio_id': 3364276}, {'photo_id': 1008922073, 'portfolio_id': 3364276}, {'photo_id': 1008922072, 'portfolio_id': 3364276}, {'photo_id': 1008922003, 'portfolio_id': 3364276}, {'photo_id': 1008922002, 'portfolio_id': 3364276}, {'photo_id': 1008921786, 'portfolio_id': 3364276}, {'photo_id': 1008921657, 'portfolio_id': 3364276}, {'photo_id': 1008921656, 'portfolio_id': 3364276}, {'photo_id': 1008921602, 'portfolio_id': 3364276}, {'photo_id': 1008921601, 'portfolio_id': 3364276}, {'photo_id': 1008921600, 'portfolio_id': 3364276}] map_portfolio_id_photo_id: {3364276: [1008922130, 1008922101, 1008922097, 1008922095, 1008922073, 1008922072, 1008922003, 1008922002, 1008921786, 1008921657, 1008921656, 1008921602, 1008921601, 1008921600]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1008922130 begin to download photo : 1008922095 begin to download photo : 1008922003 begin to download photo : 1008921657 begin to download photo : 1008921601 download finish for photo 1008922003 begin to download photo : 1008922002 download finish for photo 1008921657 begin to download photo : 1008921656 download finish for photo 1008922130 begin to download photo : 1008922101 download finish for photo 1008922095 begin to download photo : 1008922073 download finish for photo 1008921601 begin to download photo : 1008921600 download finish for photo 1008922002 begin to download photo : 1008921786 download finish for photo 1008921656 begin to download photo : 1008921602 download finish for photo 1008922073 begin to download photo : 1008922072 download finish for photo 1008922101 begin to download photo : 1008922097 download finish for photo 1008921600 download finish for photo 1008922072 download finish for photo 1008921786 download finish for photo 1008922097 download finish for photo 1008921602 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 14 ; length of list_pids : 14 ; length of list_args : 14 ##### After load_data_input time to download the photos : 1.1914699077606201 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 7 step1:crop_condition Thu Sep 25 17:07:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} param_json : {'upload_type': 'python', 'photo_hashtag_type': 3336, 'token': '7c6bc181426bc5913186d8428a0fbc15', 'feed_id_new_photos': 3364311, 'crop_type': 'rle_png_transparent', 'host': 'www.fotonower.com', 'filter': {'teint_dans_la_masse': {'min_score': 0.7}, 'autre_refus': {'min_score': 0.7}, 'carton_gris': {'min_score': 0.7}, 'cartonnette': {'min_score': 0.7}, 'carton_brun': {'min_score': 0.7}, 'plastique': {'min_score': 0.7}, 'kraft': {'min_score': 0.7}, 'metal': {'min_score': 0.7}}} Loading chi in step crop with photo_hashtag_type : 3336 Loading chi in step crop for list_pids : 14 ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and `type` in (3336) Loaded 121 chid ids of type : 3336 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2099961860,2099961861,2099961862,2099961863,2099961864,2099961865,2099961866,2099961867,2099961868,2099961869,2099961870,2099961871,2099961872,2099961873,2099961874,2099961875,2099961876,2099961877,2099961878,2099961879,2099961880,2099961881,2099961882,2099961883,2099961884,2099961885,2099961886,2099961887,2099961888,2099961889,2099961890,2099961891,2099961892,2099961893,2099961894,2099961895,2099961896,2099961897,2099961898,2099961899,2099961900,2099961901,2099961902,2099961903,2099961904,2099961905,2099961906,2099961907,2099961908,2099961909,2099961910,2099961911,2099961912,2099961913,2099961914,2099961915,2099961916,2099961917,2099961918,2099961919,2099961920,2099961921,2099961922,2099961923,2099961924,2099961925,2099961926,2099961927,2099961928,2099961929,2099961930,2099961931,2099961932,2099961933,2099961934,2099961935,2099961936,2099961937,2099961938,2099961939,2099961940,2099961941,2099961942,2099961943,2099961944,2099961945,2099961946,2099961947,2099961948,2099961949,2099961950,2099961951,2099961952,2099961953,2099961954,2099961955,2099961956,2099961957,2099961958,2099961959,2099961960,2099961961,2099961962,2099961963,2099961964,2099961965,2099961966,2099961967,2099961968,2099961969,2099961970,2099961971,2099961972,2099961973,2099961974,2099961975,2099961976,2099961977,2099961978,2099961979,2099961980) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2099961860,2099961861,2099961862,2099961863,2099961864,2099961865,2099961866,2099961867,2099961868,2099961869,2099961870,2099961871,2099961872,2099961873,2099961874,2099961875,2099961876,2099961877,2099961878,2099961879,2099961880,2099961881,2099961882,2099961883,2099961884,2099961885,2099961886,2099961887,2099961888,2099961889,2099961890,2099961891,2099961892,2099961893,2099961894,2099961895,2099961896,2099961897,2099961898,2099961899,2099961900,2099961901,2099961902,2099961903,2099961904,2099961905,2099961906,2099961907,2099961908,2099961909,2099961910,2099961911,2099961912,2099961913,2099961914,2099961915,2099961916,2099961917,2099961918,2099961919,2099961920,2099961921,2099961922,2099961923,2099961924,2099961925,2099961926,2099961927,2099961928,2099961929,2099961930,2099961931,2099961932,2099961933,2099961934,2099961935,2099961936,2099961937,2099961938,2099961939,2099961940,2099961941,2099961942,2099961943,2099961944,2099961945,2099961946,2099961947,2099961948,2099961949,2099961950,2099961951,2099961952,2099961953,2099961954,2099961955,2099961956,2099961957,2099961958,2099961959,2099961960,2099961961,2099961962,2099961963,2099961964,2099961965,2099961966,2099961967,2099961968,2099961969,2099961970,2099961971,2099961972,2099961973,2099961974,2099961975,2099961976,2099961977,2099961978,2099961979,2099961980) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2099961860,2099961861,2099961862,2099961863,2099961864,2099961865,2099961866,2099961867,2099961868,2099961869,2099961870,2099961871,2099961872,2099961873,2099961874,2099961875,2099961876,2099961877,2099961878,2099961879,2099961880,2099961881,2099961882,2099961883,2099961884,2099961885,2099961886,2099961887,2099961888,2099961889,2099961890,2099961891,2099961892,2099961893,2099961894,2099961895,2099961896,2099961897,2099961898,2099961899,2099961900,2099961901,2099961902,2099961903,2099961904,2099961905,2099961906,2099961907,2099961908,2099961909,2099961910,2099961911,2099961912,2099961913,2099961914,2099961915,2099961916,2099961917,2099961918,2099961919,2099961920,2099961921,2099961922,2099961923,2099961924,2099961925,2099961926,2099961927,2099961928,2099961929,2099961930,2099961931,2099961932,2099961933,2099961934,2099961935,2099961936,2099961937,2099961938,2099961939,2099961940,2099961941,2099961942,2099961943,2099961944,2099961945,2099961946,2099961947,2099961948,2099961949,2099961950,2099961951,2099961952,2099961953,2099961954,2099961955,2099961956,2099961957,2099961958,2099961959,2099961960,2099961961,2099961962,2099961963,2099961964,2099961965,2099961966,2099961967,2099961968,2099961969,2099961970,2099961971,2099961972,2099961973,2099961974,2099961975,2099961976,2099961977,2099961978,2099961979,2099961980) select photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type, id from MTRPhoto.photo_sub_photos where photo_id in ( 1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) begin to crop the class : teint_dans_la_masse param for this class : {'min_score': 0.7} filtre for class : teint_dans_la_masse hashtag_id of this class : 2107752385 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 2107752385) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961965] chi_id interessant : [2099961965, 2099961952] chi_id interessant : [2099961965, 2099961952, 2099961898] chi_id interessant : [2099961965, 2099961952, 2099961898, 2099961863] type of cropped photo chosen : rle_png_transparent we resize croppped photo by 1 on x axis and by 1 on y axis map_result returned by crop_photo_return_map_crop : length : 0 map_result after crop : {} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {} we have finished the crop for the class : teint_dans_la_masse begin to crop the class : autre_refus param for this class : {'min_score': 0.7} filtre for class : autre_refus hashtag_id of this class : 2107752406 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 2107752406) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961980] chi_id interessant : [2099961980, 2099961933] chi_id interessant : [2099961980, 2099961933, 2099961880] chi_id interessant : [2099961980, 2099961933, 2099961880, 2099961870] type of cropped photo chosen : rle_png_transparent we resize croppped photo by 1 on x axis and by 1 on y axis map_result returned by crop_photo_return_map_crop : length : 0 map_result after crop : {} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {} we have finished the crop for the class : autre_refus begin to crop the class : carton_gris param for this class : {'min_score': 0.7} filtre for class : carton_gris hashtag_id of this class : 2107753020 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 2107753020) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961976] chi_id interessant : [2099961976, 2099961975] chi_id interessant : [2099961976, 2099961975, 2099961971] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890, 2099961889] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890, 2099961889, 2099961882] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890, 2099961889, 2099961882, 2099961876] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890, 2099961889, 2099961882, 2099961876, 2099961867] chi_id interessant : [2099961976, 2099961975, 2099961971, 2099961964, 2099961960, 2099961950, 2099961949, 2099961937, 2099961934, 2099961915, 2099961913, 2099961912, 2099961910, 2099961908, 2099961906, 2099961903, 2099961890, 2099961889, 2099961882, 2099961876, 2099961867, 2099961862] type of cropped photo chosen : rle_png_transparent we resize croppped photo by 1 on x axis and by 1 on y axis map_result returned by crop_photo_return_map_crop : length : 0 map_result after crop : {} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {} we have finished the crop for the class : carton_gris begin to crop the class : cartonnette param for this class : {'min_score': 0.7} filtre for class : cartonnette hashtag_id of this class : 702398920 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 702398920) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961953] chi_id interessant : [2099961953, 2099961954] chi_id interessant : [2099961953, 2099961954, 2099961944] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945, 2099961922] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945, 2099961922, 2099961932] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945, 2099961922, 2099961932, 2099961892] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945, 2099961922, 2099961932, 2099961892, 2099961877] chi_id interessant : [2099961953, 2099961954, 2099961944, 2099961945, 2099961922, 2099961932, 2099961892, 2099961877, 2099961871] type of cropped photo chosen : rle_png_transparent we resize croppped photo by 1 on x axis and by 1 on y axis map_result returned by crop_photo_return_map_crop : length : 0 map_result after crop : {} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {} we have finished the crop for the class : cartonnette begin to crop the class : carton_brun param for this class : {'min_score': 0.7} filtre for class : carton_brun hashtag_id of this class : 2107753024 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 2107753024) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961974] chi_id interessant : [2099961974, 2099961969] chi_id interessant : [2099961974, 2099961969, 2099961979] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931, 2099961916] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931, 2099961916, 2099961900] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931, 2099961916, 2099961900, 2099961901] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931, 2099961916, 2099961900, 2099961901, 2099961902] chi_id interessant : [2099961974, 2099961969, 2099961979, 2099961957, 2099961963, 2099961955, 2099961942, 2099961931, 2099961916, 2099961900, 2099961901, 2099961902, 2099961872] type of cropped photo chosen : rle_png_transparent we resize croppped photo by 1 on x axis and by 1 on y axis map_result returned by crop_photo_return_map_crop : length : 0 map_result after crop : {} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {} we have finished the crop for the class : carton_brun begin to crop the class : plastique param for this class : {'min_score': 0.7} filtre for class : plastique hashtag_id of this class : 492725882 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 492725882) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2099961978] begin to crop the class : kraft param for this class : {'min_score': 0.7} filtre for class : kraft hashtag_id of this class : 493202403 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 493202403) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 3336 and photo_id in (1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and hashtag_id = 492628673) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; map of total cropped photos with some data : {} After datou_step_exec type output : time spend for datou_step_exec : 9.709021806716919 time spend to save output : 0.0005903244018554688 total time spend for step 1 : 9.709612131118774 step2:thcl Thu Sep 25 17:07:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {} VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! input_args_next_step, len :0 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Thcl ! no input After datou_step_exec type output : time spend for datou_step_exec : 0.0009715557098388672 time spend to save output : 2.8848648071289062e-05 total time spend for step 2 : 0.0010004043579101562 step3:argmax Thu Sep 25 17:07:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {} VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! input_args_next_step, len :0 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou_step Argmax ! no input After datou_step_exec type output : time spend for datou_step_exec : 8.249282836914062e-05 time spend to save output : 2.7894973754882812e-05 total time spend for step 3 : 0.00011038780212402344 step4:merge_mask_and_thcl Thu Sep 25 17:07:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {} VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! input_args_next_step, len :0 After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} debut de la step merge mask and classif [] crops sont a sauvegarder After datou_step_exec type output : time spend for datou_step_exec : 0.00010728836059570312 time spend to save output : 3.218650817871094e-05 total time spend for step 4 : 0.00013947486877441406 step5:rle_unique_nms_with_priority Thu Sep 25 17:07:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : ['temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg'] We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :14, first value : ['temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg'] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg on traite la photo : temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg on traite la photo : temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg on traite la photo : temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg on traite la photo : temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg on traite la photo : temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg on traite la photo : temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg on traite la photo : temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg on traite la photo : temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg on traite la photo : temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg on traite la photo : temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg on traite la photo : temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg on traite la photo : temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg on traite la photo : temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1008921601,1008921600,1008922095,1008922073,1008922072,1008922003,1008922002,1008921786,1008922130,1008922101,1008922097,1008921657,1008921656,1008921602) and `type` in (3418) and hashtag_id in (492668766,538914404) Loaded 26 chid ids of type : 3418 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2099963667,2099963668,2099963669,2099963670,2099963671,2099963672,2099963673,2099963674,2099963675,2099963676,2099963677,2099963678,2099963679,2099963680,2099963681,2099963682,2099963683,2099963684,2099963685,2099963686,2099963687,2099963688,2099963689,2099963690,2099963691,2099963692) ++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2099963667,2099963668,2099963669,2099963670,2099963671,2099963672,2099963673,2099963674,2099963675,2099963676,2099963677,2099963678,2099963679,2099963680,2099963681,2099963682,2099963683,2099963684,2099963685,2099963686,2099963687,2099963688,2099963689,2099963690,2099963691,2099963692) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2099963667,2099963668,2099963669,2099963670,2099963671,2099963672,2099963673,2099963674,2099963675,2099963676,2099963677,2099963678,2099963679,2099963680,2099963681,2099963682,2099963683,2099963684,2099963685,2099963686,2099963687,2099963688,2099963689,2099963690,2099963691,2099963692) nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.769134521484375 create new chi : 0.005942106246948242 proportion hashtag : refus 0.011822314499524865 proportion hashtag : papier 0.9824540455733292 time to delete rle : 0.41667771339416504 save time : 6.67572021484375e-06 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.862558126449585 create new chi : 0.006110429763793945 proportion hashtag : refus 0.01255295771301869 proportion hashtag : papier 0.9863322081881533 time to delete rle : 0.34644222259521484 save time : 4.5299530029296875e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.7108688354492188 create new chi : 0.006724357604980469 proportion hashtag : papier 0.9585115913050364 time to delete rle : 0.3203582763671875 save time : 3.814697265625e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.149885892868042 create new chi : 2.47955322265625e-05 proportion hashtag : refus 0.0034527686490338928 proportion hashtag : papier 0.9965472313509661 time to delete rle : 0.39644551277160645 save time : 4.291534423828125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.6274666786193848 create new chi : 2.8848648071289062e-05 proportion hashtag : refus 0.006595957396262274 proportion hashtag : papier 0.9934040426037377 time to delete rle : 0.3984510898590088 save time : 6.4373016357421875e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.9678149223327637 create new chi : 4.458427429199219e-05 proportion hashtag : refus 0.010260185698447893 proportion hashtag : papier 0.9897398143015521 time to delete rle : 0.33519577980041504 save time : 2.3603439331054688e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.785560131072998 create new chi : 0.006238460540771484 proportion hashtag : papier 0.98686463117675 time to delete rle : 0.30679845809936523 save time : 4.76837158203125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.2384517192840576 create new chi : 3.9577484130859375e-05 proportion hashtag : refus 0.0024127929996832437 proportion hashtag : papier 0.9975872070003168 time to delete rle : 0.38660573959350586 save time : 4.5299530029296875e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.1760175228118896 create new chi : 2.2411346435546875e-05 proportion hashtag : refus 0.009172696586949636 proportion hashtag : papier 0.9908273034130504 time to delete rle : 0.3129754066467285 save time : 7.867813110351562e-06 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.279994010925293 create new chi : 0.006239891052246094 proportion hashtag : papier 0.9896722560975609 proportion hashtag : refus 0.001785095620842572 time to delete rle : 0.39603543281555176 save time : 4.291534423828125e-06 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.3715214729309082 create new chi : 0.006247043609619141 proportion hashtag : papier 0.9968715354767184 proportion hashtag : refus 0.00213167168197656 time to delete rle : 0.415449857711792 save time : 3.5762786865234375e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.7710475921630859 create new chi : 0.0063495635986328125 proportion hashtag : papier 0.994315707158695 time to delete rle : 0.4829542636871338 save time : 4.291534423828125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.7302780151367188 create new chi : 3.504753112792969e-05 proportion hashtag : refus 0.0018834633354450428 proportion hashtag : papier 0.9981165366645549 time to delete rle : 0.39680027961730957 save time : 5.0067901611328125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.064723014831543 create new chi : 2.193450927734375e-05 proportion hashtag : refus 0.011059624445676274 proportion hashtag : papier 0.9889403755543237 time to delete rle : 0.41745877265930176 save time : 4.291534423828125e-06 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 23.806037664413452 time spend to save output : 0.00012612342834472656 total time spend for step 5 : 23.806163787841797 step6:ventilate_hashtags_in_portfolio Thu Sep 25 17:07:53 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step ventilate_hashtags_in_portfolio : To implement ! To do loadFromThcl(), then load ParamDescType : thcl2456 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (2456) thcls : [{'id': 2456, 'mtr_user_id': 31, 'name': 'learn_qualipapia_papier_refus_from_vlg_data_aug', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'papier,refus', 'svm_portfolios_learning': '3028087,3028251', 'photo_hashtag_type': 3049, 'photo_desc_type': 4999, 'type_classification': 'caffe', 'hashtag_id_list': '492668766,538914404'}] thcl {'id': 2456, 'mtr_user_id': 31, 'name': 'learn_qualipapia_papier_refus_from_vlg_data_aug', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'papier,refus', 'svm_portfolios_learning': '3028087,3028251', 'photo_hashtag_type': 3049, 'photo_desc_type': 4999, 'type_classification': 'caffe', 'hashtag_id_list': '492668766,538914404'} Update svm_hashtag_type_desc : 4999 Iterating over portfolio : 3364276 get user id for portfolio 3364276 get sub ptf for main ptf 3535038, type 3418 and hashtags ['papier', 'refus'] SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3535038 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','refus')) AND mptpi.`min_score`=0.7 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3535038 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','refus')) AND mptpi.`min_score`=0.7 To do returned map {'refus': {'main_port_id': 3535038, 'sub_port_id': 3535090, 'hashtag': 'refus', 'pht': 3418, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 8903, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2021, 3, 5, 16, 19, 20)}, 'papier': {'main_port_id': 3535038, 'sub_port_id': 3535091, 'hashtag': 'papier', 'pht': 3418, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 8904, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2021, 3, 5, 16, 19, 20)}} insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3535090 , sub_photo_id, 739,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3364276 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=3418 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='refus' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3535091 , sub_photo_id, 739,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3364276 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=3418 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='papier' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; To do ! Use context local managing function ! get sub ptf for main ptf 3364276, type 3418 and hashtags ['papier', 'refus'] SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3364276 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','refus')) AND mptpi.`min_score`=0.7 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3364276 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','refus')) AND mptpi.`min_score`=0.7 To do returned map {'refus': {'main_port_id': 3364276, 'sub_port_id': 3534897, 'hashtag': 'refus', 'pht': 3418, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 8901, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2021, 3, 5, 15, 22, 49)}, 'papier': {'main_port_id': 3364276, 'sub_port_id': 3534898, 'hashtag': 'papier', 'pht': 3418, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 8902, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2021, 3, 5, 15, 22, 49)}} insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3534897 , sub_photo_id, 739,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3364276 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=3418 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='refus' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 3534898 , sub_photo_id, 739,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=3364276 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=3418 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='papier' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; To do ! Use context local managing function ! After datou_step_exec type output : time spend for datou_step_exec : 0.1544046401977539 time spend to save output : 6.270408630371094e-05 total time spend for step 6 : 0.15446734428405762 step7:final Thu Sep 25 17:07:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} input_args_next_step : {1008921601: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921601 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921600 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922095 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922073 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922072 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922003 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922002 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921786 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922130 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: (0.005230650193135238,), 1008922101: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922101 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: (0.005230650193135238,), 1008922101: (0.005230650193135238,), 1008922097: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008922097 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: (0.005230650193135238,), 1008922101: (0.005230650193135238,), 1008922097: (0.005230650193135238,), 1008921657: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921657 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: (0.005230650193135238,), 1008922101: (0.005230650193135238,), 1008922097: (0.005230650193135238,), 1008921657: (0.005230650193135238,), 1008921656: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921656 depend.output_id : 0 input_args_next_step : {1008921601: (0.005230650193135238,), 1008921600: (0.005230650193135238,), 1008922095: (0.005230650193135238,), 1008922073: (0.005230650193135238,), 1008922072: (0.005230650193135238,), 1008922003: (0.005230650193135238,), 1008922002: (0.005230650193135238,), 1008921786: (0.005230650193135238,), 1008922130: (0.005230650193135238,), 1008922101: (0.005230650193135238,), 1008922097: (0.005230650193135238,), 1008921657: (0.005230650193135238,), 1008921656: (0.005230650193135238,), 1008921602: ()} output_args : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274)} args : 1008921602 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :14, first value : (0.005230650193135238,) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg': 1008921601, 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg': 1008921600, 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg': 1008922095, 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg': 1008922073, 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg': 1008922072, 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg': 1008922003, 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg': 1008922002, 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg': 1008921786, 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg': 1008922130, 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg': 1008922101, 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg': 1008922097, 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg': 1008921657, 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg': 1008921656, 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg': 1008921602} map_photo_id_path_extension : {1008921601: {'path': 'temp/1758812839_3157952_1008921601_8e77b77d2ac41a1e6ec6af186d0ee0e0.jpg', 'extension': 'jpg'}, 1008921600: {'path': 'temp/1758812839_3157952_1008921600_37a7af01ee43a568dfe3728dcdbe17a4.jpg', 'extension': 'jpg'}, 1008922095: {'path': 'temp/1758812839_3157952_1008922095_dc858351f179fe112b62a458b452c880.jpg', 'extension': 'jpg'}, 1008922073: {'path': 'temp/1758812839_3157952_1008922073_f4a476ca7bbbdbb6286b3964cb9dfa09.jpg', 'extension': 'jpg'}, 1008922072: {'path': 'temp/1758812839_3157952_1008922072_0b2e247d5ad70c283fb6fd8596c1a378.jpg', 'extension': 'jpg'}, 1008922003: {'path': 'temp/1758812839_3157952_1008922003_b378dd1de9a27a4b0a8bb35c5e0d5b99.jpg', 'extension': 'jpg'}, 1008922002: {'path': 'temp/1758812839_3157952_1008922002_4e629eb338e1fe79a3726963bf6d47dd.jpg', 'extension': 'jpg'}, 1008921786: {'path': 'temp/1758812839_3157952_1008921786_066e79494b5536cc7d2f3293519cd617.jpg', 'extension': 'jpg'}, 1008922130: {'path': 'temp/1758812839_3157952_1008922130_4c0c64c8974710b1875fb84156e8457c.jpg', 'extension': 'jpg'}, 1008922101: {'path': 'temp/1758812839_3157952_1008922101_1a025189b8603388d54304e6754e9df9.jpg', 'extension': 'jpg'}, 1008922097: {'path': 'temp/1758812839_3157952_1008922097_6c2f48fc82a23eb61afdc5b17b032e88.jpg', 'extension': 'jpg'}, 1008921657: {'path': 'temp/1758812839_3157952_1008921657_46fce4176daed1c358e2a7c299fc5587.jpg', 'extension': 'jpg'}, 1008921656: {'path': 'temp/1758812839_3157952_1008921656_c93a3fc2cd8645066f3120d727a4ce22.jpg', 'extension': 'jpg'}, 1008921602: {'path': 'temp/1758812839_3157952_1008921602_383b6a7758931a2dff9de560df82456c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step final ! query to retrieve results for portfolio 3364276 : SELECT photo_id, hashtag_id, ratio from MTRPhoto.photo_carac_ratio where hashtag_type = 3418 and photo_id in (1008921602,1008921601,1008921600,1008921657,1008921656,1008921786,1008922003,1008922002,1008922073,1008922072,1008922097,1008922095,1008922101,1008922130); insert ignore into MTRUser.portfolio_carac_ratio (portfolio_id, hashtag_type, hashtag_id, value) values (%s,%s,%s,%s) on DUPLICATE KEY UPDATE value=VALUES(value) After datou_step_exec type output : time spend for datou_step_exec : 0.019081830978393555 time spend to save output : 5.53131103515625e-05 total time spend for step 7 : 0.019137144088745117 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True original output for save of step final : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',)} new output for save of step final : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',)} [1008921601, 1008921600, 1008922095, 1008922073, 1008922072, 1008922003, 1008922002, 1008921786, 1008922130, 1008922101, 1008922097, 1008921657, 1008921656, 1008921602] map_info['map_portfolio_photo'] : {3364276: [1008922130, 1008922101, 1008922097, 1008922095, 1008922073, 1008922072, 1008922003, 1008922002, 1008921786, 1008921657, 1008921656, 1008921602, 1008921601, 1008921600]} final : True mtd_id 3164 list_pids : [1008921601, 1008921600, 1008922095, 1008922073, 1008922072, 1008922003, 1008922002, 1008921786, 1008922130, 1008922101, 1008922097, 1008921657, 1008921656, 1008921602] Looping around the photos to save general results len do output : 14 /1008921601.Didn't retrieve data . /1008921600.Didn't retrieve data . /1008922095.Didn't retrieve data . /1008922073.Didn't retrieve data . /1008922072.Didn't retrieve data . /1008922003.Didn't retrieve data . /1008922002.Didn't retrieve data . /1008921786.Didn't retrieve data . /1008922130.Didn't retrieve data . /1008922101.Didn't retrieve data . /1008922097.Didn't retrieve data . /1008921657.Didn't retrieve data . /1008921656.Didn't retrieve data . /1008921602.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921601', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921600', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922095', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922073', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922072', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922003', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922002', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921786', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922130', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922101', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922097', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921657', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921656', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921602', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 42 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3164', '3364276', '1008921601', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008921600', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922095', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922073', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922072', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922003', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922002', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008921786', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922130', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922101', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008922097', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008921657', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008921656', '0.005252307643909098', None, None, None, None, None), ('3164', '3364276', '1008921602', '0.005252307643909098', None, None, None, None, None)] time used for this insertion : 0.014133691787719727 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 7 output : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',)} {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',)} ############################### TEST ventilate_hashtags_in_portfolio ################################ DELETE FROM MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 5486631; Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3070 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3070 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3070 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3070 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : ventilate_hashtags_in_portfolio list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5363525) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5363525) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1075306598, 'portfolio_id': 5363525}, {'photo_id': 1075306564, 'portfolio_id': 5363525}, {'photo_id': 1075306534, 'portfolio_id': 5363525}, {'photo_id': 1075306522, 'portfolio_id': 5363525}, {'photo_id': 1075304668, 'portfolio_id': 5363525}] map_portfolio_id_photo_id: {5363525: [1075306598, 1075306564, 1075306534, 1075306522, 1075304668]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.014490604400634766 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:ventilate_hashtags_in_portfolio Thu Sep 25 17:07:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 5363525 get user id for portfolio 5363525 get sub ptf for main ptf 5363525, type 4268 and hashtags ['pet_clair', 'error', 'environment'] SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=5363525 AND mptpi.`type`=4268 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','error','environment')) AND mptpi.`min_score`=0.3 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=5363525 AND mptpi.`type`=4268 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','error','environment')) AND mptpi.`min_score`=0.3 To do returned map {'pet_clair': {'main_port_id': 5363525, 'sub_port_id': 5486630, 'hashtag': 'pet_clair', 'pht': 4268, 'min_score': 0.3, 'mtr_user_id': 31, 'id': 1060439, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2022, 2, 16, 13, 28, 54)}, 'error': {'main_port_id': 5363525, 'sub_port_id': 5486631, 'hashtag': 'error', 'pht': 4268, 'min_score': 0.3, 'mtr_user_id': 31, 'id': 1060440, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2022, 2, 16, 13, 28, 54)}, 'environment': {'main_port_id': 5363525, 'sub_port_id': 5486632, 'hashtag': 'environment', 'pht': 4268, 'min_score': 0.3, 'mtr_user_id': 31, 'id': 1060441, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 44, 47), 'last_updated_at_asc': datetime.datetime(2022, 2, 16, 13, 28, 54)}} insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 5486630 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=5363525 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.3 AND chi.type=4268 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='pet_clair' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 5486631 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=5363525 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.3 AND chi.type=4268 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='error' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 5486632 , sub_photo_id, 31,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=5363525 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.3 AND chi.type=4268 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='environment' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; To do ! Use context local managing function ! After datou_step_exec type output : time spend for datou_step_exec : 0.06572723388671875 time spend to save output : 6.0558319091796875e-05 total time spend for step 1 : 0.06578779220581055 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1075306598, 1075306564, 1075306534, 1075306522, 1075304668] map_info['map_portfolio_photo'] : {5363525: [1075306598, 1075306564, 1075306534, 1075306522, 1075304668]} final : True mtd_id 3070 list_pids : [1075306598, 1075306564, 1075306534, 1075306522, 1075304668] Looping around the photos to save general results len do output : 1 /5363525. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306598', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306564', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306534', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306522', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075304668', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3070', None, '5363525', "{'pet_clair': 5486630, 'error': 5486631, 'environment': 5486632}", None, None, None, None, None), ('3070', '5363525', '1075306598', None, None, None, None, None, None), ('3070', '5363525', '1075306564', None, None, None, None, None, None), ('3070', '5363525', '1075306534', None, None, None, None, None, None), ('3070', '5363525', '1075306522', None, None, None, None, None, None), ('3070', '5363525', '1075304668', None, None, None, None, None, None)] time used for this insertion : 0.013761758804321289 save_final save missing photos in datou_result : After save, about to update current ! SELECT count(*) from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id = 5486631 and hide_status = 0 Ayatollah of tests excluded it ! (Bon le prochain developpeur qui passe ici peut enlever ayatollah VR 11-2-21) name : merge_qualipapia_like not run because too long ############################### TEST poly_ro_rle ################################ test creation de rle a partir de polygon Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3138 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3138 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3138 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3138 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : poly_to_rle list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3337029) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (3337029) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1003369118, 'portfolio_id': 3337029}] map_portfolio_id_photo_id: {3337029: [1003369118]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1003369118 download finish for photo 1003369118 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.20807266235351562 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:poly_to_rle Thu Sep 25 17:07:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812874_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg': 1003369118} map_photo_id_path_extension : {1003369118: {'path': 'temp/1758812874_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} can't find the hashtag_type_input ,set the output_type same as the input_type on traite la photo : temp/1758812874_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1003369118) and `type` in (3391) Loaded 16 chid ids of type : 3391 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) ++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) time for calcul the mask position with numpy : 0.008109569549560547 nb_pixel_total : 110633 time to create 1 rle with old method : 0.11944961547851562 time for calcul the mask position with numpy : 0.0073397159576416016 nb_pixel_total : 15826 time to create 1 rle with old method : 0.01705193519592285 time for calcul the mask position with numpy : 0.0069768428802490234 nb_pixel_total : 5286 time to create 1 rle with old method : 0.00675201416015625 time for calcul the mask position with numpy : 0.006861448287963867 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0019567012786865234 time for calcul the mask position with numpy : 0.007202863693237305 nb_pixel_total : 105533 time to create 1 rle with old method : 0.11679816246032715 time for calcul the mask position with numpy : 0.007268428802490234 nb_pixel_total : 4393 time to create 1 rle with old method : 0.005057096481323242 time for calcul the mask position with numpy : 0.006879329681396484 nb_pixel_total : 632 time to create 1 rle with old method : 0.000850677490234375 time for calcul the mask position with numpy : 0.007391452789306641 nb_pixel_total : 62627 time to create 1 rle with old method : 0.06815481185913086 time for calcul the mask position with numpy : 0.007188558578491211 nb_pixel_total : 33681 time to create 1 rle with old method : 0.03550529479980469 time for calcul the mask position with numpy : 0.0070648193359375 nb_pixel_total : 37724 time to create 1 rle with old method : 0.04042625427246094 time for calcul the mask position with numpy : 0.0072443485260009766 nb_pixel_total : 48775 time to create 1 rle with old method : 0.05297541618347168 time for calcul the mask position with numpy : 0.022533416748046875 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.2834460735321045 time for calcul the mask position with numpy : 0.007004976272583008 nb_pixel_total : 2310 time to create 1 rle with old method : 0.0026702880859375 time for calcul the mask position with numpy : 0.006937742233276367 nb_pixel_total : 2256 time to create 1 rle with old method : 0.0028982162475585938 time for calcul the mask position with numpy : 0.0068073272705078125 nb_pixel_total : 3112 time to create 1 rle with old method : 0.0036165714263916016 time for calcul the mask position with numpy : 0.0067670345306396484 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0019905567169189453 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 16 chid ids of type : 3391 ++++++++++++++++Number RLEs to save : 0 INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 1.148963451385498 time spend to save output : 9.179115295410156e-05 total time spend for step 1 : 1.1490552425384521 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1003369118: 'temp/1758812874_3157952_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg'} batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1003369118) and `type` in (3391) Loaded 16 chid ids of type : 3391 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) ++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (1967620930,1967620931,1967620932,1967620933,1967620934,1967620935,1967620936,1967620937,1967620938,1967620939,1967620940,1967620941,1967620942,1967620943,1967620944,1967620945) fin du test de poly_to_rle ############################### TEST cod_sts ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3781 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3781 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3781 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3781 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : split_time_score list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4453840) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4453840) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1050302186, 'portfolio_id': 4453840}, {'photo_id': 1050302153, 'portfolio_id': 4453840}, {'photo_id': 1050302152, 'portfolio_id': 4453840}, {'photo_id': 1050302146, 'portfolio_id': 4453840}, {'photo_id': 1050302113, 'portfolio_id': 4453840}, {'photo_id': 1050302110, 'portfolio_id': 4453840}, {'photo_id': 1050302106, 'portfolio_id': 4453840}] map_portfolio_id_photo_id: {4453840: [1050302186, 1050302153, 1050302152, 1050302146, 1050302113, 1050302110, 1050302106]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.01416468620300293 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Thu Sep 25 17:07:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} SELECT app_name, token FROM MTRUser.mtr_app_api_token WHERE mtr_user_id=739 AND app_name="token_split_time_score" AND expire_at > NOW() TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] select SUBSTRING(ph.text,16,2) as h, count(*) from MTRUser.mtr_portfolio_photos mpp inner join MTRBack.view_photos_with_urls_250912 ph on mpp.mtr_photo_id = ph.photo_id where mpp.mtr_portfolio_id = 4453840 group by h (('48', 4), ('42', 3)) SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4453840 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4453840) AND cps.thcl in (861) order by cps.score desc LIMIT 0, 100000 SELECT cps.photo_id, cps.score, h.hashtag, cps.hashtag_id, mpp1.mtr_portfolio_id FROM MTRPhoto.class_photo_score cps, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp1 where mpp1.mtr_photo_id=cps.photo_id AND h.hashtag_id=cps.hashtag_id AND mpp1.hide_status=0 AND mpp1.mtr_portfolio_id in (4453840) AND cps.thcl in (758) order by cps.score desc LIMIT 0, 100000 ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 17082021 4453840 Nombre de photos uploadées : 7 / 23040 (0%) 17082021 4453840 Nombre de photos taguées (types de déchets): 0 / 7 (0%) 17082021 4453840 Nombre de photos taguées (volume) : 0 / 7 (0%) [{'photo_id': 1050302113, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/9/13/8b089b6e181d22a2bb6883e02fd3a110.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20210817_104213.jpg'}, {'photo_id': 1050302153, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/9/13/fd7af64d2c8fdd6083cf479b54278cc7.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20210817_104213.jpg'}, {'photo_id': 1050302186, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/9/13/c60917e9be6d6a9f1fa465e963bfa064.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20210817_104216.jpg'}, {'photo_id': 1050302110, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2021/9/13/314ca6fa7e24f250d19c3f32c9493132.jpg', 'username': None, 'uploaded_at': None, 'text': 'IMG_20210817_094832.jpg'}] 0 [] elapsed_time : load_data_split_time_score 4.5299530029296875e-06 elapsed_time : order_list_meta_photo_and_scores 7.62939453125e-06 ??????? elapsed_time : fill_and_build_computed_from_old_data 0.0004508495330810547 INSERT INTO `MTRPhoto`.`dashboard_entry_day` (`dashboard_place_id`, `mtr_portfolio_id`, `date`) VALUES ( 34, 4453840, '2021-08-17' ) ON DUPLICATE KEY UPDATE mtr_portfolio_id=VALUES(mtr_portfolio_id), updated_at=NOW(); Catched exception ! Connect or reconnect ! SELECT id FROM MTRPhoto.dashboard_entry_day where dashboard_place_id = 34 and date = '2021-08-17' ; INSERT INTO `MTRPhoto`.`dashboard_run_ids` (`dashboard_entry_day`, `mtr_user_id`, `misc_info`) VALUES (173725,739,"{}"); Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.22438979148864746 TODO 20-09-21 https://github.com/fotonower/raspi-fotonower-x/issues/253#issuecomment-923099773 TODO 20-9-21 TODO 20-9-21 ***** BEGIN SPLIT TIME ***** ```````list printed: [[0, 1, 2, 3], [4, 5, 6]] forced_hashtag: jrm force hashtag to jrm elapsed_time : SPLIT_TIME 0.005869865417480469 ***** END SPLIT TIME ***** NUMBER BATCH : 2 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['jrm'] Listed one port to create portfolio : jrm_diff_batch__17082021_09_48_08_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__17082021_09_48_08_000000 : 0 duration : 24.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '17082021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 24.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20210817_094808.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Listed one port to create portfolio : jrm_diff_batch__17082021_10_42_13_000000 ERROR missing amount info ERROR missing amount info ERROR missing amount info Nombres de balles jrm_diff_batch__17082021_10_42_13_000000 : 0 duration : 3.0 update_text_in_photos list_photo_id_text len : 0 , 100 first caracter of query INSERT IGNORE INTO MTRUser.mtr_photos (`photo_id`, `text`) VALUES ( %s, %s) on duplicate key update None result_one_balle_Type_jrm:{'day': '17082021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 3.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20210817_104213.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 2 list_same_port_ids : [4453926] find same portfolio which already exist 4453926 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4453926 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4453926 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 list_same_port_ids : [4652336] find same portfolio which already exist 4652336 , we will use it INSERT ignore into MTRUser.mtr_portfolio_photos (`mtr_portfolio_id`, `mtr_photo_id`, `order`) SELECT 4652336 , ph.photo_id,50000000*CAST(SUBSTRING(ph.text, 13, 2) as unsigned integer) + 4000000*CAST(SUBSTRING(ph.text, 9, 2) as unsigned integer) + 100000*CAST(SUBSTRING(ph.text, 7, 2) as unsigned integer) + 60*60*CAST(SUBSTRING(ph.text, 16, 2) as unsigned integer) + 60*CAST(SUBSTRING(ph.text, 19, 2) as unsigned integer)+ CAST(SUBSTRING(ph.text, 22, 2) as unsigned integer) FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4652336 AND mpp.hide_status=0 on duplicate key update `order`=VALUES(`order`); 0 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4453926 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4453926 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4453926 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4453926 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358489, '_______jrm', '2021-08-17 09:48:08', '2021-08-17 09:48:32', 4, 4453926, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'url_report': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Qualipapia_P4453926_21-11-2024_01_57_11.pdf', 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 18491127, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 18491128, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 18491129, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 18491130, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 18491131, 'pht': 4038}, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 18491132, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 18491133, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 18491134, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 18491135, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 18491136, 'pht': 4038}}" ); SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4652336 AND result is not null and result<>"None" and result<>0.0 AND mtd_id=3543 ORDER BY id desc LIMIT 1 SELECT mtd_id, mtr_current_id, mtr_portfolio_id, created_at, result, result_long, result_double FROM MTRPhoto.mtr_datou_result WHERE mtr_portfolio_id = 4652336 AND result is not null and result<>"None" and result=0.0 AND mtd_id=3543 ORDER BY created_at desc LIMIT 1 list_result_datou : [] select url from MTRUser.mtr_files where mtd_id = 3543 and mtr_portfolio_id = 4652336 order by file_id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4652336 AND mptpi.`type`=4038 To do INSERT INTO `MTRPhoto`.`dashboard_results` (`dashboard_run_id`, `hashtag`, `date_debut`, `date_fin`, `nombre_balle`, `mtr_portfolio_id`, `qualite`, `datou_result_id_qualite`, `completion_percentage`, `completion_json`) VALUES (2358489, '_______jrm', '2021-08-17 10:42:13', '2021-08-17 10:42:16', 3, 4652336, -1, -1, '-1', "{'max_time_prod_two_photos': 0, 'autre_refus': {'hashtag': 'autre_refus', 'sub_port_id': 18491234, 'pht': 4038}, 'Carton_gris': {'hashtag': 'Carton_gris', 'sub_port_id': 18491235, 'pht': 4038}, 'cartonnette': {'hashtag': 'cartonnette', 'sub_port_id': 18491236, 'pht': 4038}, 'Carton_brun': {'hashtag': 'Carton_brun', 'sub_port_id': 18491237, 'pht': 4038}, 'plastique': {'hashtag': 'plastique', 'sub_port_id': 18491238, 'pht': 4038}, 'papier': {'hashtag': 'papier', 'sub_port_id': 18491239, 'pht': 4038}, 'Teint_Dans_La_Masse': {'hashtag': 'Teint_Dans_La_Masse', 'sub_port_id': 18491240, 'pht': 4038}, 'metal': {'hashtag': 'metal', 'sub_port_id': 18491241, 'pht': 4038}, 'environnement': {'hashtag': 'environnement', 'sub_port_id': 18491242, 'pht': 4038}, 'kraft': {'hashtag': 'kraft', 'sub_port_id': 18491243, 'pht': 4038}}" ); elapsed_time : count_nb_balles_and_create_portfolio 1.3603498935699463 # DISPLAY ALL COLLECTED DATA : {'17082021': {'nb_upload': 7, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} After datou_step_exec type output : time spend for datou_step_exec : 1.6355648040771484 time spend to save output : 4.0531158447265625e-05 total time spend for step 1 : 1.6356053352355957 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1050302186, 1050302153, 1050302152, 1050302146, 1050302113, 1050302110, 1050302106] map_info['map_portfolio_photo'] : {4453840: [1050302186, 1050302153, 1050302152, 1050302146, 1050302113, 1050302110, 1050302106]} final : True mtd_id 3781 list_pids : [1050302186, 1050302153, 1050302152, 1050302146, 1050302113, 1050302110, 1050302106] Looping around the photos to save general results len do output : 1 /4453840Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302186', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302153', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302152', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302146', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302113', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302110', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302106', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3781', None, '4453840', 'None', None, None, None, None, None), ('3781', '4453840', '1050302186', None, None, None, None, None, None), ('3781', '4453840', '1050302153', None, None, None, None, None, None), ('3781', '4453840', '1050302152', None, None, None, None, None, None), ('3781', '4453840', '1050302146', None, None, None, None, None, None), ('3781', '4453840', '1050302113', None, None, None, None, None, None), ('3781', '4453840', '1050302110', None, None, None, None, None, None), ('3781', '4453840', '1050302106', None, None, None, None, None, None)] time used for this insertion : 0.012918233871459961 save_final save missing photos in datou_result : After save, about to update current ! Result test cod : {4453840: ([[0, 1, 2, 3], [4, 5, 6]], {'Rungis_jrm': [(0, 1), (1, 2)]}, {4453926: {'list_of_photos': [1050302106, 1050302146, 1050302110, 1050302152], 'hashtag': 'jrm'}, 4652336: {'list_of_photos': [1050302113, 1050302153, 1050302186], 'hashtag': 'jrm'}}, {2107757407: 7}, {'amount_uploaded_and_tagged': {'17082021': {'nb_upload': 7, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2)]}})}| ############################### TEST cod_download ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data [] ["[Errno 13] Permission denied: '/data/data_root'\n", "[Errno 13] Permission denied: '/data/data_root'\n"] ############################### TEST sendgrid ################################ test sendgrid senders@fotonower.com no problem of authentification, for test if the email can be received, try with a real receiver fin du test de sendgrid ############################### TEST rym_consolidate ################################ test_rym_consolidate DELETE FROM MTRUser.portfolio_carac_ratio WHERE portfolio_id = 4709558 AND hashtag_type = 4016 Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3818 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3818 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3818 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3818 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 9321 copy_chis is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 9357 consolidate_hashtags_from_manual_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 9318 rle_unique_nms_with_priority is not consistent : 3 used against 1 in the step definition ! WARNING : number of outputs for step 9318 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 9410 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 9319 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 9328 blur_detection have less inputs used (0) than in the step definition (1) : maybe we manage optionnal inputs ! Step 9327 brightness have less inputs used (0) than in the step definition (1) : maybe we manage optionnal inputs ! Step 9326 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 9321 have datatype=11 whereas input 0 of step 9318 have datatype=2 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 9357 doesn't seem to be define in the database( WARNING : type of input 1 of step 9318 doesn't seem to be define in the database( WARNING : type of output 1 of step 9357 doesn't seem to be define in the database( WARNING : type of input 3 of step 9319 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 9410 doesn't seem to be define in the database( WARNING : output 1 of step 9318 have datatype=7 whereas input 1 of step 9410 have datatype=None WARNING : type of output 1 of step 9410 doesn't seem to be define in the database( WARNING : type of input 4 of step 9319 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 9410 have datatype=10 whereas input 3 of step 9326 have datatype=6 WARNING : type of output 1 of step 9321 doesn't seem to be define in the database( WARNING : type of input 1 of step 9357 doesn't seem to be define in the database( DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : copy_chis, consolidate_hashtags_from_manual_portfolio, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, send_mail_cod list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4709558) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4709558) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1057289546, 'portfolio_id': 4709558}, {'photo_id': 1057289467, 'portfolio_id': 4709558}] map_portfolio_id_photo_id: {4709558: [1057289546, 1057289467]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1057289546 begin to download photo : 1057289467 download finish for photo 1057289546 download finish for photo 1057289467 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 ##### After load_data_input time to download the photos : 0.20428013801574707 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 8 step1:copy_chis Thu Sep 25 17:08:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step datou_step_copy_crop processing picture : temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg processing picture : temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057289546,1057289467) and `type` in (3326) and score>0.7and hashtag_id in (2107755846,492622729) Loaded 0 chid ids of type : 0 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in () map_nb_chis : {} After datou_step_exec type output : time spend for datou_step_exec : 0.004649162292480469 time spend to save output : 4.00543212890625e-05 total time spend for step 1 : 0.004689216613769531 step2:consolidate_hashtags_from_manual_portfolio Thu Sep 25 17:08:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step consolidate_hashtags_from_manual_portfolio Iterating over portfolio : 4709558 on est dans le IF portfolio mere 26T SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4683188 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673496 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673496, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673496; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673496 and b.mtr_portfolio_id = 4673496; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673496, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673496; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673496 and b.mtr_portfolio_id = 4673496; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673497 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673497, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673497; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673497 and b.mtr_portfolio_id = 4673497; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673497, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673497; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673497 and b.mtr_portfolio_id = 4673497; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673498 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673498, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673498; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673498 and b.mtr_portfolio_id = 4673498; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673498, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673498; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673498 and b.mtr_portfolio_id = 4673498; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673500 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673500, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673500; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673500 and b.mtr_portfolio_id = 4673500; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673500, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673500; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673500 and b.mtr_portfolio_id = 4673500; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673501 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673501, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673501; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673501 and b.mtr_portfolio_id = 4673501; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673501, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673501; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673501 and b.mtr_portfolio_id = 4673501; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673502 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673502, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673502; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673502 and b.mtr_portfolio_id = 4673502; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673502, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673502; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673502 and b.mtr_portfolio_id = 4673502; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673503 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673503, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673503; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673503 and b.mtr_portfolio_id = 4673503; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673503, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673503; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673503 and b.mtr_portfolio_id = 4673503; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673504 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673504, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673504; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673504 and b.mtr_portfolio_id = 4673504; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673504, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673504; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673504 and b.mtr_portfolio_id = 4673504; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673505 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673505, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673505; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673505 and b.mtr_portfolio_id = 4673505; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673505, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673505; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673505 and b.mtr_portfolio_id = 4673505; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673506 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673506, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673506; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673506 and b.mtr_portfolio_id = 4673506; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673506, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673506; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673506 and b.mtr_portfolio_id = 4673506; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673507 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673507, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673507; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673507 and b.mtr_portfolio_id = 4673507; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673507, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673507; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673507 and b.mtr_portfolio_id = 4673507; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673508 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673508, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673508; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673508 and b.mtr_portfolio_id = 4673508; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 4673508, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 4673508; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =4673508 and b.mtr_portfolio_id = 4673508; UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (572316,572317,572315,572314,572313,572312,572306,572311,572310,572309,572308,572307); UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (572316,572317,572315,572314,572313,572312,572306,572311,572310,572309,572308,572307); UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (561088,561089,561087,561086,561082,561081,561075,561084,561079,561078,561077,561076); To test ! Use context local managing function ! After datou_step_exec type output : time spend for datou_step_exec : 0.6454615592956543 time spend to save output : 3.8623809814453125e-05 total time spend for step 2 : 0.6455001831054688 step3:rle_unique_nms_with_priority Thu Sep 25 17:08:01 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : ['temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg'] We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : ['temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg'] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step rle-unique-nms on traite la photo : temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg on traite la photo : temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057289546,1057289467) and `type` in (4016) and hashtag_id in (492622729,494826614,492668766,2107756122,492774966,493546845,2107755900,492628673,2107756859,628944319,492645504,492636447,2107755846,2107755527,493012381) Loaded 65 chid ids of type : 4016 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2211485914,2211485915,2211485916,2211485917,2211485918,2211485919,2211485920,2211485921,2211485922,2211485923,2211485924,2211485925,2211485926,2211485927,2211485928,2211485929,2211485930,2211485931,2211485932,2211485933,2211485934,2211485935,2211485936,2211485937,2211485938,2211485939,2211485940,2211485941,2211485942,2211485943,2211485944,2211486029,2211486030,2211486031,2211486032,2211486033,2211486034,2211486035,2211486036,2211486037,2211486038,2211486039,2211486040,2211486041,2211486042,2211486043,2211486044,2211486045,2211486046,2211486047,2211486048,2211486049,2211486050,2211486051,2211486052,2211486053,2211486054,2211486055,2211486056,2211486057,2211486058,2241206166,2241206167,2241206168,2241206169) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2211485914,2211485915,2211485916,2211485917,2211485918,2211485919,2211485920,2211485921,2211485922,2211485923,2211485924,2211485925,2211485926,2211485927,2211485928,2211485929,2211485930,2211485931,2211485932,2211485933,2211485934,2211485935,2211485936,2211485937,2211485938,2211485939,2211485940,2211485941,2211485942,2211485943,2211485944,2211486029,2211486030,2211486031,2211486032,2211486033,2211486034,2211486035,2211486036,2211486037,2211486038,2211486039,2211486040,2211486041,2211486042,2211486043,2211486044,2211486045,2211486046,2211486047,2211486048,2211486049,2211486050,2211486051,2211486052,2211486053,2211486054,2211486055,2211486056,2211486057,2211486058,2241206166,2241206167,2241206168,2241206169) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2211485914,2211485915,2211485916,2211485917,2211485918,2211485919,2211485920,2211485921,2211485922,2211485923,2211485924,2211485925,2211485926,2211485927,2211485928,2211485929,2211485930,2211485931,2211485932,2211485933,2211485934,2211485935,2211485936,2211485937,2211485938,2211485939,2211485940,2211485941,2211485942,2211485943,2211485944,2211486029,2211486030,2211486031,2211486032,2211486033,2211486034,2211486035,2211486036,2211486037,2211486038,2211486039,2211486040,2211486041,2211486042,2211486043,2211486044,2211486045,2211486046,2211486047,2211486048,2211486049,2211486050,2211486051,2211486052,2211486053,2211486054,2211486055,2211486056,2211486057,2211486058,2241206166,2241206167,2241206168,2241206169) nb_obj : 0 nb_hashtags : 3 time to prepare the origin masks : 10.168904304504395 create new chi : 3.457069396972656e-05 proportion hashtag : pet_clair 0.5358597032000172 proportion hashtag : environment 0.16202715754672498 proportion hashtag : etiquette 0.004007054290980795 time to delete rle : 0.2797417640686035 save time : 6.4373016357421875e-06 nb_obj : 0 nb_hashtags : 3 time to prepare the origin masks : 9.114228248596191 create new chi : 5.364418029785156e-05 proportion hashtag : environment 0.29592690382801784 proportion hashtag : pet_clair 0.39099757399905694 proportion hashtag : etiquette 0.0016148780435528121 time to delete rle : 0.132798433303833 save time : 3.0517578125e-05 INSERT IGNORE INTO MTRPhoto.photo_carac_ratio (`photo_id`, `hashtag_type`, `hashtag_id`, `ratio`) VALUES (%s, %s, %s, %s) on duplicate key update `ratio` = VALUES(`ratio`) map_output_result : {1057289546: (0.0, 'Should be the crop_list due to order', 0.0), 1057289467: (0.0, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms After datou_step_exec type output : time spend for datou_step_exec : 19.991475582122803 time spend to save output : 0.00019121170043945312 total time spend for step 3 : 19.991666793823242 step4:ventilate_hashtags_in_portfolio Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 4709558 get user id for portfolio 4709558 get sub ptf for main ptf 4709558, type 4016 and hashtags ['environnement', 'mal_croppe', 'pet_clair', 'etiquette', 'bouchon', 'pehd', 'barquette_avec_film', 'metal', 'pet_fonce', 'aluminium', 'carton', 'film_plastique', 'papier', 'autre'] SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','mal_croppe','pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) AND mptpi.`min_score`=0.7 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','mal_croppe','pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) AND mptpi.`min_score`=0.7 To do returned map {'mal_croppe': {'main_port_id': 4709558, 'sub_port_id': 4673494, 'hashtag': 'mal_croppe', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572305, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2021, 10, 28, 16, 30, 19)}, 'papier': {'main_port_id': 4709558, 'sub_port_id': 4673496, 'hashtag': 'papier', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572316, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'autre': {'main_port_id': 4709558, 'sub_port_id': 4673497, 'hashtag': 'autre', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572317, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'film_plastique': {'main_port_id': 4709558, 'sub_port_id': 4673498, 'hashtag': 'film_plastique', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572315, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'carton': {'main_port_id': 4709558, 'sub_port_id': 4673500, 'hashtag': 'carton', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572314, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'aluminium': {'main_port_id': 4709558, 'sub_port_id': 4673501, 'hashtag': 'aluminium', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572313, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'pet_fonce': {'main_port_id': 4709558, 'sub_port_id': 4673502, 'hashtag': 'pet_fonce', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572312, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'pet_clair': {'main_port_id': 4709558, 'sub_port_id': 4673503, 'hashtag': 'pet_clair', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572306, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'metal': {'main_port_id': 4709558, 'sub_port_id': 4673504, 'hashtag': 'metal', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572311, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'barquette_avec_film': {'main_port_id': 4709558, 'sub_port_id': 4673505, 'hashtag': 'barquette_avec_film', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572310, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'pehd': {'main_port_id': 4709558, 'sub_port_id': 4673506, 'hashtag': 'pehd', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572309, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'bouchon': {'main_port_id': 4709558, 'sub_port_id': 4673507, 'hashtag': 'bouchon', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572308, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'etiquette': {'main_port_id': 4709558, 'sub_port_id': 4673508, 'hashtag': 'etiquette', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 0, 'id': 572307, 'last_updated_at': datetime.datetime(2025, 9, 25, 17, 8, 1), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2025, 9, 25, 17, 8, 1)}, 'environnement': {'main_port_id': 4709558, 'sub_port_id': 4709559, 'hashtag': 'environnement', 'pht': 4016, 'min_score': 0.7, 'mtr_user_id': 970, 'id': 572318, 'last_updated_at': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_desc': datetime.datetime(2025, 9, 25, 16, 45, 14), 'last_updated_at_asc': datetime.datetime(2021, 10, 28, 16, 34, 8)}} insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673494 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='mal_croppe' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673496 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='papier' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673497 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='autre' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673498 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='film_plastique' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673500 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='carton' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673501 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='aluminium' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673502 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='pet_fonce' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673503 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='pet_clair' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673504 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='metal' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673505 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='barquette_avec_film' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673506 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='pehd' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673507 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='bouchon' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4673508 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='etiquette' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id,created_at) SELECT 4709559 , sub_photo_id, 970,now() FROM (SELECT csp.sub_photo_id, csp.crop_hashtag_id, csp.created_at FROM MTRPhoto.crop_sub_photo_ids csp, MTRPhoto.crop_hashtag_ids chi, MTRBack.hashtags h, MTRUser.mtr_portfolio_photos mpp WHERE mpp.mtr_portfolio_id=4709558 AND mpp.mtr_photo_id=chi.photo_id AND chi.id=csp.crop_hashtag_id AND chi.score>0.7 AND chi.type=4016 AND chi.hashtag_id=h.hashtag_id AND h.hashtag='environnement' GROUP BY csp.crop_hashtag_id, csp.created_at order by csp.created_at desc) as a group by crop_hashtag_id; To do ! Use context local managing function ! After datou_step_exec type output : time spend for datou_step_exec : 0.18677973747253418 time spend to save output : 6.723403930664062e-05 total time spend for step 4 : 0.18684697151184082 step5:final Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 : {1057289546: (0.0, 'Should be the crop_list due to order', 0.0), 1057289467: (0.0, 'Should be the crop_list due to order', 0.0)} input_args_next_step : {1057289546: ()} output_args : {1057289546: (0.0, 'Should be the crop_list due to order', 0.0), 1057289467: (0.0, 'Should be the crop_list due to order', 0.0)} args : 1057289546 depend.output_id : 0 input_args_next_step : {1057289546: (0.0,), 1057289467: ()} output_args : {1057289546: (0.0, 'Should be the crop_list due to order', 0.0), 1057289467: (0.0, 'Should be the crop_list due to order', 0.0)} args : 1057289467 depend.output_id : 0 VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :2, first value : (0.0,) After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step final ! query to retrieve results for portfolio 4709558 : SELECT photo_id, hashtag_id, ratio from MTRPhoto.photo_carac_ratio where hashtag_type = 4016 and photo_id in (1057289467,1057289546); insert ignore into MTRUser.portfolio_carac_ratio (portfolio_id, hashtag_type, hashtag_id, value) values (%s,%s,%s,%s) on DUPLICATE KEY UPDATE value=VALUES(value) After datou_step_exec type output : time spend for datou_step_exec : 0.029050588607788086 time spend to save output : 4.506111145019531e-05 total time spend for step 5 : 0.02909564971923828 step6:blur_detection Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} inside step blur_detection toutes les photos sont déjà traitées, on saute les calculs score_blur_detection : {1057289546: [(1057289546, -4.333383571220791, 492609224)], 1057289467: [(1057289467, -4.424440243329978, 492609224)]} After datou_step_exec type output : time spend for datou_step_exec : 0.00430750846862793 time spend to save output : 4.2438507080078125e-05 total time spend for step 6 : 0.004349946975708008 step7:brightness Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} inside step calcul brightness toutes les photos sont déjà traitées, on saute les calculs brightness_score : {1057289467: [(1057289467, -0.4062218880770088, 496442774)], 1057289546: [(1057289546, -0.5998675991292823, 501862349)]} After datou_step_exec type output : imagette46734941758812901/ imagette46734961758812901/ imagette46734971758812901/ imagette46734981758812901/ imagette46735001758812901/ imagette46735011758812901/ imagette46735021758812901/ time spend for datou_step_exec : 0.00494694709777832 time spend to save output : 2.4557113647460938e-05 total time spend for step 7 : 0.004971504211425781 step8:send_mail_cod Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 : {1057289546: [(1057289546, -4.333383571220791, 492609224)], 1057289467: [(1057289467, -4.424440243329978, 492609224)]} input_args_next_step : {1057289546: ()} output_args : {1057289546: [(1057289546, -4.333383571220791, 492609224)], 1057289467: [(1057289467, -4.424440243329978, 492609224)]} args : 1057289546 depend.output_id : 0 input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224),), 1057289467: ()} output_args : {1057289546: [(1057289546, -4.333383571220791, 492609224)], 1057289467: [(1057289467, -4.424440243329978, 492609224)]} args : 1057289467 depend.output_id : 0 complete output_args for input 1 : {1057289467: [(1057289467, -0.4062218880770088, 496442774)], 1057289546: [(1057289546, -0.5998675991292823, 501862349)]} input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224),), 1057289467: ((1057289467, -4.424440243329978, 492609224),)} output_args : {1057289467: [(1057289467, -0.4062218880770088, 496442774)], 1057289546: [(1057289546, -0.5998675991292823, 501862349)]} args : 1057289467 depend.output_id : 0 input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224),), 1057289467: ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774))} output_args : {1057289467: [(1057289467, -0.4062218880770088, 496442774)], 1057289546: [(1057289546, -0.5998675991292823, 501862349)]} args : 1057289546 depend.output_id : 0 complete output_args for input 2 : {1057289546: ('0.009511382621534484',), 1057289467: ('0.009511382621534484',)} input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349)), 1057289467: ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774))} output_args : {1057289546: ('0.009511382621534484',), 1057289467: ('0.009511382621534484',)} args : 1057289546 depend.output_id : 0 input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484'), 1057289467: ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774))} output_args : {1057289546: ('0.009511382621534484',), 1057289467: ('0.009511382621534484',)} args : 1057289467 depend.output_id : 0 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 : {4709558: [{'mal_croppe': 4673494, 'papier': 4673496, 'autre': 4673497, 'film_plastique': 4673498, 'carton': 4673500, 'aluminium': 4673501, 'pet_fonce': 4673502, 'pet_clair': 4673503, 'metal': 4673504, 'barquette_avec_film': 4673505, 'pehd': 4673506, 'bouchon': 4673507, 'etiquette': 4673508, 'environnement': 4709559}]} input_args_next_step : {1057289546: ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484'), 1057289467: ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774), '0.009511382621534484'), 4709558: ()} output_args : {4709558: [{'mal_croppe': 4673494, 'papier': 4673496, 'autre': 4673497, 'film_plastique': 4673498, 'carton': 4673500, 'aluminium': 4673501, 'pet_fonce': 4673502, 'pet_clair': 4673503, 'metal': 4673504, 'barquette_avec_film': 4673505, 'pehd': 4673506, 'bouchon': 4673507, 'etiquette': 4673508, 'environnement': 4709559}]} args : 4709558 depend.output_id : 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :3, first value : ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484') After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg': 1057289546, 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg': 1057289467} map_photo_id_path_extension : {1057289546: {'path': 'temp/1758812880_3157952_1057289546_da9d43be274d4fe0bc4d06d071dbd3bd.jpg', 'extension': 'jpg'}, 1057289467: {'path': 'temp/1758812880_3157952_1057289467_5eaa0f3f506e9775c4ed0da9d66dfffc.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} dans la step send mail cod work_area: /home/admin/temp in order to get the selector url, please entre the license of selector results_COD_P4709558_25-09-2025_17_08_21.pdf 4673494 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673494 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46734941758812901 4673496 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673496 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46734961758812901 4673497 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673497 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46734971758812901 4673498 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673498 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46734981758812901 4673500 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673500 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735001758812901 4673501 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673501 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735011758812901 4673502 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673502 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735021758812901 4673503 imagette46735031758812901/ imagette46735041758812901/ imagette46735051758812901/ imagette46735061758812901/ imagette46735071758812901/ imagette46735081758812901/ SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673503 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735031758812901 4673504 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673504 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735041758812901 4673505 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673505 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735051758812901 4673506 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673506 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735061758812901 4673507 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673507 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735071758812901 4673508 SELECT ph.photo_id,ph.url,ph.username,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673508 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 20 map_photo_id_text : {} imagette46735081758812901 velour_link : ce batch n'est pas dans un dashboard, on n'envoi pas de mail. si vous voulez quand même des mail , veuillez configurer no_mail = 2 args[1057289546] : ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484') We are sending mail with results at marine@fotonower.com args[1057289467] : ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774), '0.009511382621534484') We are sending mail with results at marine@fotonower.com refus_total : 0.009511382621534484 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4709558 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 error for generate pdf : 'NoneType' object has no attribute 'startswith' After datou_step_exec type output : time spend for datou_step_exec : 0.2953658103942871 time spend to save output : 4.100799560546875e-05 total time spend for step 8 : 0.2954068183898926 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 8 output : SELECT value FROM MTRUser.portfolio_carac_ratio WHERE portfolio_id = 4709558 AND hashtag_type = 4016 ORDER BY hashtag_id; fin du test de rym_consolidate ############################### TEST generate_new_image_add_crop ################################ test_generate_new_image_add_crop DELETE FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id = 4789106 DELETE FROM MTRPhoto.crop_hashtag_ids WHERE type = 4086 Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3870 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3870 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3870 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3870 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : generate_new_image list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4789595) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4789595) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1057314774, 'portfolio_id': 4789595}, {'photo_id': 1057314768, 'portfolio_id': 4789595}, {'photo_id': 1057314766, 'portfolio_id': 4789595}] map_portfolio_id_photo_id: {4789595: [1057314774, 1057314768, 1057314766]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1057314774 begin to download photo : 1057314768 begin to download photo : 1057314766 download finish for photo 1057314766 download finish for photo 1057314774 download finish for photo 1057314768 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 ##### After load_data_input time to download the photos : 0.2306666374206543 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:generate_new_image Thu Sep 25 17:08:21 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812901_3157952_1057314766_850e771a4800ad0a89e4fec977bcfedd_29707587.jpg': 1057314766, 'temp/1758812901_3157952_1057314774_6bab7ce0e063fda7d35a74c0adf7f25b_17612544.jpg': 1057314774, 'temp/1758812901_3157952_1057314768_3b6c8b2738f519f078355064487ef55f_72134828.jpg': 1057314768} map_photo_id_path_extension : {1057314766: {'path': 'temp/1758812901_3157952_1057314766_850e771a4800ad0a89e4fec977bcfedd_29707587.jpg', 'extension': 'jpg'}, 1057314774: {'path': 'temp/1758812901_3157952_1057314774_6bab7ce0e063fda7d35a74c0adf7f25b_17612544.jpg', 'extension': 'jpg'}, 1057314768: {'path': 'temp/1758812901_3157952_1057314768_3b6c8b2738f519f078355064487ef55f_72134828.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4789595 ORDER BY ph.size desc select id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057314774,1057314766,1057314768) and `type` in (4021) SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4789595) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 1000000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (4789595) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 1000000 list_result: [{'photo_id': 1057314774, 'portfolio_id': 4789595}, {'photo_id': 1057314768, 'portfolio_id': 4789595}, {'photo_id': 1057314766, 'portfolio_id': 4789595}] map_portfolio_id_photo_id: {4789595: [1057314774, 1057314768, 1057314766]} we need 3 photos there is already 3 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 3 photo needed from our local_cache list of photo_id_missing : [] batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where id in (2208326711,2208326718) Loaded 2 chid ids of type : 4021 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2208326711,2208326718) ++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2208326711,2208326718) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2208326711,2208326718) SELECT photo_id, url FROM MTRBack.view_photos_with_urls_250912 ph WHERE photo_id IN (1057314766,1057314768) Found this number of photos: 2 we need 2 photos there is already 2 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 2 photo needed from our local_cache list of photo_id_missing : [] begin to treate photo :1057314774 add chi : 2208326711 , rotate : 87 (672, 672) (169, 642, 0, 205) (205, 473, 3) (205, 473) (672, 672, 3) time for calcul the mask position with numpy : 0.001425027847290039 nb_pixel_total : 65389 time to create 1 rle with old method : 0.07067441940307617 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057314774) and `type` in (4021) Loaded 0 chid ids of type : 0 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in () time for calcul the mask position with numpy : 0.0017743110656738281 nb_pixel_total : 65389 time to create 1 rle with old method : 0.06937432289123535 begin to treate photo :1057314768 add chi : 2208326718 , rotate : 31 (878, 878) (12, 315, 554, 735) (181, 303, 3) (181, 303) (878, 878, 3) time for calcul the mask position with numpy : 0.0011031627655029297 nb_pixel_total : 8859 time to create 1 rle with old method : 0.010777473449707031 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057314768) and `type` in (4021) Loaded 2 chid ids of type : 4021 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2208326718,2208326717) ++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2208326718,2208326717) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2208326718,2208326717) time for calcul the mask position with numpy : 0.0024182796478271484 nb_pixel_total : 80840 time to create 1 rle with old method : 0.08341145515441895 time for calcul the mask position with numpy : 0.001241922378540039 nb_pixel_total : 8859 time to create 1 rle with old method : 0.009311914443969727 time for calcul the mask position with numpy : 0.0011622905731201172 nb_pixel_total : 8755 time to create 1 rle with old method : 0.008911848068237305 begin to treate photo :1057314766 add chi : 2208326711 , rotate : 140 (901, 901) (529, 899, 145, 615) (470, 370, 3) (470, 370) (901, 901, 3) time for calcul the mask position with numpy : 0.0014100074768066406 nb_pixel_total : 65375 time to create 1 rle with old method : 0.07177019119262695 batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1057314766) and `type` in (4021) Loaded 3 chid ids of type : 4021 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2208326711,2208326712,2208326713) +++SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2208326711,2208326712,2208326713) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2208326711,2208326712,2208326713) time for calcul the mask position with numpy : 0.001857757568359375 nb_pixel_total : 62136 time to create 1 rle with old method : 0.06992506980895996 time for calcul the mask position with numpy : 0.0015034675598144531 nb_pixel_total : 65375 time to create 1 rle with old method : 0.0724344253540039 time for calcul the mask position with numpy : 0.001917123794555664 nb_pixel_total : 68219 time to create 1 rle with old method : 0.07604551315307617 time for calcul the mask position with numpy : 0.0012760162353515625 nb_pixel_total : 2012 time to create 1 rle with old method : 0.002366781234741211 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812903_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 1 photos in the portfolio 4789106 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 1 chid ids of type : 4086 Number RLEs to save : 235 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975222021', '619', '61', '12') ... last line : ('3975222021', '630', '265', '7') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812904_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 1 photos in the portfolio 4789106 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 3 chid ids of type : 4086 Number RLEs to save : 626 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975222022', '380', '0', '156') ... last line : ('3975222024', '13', '639', '352') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1758812904_3157952 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 1 photos in the portfolio 4789106 insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 4 chid ids of type : 4086 Number RLEs to save : 1613 INSERT IGNORE INTO MTRPhoto.crop_segments (`crop_hashtag_id`, `x0`, `y0`, `length`) VALUES (%s, %s, %s , %s) first line : ('3975222034', '0', '4', '1') ... last line : ('3975222037', '429', '242', '1') INSERT IGNORE INTO MTRPhoto.crop_sum_segments (`crop_hashtag_id`, `sum_segments`) VALUES (%s, %s) TO DO : save crop sub photo not yet done ! After datou_step_exec type output : time spend for datou_step_exec : 3.1922152042388916 time spend to save output : 3.719329833984375e-05 total time spend for step 1 : 3.1922523975372314 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None SELECT * FROM MTRPhoto.crop_hashtag_ids where photo_id in (SELECT mtr_photo_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id = 4789106) and type = 4086 fin du test de generate_new_image ############################### TEST velours_tree ################################ test velours_tree - Retrieving photos to tag... query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4837217 ORDER BY ph.size desc - Loading descriptors... Size : 512 len(descriptors) : 5 Compute structured hierarchical clustering... ward : AgglomerativeClustering(n_clusters=5) ward.labels_ : [4 3 2 1 0] Elapsed time: 0.00804901123046875 graph_id used : 1145 - Beta version, working pretty good on 11-5-16 ! fin du test de velours_tree ############################### TEST step ACP ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4208 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4208 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4208 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4208 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : acp list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1069306967, 'portfolio_id': 5709050}, {'photo_id': 1069306964, 'portfolio_id': 5709050}, {'photo_id': 1069306954, 'portfolio_id': 5709050}, {'photo_id': 1069306844, 'portfolio_id': 5709050}, {'photo_id': 1069306843, 'portfolio_id': 5709050}, {'photo_id': 1069306841, 'portfolio_id': 5709050}, {'photo_id': 1069306815, 'portfolio_id': 5709050}, {'photo_id': 1069306805, 'portfolio_id': 5709050}, {'photo_id': 1069306710, 'portfolio_id': 5709050}, {'photo_id': 1069306708, 'portfolio_id': 5709050}] map_portfolio_id_photo_id: {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.014229774475097656 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:acp Thu Sep 25 17:08:25 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} Cette step permet de calculer une ACP. ATTENTION : le size etait trop grand : 20, on a changé sa valeur à : 9 SELECT id FROM MTRPhoto.photo_desc_type_params where name = 'ACP_from_type_5619_size_9'; find save_photo_desc_type : 5705 On sauvegarde les nouveaux descripteurs dans le photo desc type : 5705 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (5705) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5705, 'ACP_from_type_5619_size_9', 9, 9, 'ACP_from_type_5619_size_9', None, 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 16, 11, 6, 15), None) (10, 9) Got the blobs of the net to insert : [255, 0, 0, 0, 0, 8, 20, 3, 5] code_as_byte_string:b'c3bf000000'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 0, 34, 179] code_as_byte_string:b'0000000000'| Got the blobs of the net to insert : [0, 6, 0, 0, 0, 0, 0, 138, 0] code_as_byte_string:b'0006000000'| Got the blobs of the net to insert : [0, 108, 0, 0, 0, 196, 62, 0, 0] code_as_byte_string:b'006c000000'| Got the blobs of the net to insert : [0, 52, 0, 237, 64, 61, 115, 122, 0] code_as_byte_string:b'003400c3ad'| Got the blobs of the net to insert : [0, 0, 45, 0, 249, 0, 0, 0, 0] code_as_byte_string:b'00002d00c3'| Got the blobs of the net to insert : [0, 0, 0, 134, 0, 84, 0, 0, 0] code_as_byte_string:b'000000c286'| Got the blobs of the net to insert : [20, 131, 255, 31, 0, 0, 0, 0, 0] code_as_byte_string:b'14c283c3bf'| Got the blobs of the net to insert : [6, 255, 0, 88, 26, 0, 0, 0, 31] code_as_byte_string:b'06c3bf0058'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 171, 0, 0] code_as_byte_string:b'0000000000'| time to traite the descriptors : 0.0002989768981933594 Testing : ['1069306708', '1069306710', '1069306805', '1069306815', '1069306841', '1069306843', '1069306844', '1069306954', '1069306964', '1069306967'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (1069306708,1069306710,1069306805,1069306815,1069306841,1069306843,1069306844,1069306954,1069306964,1069306967) result : {1069306708: {'photo_id': 1069306708, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/7eba568f0aa961284ede154354a8b509.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_33_10134.jpg'}, 1069306710: {'photo_id': 1069306710, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/fe3d201fbfd00dfcd98aa3625d2cfe6a.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_43_10066.jpg'}, 1069306805: {'photo_id': 1069306805, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/42a49f97933b37a87ca53e38379f29b0.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_53_9809.jpg'}, 1069306815: {'photo_id': 1069306815, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/2f5091223d1b3946ee6eb8576faac354.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_03_10054.jpg'}, 1069306841: {'photo_id': 1069306841, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/547760f05364a61b63ad9db90d0b0dec.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_13_10036.jpg'}, 1069306843: {'photo_id': 1069306843, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/5d2b7a6367578e8ac1382d2a1a0bba36.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_23_10032.jpg'}, 1069306844: {'photo_id': 1069306844, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/5b215fd7500b354740ce88c56edeaf99.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_33_10008.jpg'}, 1069306954: {'photo_id': 1069306954, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/2019d5d809e04d2e01c269b108974cd3.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_03_9803.jpg'}, 1069306964: {'photo_id': 1069306964, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/d58c1cb31781763bc3bb045dfac967c3.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_13_10051.jpg'}, 1069306967: {'photo_id': 1069306967, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/642d8a900dd65f94ea75eb2a9d95b7dd.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_23_10019.jpg'}} list_photo_exists : [1069306708, 1069306710, 1069306805, 1069306815, 1069306841, 1069306843, 1069306844, 1069306954, 1069306964, 1069306967] storage_type for insertDescriptorsMulti : 3 Missing photo l117 : 1069306708 Missing photo l117 : 1069306710 Missing photo l117 : 1069306805 Missing photo l117 : 1069306815 Missing photo l117 : 1069306841 Missing photo l117 : 1069306843 Missing photo l117 : 1069306844 Missing photo l117 : 1069306954 Missing photo l117 : 1069306964 Missing photo l117 : 1069306967 To insert : 1069306708 To insert : 1069306710 To insert : 1069306805 To insert : 1069306815 To insert : 1069306841 To insert : 1069306843 To insert : 1069306844 To insert : 1069306954 To insert : 1069306964 To insert : 1069306967 time to insert the descriptors : 2.1993651390075684 res : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} After datou_step_exec type output : time spend for datou_step_exec : 3.1981945037841797 time spend to save output : 8.630752563476562e-05 total time spend for step 1 : 3.1982808113098145 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] map_info['map_portfolio_photo'] : {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} final : True mtd_id 4208 list_pids : [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results len do output : 10 /1069306708Didn't retrieve data . /1069306710Didn't retrieve data . /1069306805Didn't retrieve data . /1069306815Didn't retrieve data . /1069306841Didn't retrieve data . /1069306843Didn't retrieve data . /1069306844Didn't retrieve data . /1069306954Didn't retrieve data . /1069306964Didn't retrieve data . /1069306967Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306967', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306964', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306954', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306844', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306843', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306841', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306815', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306805', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306710', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306708', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 20 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4208', '5709050', '1069306708', 'None', None, None, None, None, None), ('4208', '5709050', '1069306710', 'None', None, None, None, None, None), ('4208', '5709050', '1069306805', 'None', None, None, None, None, None), ('4208', '5709050', '1069306815', 'None', None, None, None, None, None), ('4208', '5709050', '1069306841', 'None', None, None, None, None, None), ('4208', '5709050', '1069306843', 'None', None, None, None, None, None), ('4208', '5709050', '1069306844', 'None', None, None, None, None, None), ('4208', '5709050', '1069306954', 'None', None, None, None, None, None), ('4208', '5709050', '1069306964', 'None', None, None, None, None, None), ('4208', '5709050', '1069306967', 'None', None, None, None, None, None)] time used for this insertion : 0.013445615768432617 save_final save missing photos in datou_result : After save, about to update current ! ret : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4209 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4209 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4209 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4209 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : acp list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1069306967, 'portfolio_id': 5709050}, {'photo_id': 1069306964, 'portfolio_id': 5709050}, {'photo_id': 1069306954, 'portfolio_id': 5709050}, {'photo_id': 1069306844, 'portfolio_id': 5709050}, {'photo_id': 1069306843, 'portfolio_id': 5709050}, {'photo_id': 1069306841, 'portfolio_id': 5709050}, {'photo_id': 1069306815, 'portfolio_id': 5709050}, {'photo_id': 1069306805, 'portfolio_id': 5709050}, {'photo_id': 1069306710, 'portfolio_id': 5709050}, {'photo_id': 1069306708, 'portfolio_id': 5709050}] map_portfolio_id_photo_id: {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.014712810516357422 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:acp Thu Sep 25 17:08:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} Cette step permet de calculer une ACP. ATTENTION : le size etait trop grand : 20, on a changé sa valeur à : 9 Sauvegarde du modèle et envoi sur OVH Attention : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 existe, son contenu risque d'être écrasé model_param file didn't exist model didn't exist , save the new model in s3 local folder to save in s3 : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 update : 1758812911.4421103 done ! 1758812911.5983768 {'files': [{'name': 'pca_model.pkl', 'size': 103314, 'last_modified': '2025-09-25T15:08:31.461120', 'hash': 'd7e2c6aa9a1ef592ffdfc4abe9c66263'}], 'directories': []} Création d'un nouveau thème de classification Le thème de classification 'ACP_from_port_5709050_type_5619_size_9' existe déjà, merci de relancer avec un nouveau nom dans les params-json. After datou_step_exec type output : time spend for datou_step_exec : 2.413065195083618 time spend to save output : 5.555152893066406e-05 total time spend for step 1 : 2.413120746612549 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] map_info['map_portfolio_photo'] : {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} final : True mtd_id 4209 list_pids : [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results object of type 'int' has no len() begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4209', '5709050', '1069306967', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306964', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306954', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306844', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306843', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306841', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306815', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306805', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306710', '0', '0', '-1.0', '501120777', '1.0', None), ('4209', '5709050', '1069306708', '0', '0', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.015437126159667969 save_final save missing photos in datou_result : After save, about to update current ! Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4212 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4212 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4212 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4212 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : acp list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (5709050) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1069306967, 'portfolio_id': 5709050}, {'photo_id': 1069306964, 'portfolio_id': 5709050}, {'photo_id': 1069306954, 'portfolio_id': 5709050}, {'photo_id': 1069306844, 'portfolio_id': 5709050}, {'photo_id': 1069306843, 'portfolio_id': 5709050}, {'photo_id': 1069306841, 'portfolio_id': 5709050}, {'photo_id': 1069306815, 'portfolio_id': 5709050}, {'photo_id': 1069306805, 'portfolio_id': 5709050}, {'photo_id': 1069306710, 'portfolio_id': 5709050}, {'photo_id': 1069306708, 'portfolio_id': 5709050}] map_portfolio_id_photo_id: {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} ##### Call download_photos : nb_thread : 5 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos ##### After load_data_input time to download the photos : 0.014328718185424805 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:acp Thu Sep 25 17:08:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {} map_photo_id_path_extension : {} map_subphoto_mainphoto : {} Cette step permet de calculer une ACP. To do loadFromThcl(), then load ParamDescType : thcl3412 get_desc_type_from_thcl : type of cat SELECT id, mtr_user_id, name, pb_hashtag_id, hashtag_id_list, button_legend_list, portfolio_id_lists, photo_hashtag_type, photo_desc_type, svm_limit, limit_tagging, is_public, live, created_at, updated_at, type_classification FROM MTRDatou.classification_theme WHERE `id` IN (3412) thcls : [{'id': 3412, 'mtr_user_id': 31, 'name': 'ACP_from_port_5709050_type_5619_size_9', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '', 'svm_portfolios_learning': '0', 'photo_hashtag_type': 4398, 'photo_desc_type': 5706, 'type_classification': 'ACP', 'hashtag_id_list': '0'}] thcl {'id': 3412, 'mtr_user_id': 31, 'name': 'ACP_from_port_5709050_type_5619_size_9', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '', 'svm_portfolios_learning': '0', 'photo_hashtag_type': 4398, 'photo_desc_type': 5706, 'type_classification': 'ACP', 'hashtag_id_list': '0'} Update svm_hashtag_type_desc : 5706 SELECT * FROM MTRDatou.photo_desc_type_params WHERE id in (5706) FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5706, 'ACP_from_port_5709050_type_5619_size_9', 9, 9, 'ACP_from_port_5709050_type_5619_size_9', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 16, 11, 8, 14), datetime.datetime(2022, 6, 16, 11, 8, 14)) model_param file didn't exist model_name : ACP_from_port_5709050_type_5619_size_9 model_type : acp list file need : ['pca_model.pkl'] file exist in s3 : ['pca_model.pkl'] file manque in s3 : [] local folder : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 /data/models_weight/ACP_from_port_5709050_type_5619_size_9/pca_model.pkl size_local : 103314 size in s3 : 103314 create time local : 2025-09-25 17:08:30 create time in s3 : 2025-09-25 15:08:31 pca_model.pkl already exist and didn't need to update model_name : ACP_from_port_5709050_type_5619_size_9 On sauvegarde les nouveaux descripteurs dans le photo desc type : 5706 (10, 9) Got the blobs of the net to insert : [255, 0, 0, 0, 0, 8, 20, 3, 5] code_as_byte_string:b'c3bf000000'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 0, 34, 179] code_as_byte_string:b'0000000000'| Got the blobs of the net to insert : [0, 6, 0, 0, 0, 0, 0, 138, 0] code_as_byte_string:b'0006000000'| Got the blobs of the net to insert : [0, 108, 0, 0, 0, 196, 62, 0, 0] code_as_byte_string:b'006c000000'| Got the blobs of the net to insert : [0, 52, 0, 237, 64, 61, 115, 122, 0] code_as_byte_string:b'003400c3ad'| Got the blobs of the net to insert : [0, 0, 45, 0, 249, 0, 0, 0, 0] code_as_byte_string:b'00002d00c3'| Got the blobs of the net to insert : [0, 0, 0, 134, 0, 84, 0, 0, 0] code_as_byte_string:b'000000c286'| Got the blobs of the net to insert : [20, 131, 255, 31, 0, 0, 0, 0, 0] code_as_byte_string:b'14c283c3bf'| Got the blobs of the net to insert : [6, 255, 0, 88, 26, 0, 0, 0, 31] code_as_byte_string:b'06c3bf0058'| Got the blobs of the net to insert : [0, 0, 0, 0, 0, 0, 171, 0, 0] code_as_byte_string:b'0000000000'| time to traite the descriptors : 0.00039196014404296875 Testing : ['1069306708', '1069306710', '1069306805', '1069306815', '1069306841', '1069306843', '1069306844', '1069306954', '1069306964', '1069306967'] In select_photos_meta_from_ids: SELECT photo_id, url, FROM_UNIXTIME(uploaded_at), latitude, longitude, text FROM MTRBack.view_photos_with_urls_250912 WHERE photo_id IN (1069306708,1069306710,1069306805,1069306815,1069306841,1069306843,1069306844,1069306954,1069306964,1069306967) result : {1069306708: {'photo_id': 1069306708, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/7eba568f0aa961284ede154354a8b509.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_33_10134.jpg'}, 1069306710: {'photo_id': 1069306710, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/fe3d201fbfd00dfcd98aa3625d2cfe6a.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_43_10066.jpg'}, 1069306805: {'photo_id': 1069306805, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/42a49f97933b37a87ca53e38379f29b0.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_46_53_9809.jpg'}, 1069306815: {'photo_id': 1069306815, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/2f5091223d1b3946ee6eb8576faac354.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_03_10054.jpg'}, 1069306841: {'photo_id': 1069306841, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/547760f05364a61b63ad9db90d0b0dec.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_13_10036.jpg'}, 1069306843: {'photo_id': 1069306843, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/5d2b7a6367578e8ac1382d2a1a0bba36.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_23_10032.jpg'}, 1069306844: {'photo_id': 1069306844, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/5b215fd7500b354740ce88c56edeaf99.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_47_33_10008.jpg'}, 1069306954: {'photo_id': 1069306954, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/2019d5d809e04d2e01c269b108974cd3.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_03_9803.jpg'}, 1069306964: {'photo_id': 1069306964, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/d58c1cb31781763bc3bb045dfac967c3.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_13_10051.jpg'}, 1069306967: {'photo_id': 1069306967, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2022/1/4/642d8a900dd65f94ea75eb2a9d95b7dd.jpg', 'latitude': None, 'longitude': None, 'text': 'image_04012022_05_48_23_10019.jpg'}} list_photo_exists : [1069306708, 1069306710, 1069306805, 1069306815, 1069306841, 1069306843, 1069306844, 1069306954, 1069306964, 1069306967] storage_type for insertDescriptorsMulti : 3 Missing photo l117 : 1069306708 Missing photo l117 : 1069306710 Missing photo l117 : 1069306805 Missing photo l117 : 1069306815 Missing photo l117 : 1069306841 Missing photo l117 : 1069306843 Missing photo l117 : 1069306844 Missing photo l117 : 1069306954 Missing photo l117 : 1069306964 Missing photo l117 : 1069306967 To insert : 1069306708 To insert : 1069306710 To insert : 1069306805 To insert : 1069306815 To insert : 1069306841 To insert : 1069306843 To insert : 1069306844 To insert : 1069306954 To insert : 1069306964 To insert : 1069306967 time to insert the descriptors : 2.147989273071289 res : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} After datou_step_exec type output : time spend for datou_step_exec : 3.896695137023926 time spend to save output : 9.298324584960938e-05 total time spend for step 1 : 3.8967881202697754 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] map_info['map_portfolio_photo'] : {5709050: [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708]} final : True mtd_id 4212 list_pids : [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results len do output : 10 /1069306708Didn't retrieve data . /1069306710Didn't retrieve data . /1069306805Didn't retrieve data . /1069306815Didn't retrieve data . /1069306841Didn't retrieve data . /1069306843Didn't retrieve data . /1069306844Didn't retrieve data . /1069306954Didn't retrieve data . /1069306964Didn't retrieve data . /1069306967Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306967', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306964', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306954', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306844', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306843', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306841', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306815', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306805', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306710', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306708', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 20 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4212', '5709050', '1069306708', 'None', None, None, None, None, None), ('4212', '5709050', '1069306710', 'None', None, None, None, None, None), ('4212', '5709050', '1069306805', 'None', None, None, None, None, None), ('4212', '5709050', '1069306815', 'None', None, None, None, None, None), ('4212', '5709050', '1069306841', 'None', None, None, None, None, None), ('4212', '5709050', '1069306843', 'None', None, None, None, None, None), ('4212', '5709050', '1069306844', 'None', None, None, None, None, None), ('4212', '5709050', '1069306954', 'None', None, None, None, None, None), ('4212', '5709050', '1069306964', 'None', None, None, None, None, None), ('4212', '5709050', '1069306967', 'None', None, None, None, None, None)] time used for this insertion : 0.020249605178833008 save_final save missing photos in datou_result : After save, about to update current ! ret : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} fin du test de la step acp ############################### TEST blur_crop ################################ Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=3990 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=3990 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 3990 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=3990 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : crop_condition list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (6135916) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (6135916) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1105701516, 'portfolio_id': 6135916}, {'photo_id': 1105701500, 'portfolio_id': 6135916}] map_portfolio_id_photo_id: {6135916: [1105701516, 1105701500]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1105701516 begin to download photo : 1105701500 download finish for photo 1105701516 download finish for photo 1105701500 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 ##### After load_data_input time to download the photos : 0.1558694839477539 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:crop_condition Thu Sep 25 17:08:35 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058.jpg': 1105701516, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27.jpg': 1105701500} map_photo_id_path_extension : {1105701516: {'path': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058.jpg', 'extension': 'jpg'}, 1105701500: {'path': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} param_json : {'filter': {'Papier_Magazine': {}, 'carton_brun': {}, 'carton_gris': {}, 'cartonnette': {}, 'kraft': {}, 'autre_refus': {}, 'metal': {}, 'plastique': {}, 'teint_dans_la_masse': {}, 'environnement': {}, 'contaminant': {}}, 'upload_type': 'python', 'photo_hashtag_type': 4356, 'token': 'bdba771f7b99dd431d09e7a0ad6ec08f', 'portfolio_name': 'crop_qualipapia_rle', 'crop_type': 'blur', 'min_score': 0.5, 'feed_id_new_photos': 6163545} Loading chi in step crop with photo_hashtag_type : 4356 Loading chi in step crop for list_pids : 2 ! batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1105701516,1105701500) and `type` in (4356) Loaded 3 chid ids of type : 4356 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2436373819,2436374092,2436374262) ++WARNING : duplicated polygon, we should remove this data for chi_id : 2436373819. Ignored now +++WARNING : duplicated polygon, we should remove this data for chi_id : 2436374262. Ignored now SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2436373819,2436374092,2436374262) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2436373819,2436374092,2436374262) select photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type, id from MTRPhoto.photo_sub_photos where photo_id in ( 1105701516,1105701500) select sub_photo_id, crop_hashtag_id from MTRPhoto.crop_sub_photo_ids where sub_photo_id in (1105703688,1105703689,1105703686) begin to crop the class : Papier_Magazine param for this class : {} filtre for class : Papier_Magazine hashtag_id of this class : 2107752386 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 2107752386) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : carton_brun param for this class : {} filtre for class : carton_brun hashtag_id of this class : 2107753024 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 2107753024) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : carton_gris param for this class : {} filtre for class : carton_gris hashtag_id of this class : 2107753020 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 2107753020) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : cartonnette param for this class : {} filtre for class : cartonnette hashtag_id of this class : 702398920 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 702398920) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : kraft param for this class : {} filtre for class : kraft hashtag_id of this class : 493202403 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 493202403) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : autre_refus param for this class : {} filtre for class : autre_refus hashtag_id of this class : 2107752406 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 2107752406) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : metal param for this class : {} filtre for class : metal hashtag_id of this class : 492628673 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 492628673) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : plastique param for this class : {} filtre for class : plastique hashtag_id of this class : 492725882 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 492725882) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : teint_dans_la_masse param for this class : {} filtre for class : teint_dans_la_masse hashtag_id of this class : 2107752385 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 2107752385) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : environnement param for this class : {} filtre for class : environnement hashtag_id of this class : 493012381 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 493012381) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; begin to crop the class : contaminant param for this class : {} filtre for class : contaminant hashtag_id of this class : 681467679 select * from (select chi.id, chi.score,(chi.x1-chi.x0)*(chi.y1-chi.y0) as surface_rectangle, (chi.x1-chi.x0)/(chi.y1-chi.y0) as proportion_allonge, IFNULL(css.sum_segments, 0) as surface_crop, IFNULL(css.sum_segments, 0) / ((chi.x1-chi.x0)*(chi.y1-chi.y0)) as coverage from MTRPhoto.crop_hashtag_ids chi left join MTRPhoto.crop_sum_segments css on chi.id =css.crop_hashtag_id where type = 4356 and photo_id in (1105701516,1105701500) and hashtag_id = 681467679) as a where proportion_allonge >= 1/1000000 and proportion_allonge <= 1000000 and coverage >= 0 and surface_rectangle >= 0; chi_id interessant : [2436373819] chi_id interessant : [2436373819, 2436374092] chi_id interessant : [2436373819, 2436374092, 2436374262] type of cropped photo chosen : blur we resize croppped photo by 1 on x axis and by 1 on y axis new_file_path_bib_crop : temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_bib_crop_2436374092_0.jpg Here we manage polygons ! new_file_path_bib_crop : temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_bib_crop_2436373819_0.jpg Here we manage polygons ! new_file_path_bib_crop : temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_bib_crop_2436374262_0.jpg Here we manage polygons ! map_result returned by crop_photo_return_map_crop : length : 3 map_result after crop : {2436374092: {'crop': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_bib_crop_2436374092_0.jpg', 'photo_id': 1105701516, 'sub_photo_id': 1105703686, 'coordonates': (25, 175, 137, 235), 'sub_photo_infos': (25, 175, 137, 235, 1, 1), 'same_chi': True, 'black': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_black_2436374092_0.jpg', 'polygon': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_2436374092_0.jpg', 'polygon_crop': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_crop_2436374092_0.jpg', 'blur': 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg'}, 2436373819: {'crop': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_bib_crop_2436373819_0.jpg', 'photo_id': 1105701500, 'sub_photo_id': 1105703688, 'coordonates': (108, 300, 16, 138), 'sub_photo_infos': (108, 300, 16, 138, 1, 1), 'same_chi': True, 'black': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_black_2436373819_0.jpg', 'polygon': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_2436373819_0.jpg', 'polygon_crop': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_crop_2436373819_0.jpg', 'blur': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg'}, 2436374262: {'crop': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_bib_crop_2436374262_0.jpg', 'photo_id': 1105701500, 'sub_photo_id': 1105703689, 'coordonates': (47, 300, 91, 247), 'sub_photo_infos': (47, 300, 91, 247, 1, 1), 'same_chi': True, 'black': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_black_2436374262_0.jpg', 'polygon': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_2436374262_0.jpg', 'polygon_crop': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_crop_2436374262_0.jpg', 'blur': 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg'}} About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! map_result_insert : {} insert ignore into MTRPhoto.crop_sub_photo_ids (crop_hashtag_id, sub_photo_id, mtr_user_id) VALUES (%s,%s,%s) : [] insert ignore into MTRPhoto.photo_sub_photos (photo_id, sub_photo_id, x0, x1, y0, y1, resize_coeff_x, resize_coeff_y, crop_type) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s) : [] map of cropped photos with some data : {1105703686: [1105701516, 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} we have finished the crop for the class : contaminant map of total cropped photos with some data : {1105703686: [1105701516, 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} After datou_step_exec type output : time spend for datou_step_exec : 0.13808584213256836 time spend to save output : 6.079673767089844e-05 total time spend for step 1 : 0.13814663887023926 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : True saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1105701516, 1105701500] map_info['map_portfolio_photo'] : {6135916: [1105701516, 1105701500]} final : True mtd_id 3990 list_pids : [1105701516, 1105701500] Looping around the photos to save general results len do output : 3 /1105703686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1105703688Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1105703689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3990', None, None, None, None, None, None, None, None) ('3990', '6135916', '1105701516', None, None, None, None, None, None) ('3990', None, None, None, None, None, None, None, None) ('3990', '6135916', '1105701500', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('3990', None, '1105703686', 'None', None, None, None, None, None), ('3990', None, '1105703688', 'None', None, None, None, None, None), ('3990', None, '1105703689', 'None', None, None, None, None, None), ('3990', '6135916', '1105701516', None, None, None, None, None, None), ('3990', '6135916', '1105701500', None, None, None, None, None, None)] time used for this insertion : 0.015699148178100586 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1105703686: [1105701516, 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} ret : {1105703686: [1105701516, 'temp/1758812915_3157952_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1758812915_3157952_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} res wanted : {1105703686: [1105701516, 'temp/1653313707_21236_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1653313707_21236_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1653313707_21236_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} fin du test de la step crop option blur ############################### TEST pma_consolidate ################################ update MTRUser.mtr_portfolio_photos set hide_status=1 where mtr_portfolio_id in ( select mtr_portfolio_id_2 from MTRPhoto.mtr_port_to_port_ids where mtr_portfolio_id_1 = 9778120) Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4492 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4492 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4492 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4492 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 12666 copy_chis is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12667 consolidate_hashtags_from_manual_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 12664 rle_unique_nms_with_priority is not consistent : 3 used against 1 in the step definition ! WARNING : number of outputs for step 12664 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12671 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 12666 have datatype=11 whereas input 0 of step 12664 have datatype=2 WARNING : type of output 1 of step 12667 doesn't seem to be define in the database( WARNING : type of input 3 of step 12665 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 12667 doesn't seem to be define in the database( WARNING : type of input 1 of step 12664 doesn't seem to be define in the database( WARNING : type of input 1 of step 12671 doesn't seem to be define in the database( WARNING : output 1 of step 12664 have datatype=7 whereas input 1 of step 12671 have datatype=None WARNING : type of output 1 of step 12671 doesn't seem to be define in the database( WARNING : type of input 4 of step 12665 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 12666 doesn't seem to be define in the database( WARNING : type of input 1 of step 12667 doesn't seem to be define in the database( DataTypes for each output/input checked ! no param json to modify List Step Type Loaded in datou : copy_chis, consolidate_hashtags_from_manual_portfolio, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT ph.photo_id, ph.url FROM MTRBack.view_photos_with_urls_250912 ph WHERE ph.photo_id IN (SELECT mtr_photo_id from MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (6549724) and hide_status = 0 ) ORDER BY ph.photo_id DESC LIMIT 0, 10000 We have 1 , {} SELECT mtr_photo_id, mtr_portfolio_id FROM MTRUser.mtr_portfolio_photos WHERE mtr_portfolio_id in (6549724) AND hide_status = 0 ORDER by mtr_photo_id desc LIMIT 0, 10000 list_result: [{'photo_id': 1114046597, 'portfolio_id': 6549724}, {'photo_id': 1114046377, 'portfolio_id': 6549724}] map_portfolio_id_photo_id: {6549724: [1114046597, 1114046377]} ##### Call download_photos : nb_thread : 5 begin to download photo : 1114046597 begin to download photo : 1114046377 download finish for photo 1114046377 download finish for photo 1114046597 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 ##### After load_data_input time to download the photos : 0.24753141403198242 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 5 step1:copy_chis Thu Sep 25 17:08:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812915_3157952_1114046377_5a616bef1e05c703d5ceed86ed97d218.jpg': 1114046377, 'temp/1758812915_3157952_1114046597_e7ec945a635561c7bd8479a35c983a2c.jpg': 1114046597} map_photo_id_path_extension : {1114046377: {'path': 'temp/1758812915_3157952_1114046377_5a616bef1e05c703d5ceed86ed97d218.jpg', 'extension': 'jpg'}, 1114046597: {'path': 'temp/1758812915_3157952_1114046597_e7ec945a635561c7bd8479a35c983a2c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Begin step datou_step_copy_crop processing picture : temp/1758812915_3157952_1114046377_5a616bef1e05c703d5ceed86ed97d218.jpg processing picture : temp/1758812915_3157952_1114046597_e7ec945a635561c7bd8479a35c983a2c.jpg batch 1 select photo_id, hashtag_id, `type`, x0, x1, y0, y1, score, id from MTRPhoto.crop_hashtag_ids where photo_id in ( 1114046377,1114046597) and `type` in (4482) and score>0.01and hashtag_id in (493061979,493012381) Loaded 21 chid ids of type : 4482 SELECT crop_hashtag_id, points FROM MTRPhoto.crop_polygon_points WHERE crop_hashtag_id in (2805052771,2805052797,2805052780,2805052791,2805052814,2805052803,2805052772,2805052776,2805052811,2805052774,2805052812,2805052822,2805052723,2805052749,2805052752,2805052757,2805052743,2805052760,2805052740,2805052726,2805052770) SELECT * FROM MTRPhoto.crop_segments WHERE crop_hashtag_id in (2805052771,2805052797,2805052780,2805052791,2805052814,2805052803,2805052772,2805052776,2805052811,2805052774,2805052812,2805052822,2805052723,2805052749,2805052752,2805052757,2805052743,2805052760,2805052740,2805052726,2805052770) SELECT * FROM MTRPhoto.crop_sum_segments WHERE crop_hashtag_id in (2805052771,2805052797,2805052780,2805052791,2805052814,2805052803,2805052772,2805052776,2805052811,2805052774,2805052812,2805052822,2805052723,2805052749,2805052752,2805052757,2805052743,2805052760,2805052740,2805052726,2805052770) insert ignore into MTRPhoto.crop_hashtag_ids (photo_id, hashtag_id, `type`,x0,x1,y0,y1,score) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) batch 1 Loaded 88 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! map_nb_chis : {1114046377: 12, 1114046597: 9} After datou_step_exec type output : time spend for datou_step_exec : 0.04933953285217285 time spend to save output : 8.153915405273438e-05 total time spend for step 1 : 0.049421072006225586 step2:consolidate_hashtags_from_manual_portfolio Thu Sep 25 17:08:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure input_args_next_step, len :0, first value : [] After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1758812915_3157952_1114046377_5a616bef1e05c703d5ceed86ed97d218.jpg': 1114046377, 'temp/1758812915_3157952_1114046597_e7ec945a635561c7bd8479a35c983a2c.jpg': 1114046597} map_photo_id_path_extension : {1114046377: {'path': 'temp/1758812915_3157952_1114046377_5a616bef1e05c703d5ceed86ed97d218.jpg', 'extension': 'jpg'}, 1114046597: {'path': 'temp/1758812915_3157952_1114046597_e7ec945a635561c7bd8479a35c983a2c.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} beginning of datou step consolidate_hashtags_from_manual_portfolio Iterating over portfolio : 6549724 on est dans le IF portfolio mere 26T SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=9778120 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755323 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755346, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755323; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755346 and b.mtr_portfolio_id = 9755323; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092606, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755323; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092606 and b.mtr_portfolio_id = 9755323; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755324 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755347, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755324; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755347 and b.mtr_portfolio_id = 9755324; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092607, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755324; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092607 and b.mtr_portfolio_id = 9755324; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755325 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755348, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755325; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755348 and b.mtr_portfolio_id = 9755325; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092608, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755325; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092608 and b.mtr_portfolio_id = 9755325; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755326 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755349, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755326; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755349 and b.mtr_portfolio_id = 9755326; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092609, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755326; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092609 and b.mtr_portfolio_id = 9755326; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755327 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755350, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755327; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755350 and b.mtr_portfolio_id = 9755327; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092610, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755327; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092610 and b.mtr_portfolio_id = 9755327; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755328 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755351, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755328; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755351 and b.mtr_portfolio_id = 9755328; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092611, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755328; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092611 and b.mtr_portfolio_id = 9755328; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755329 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755352, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755329; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755352 and b.mtr_portfolio_id = 9755329; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092612, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755329; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092612 and b.mtr_portfolio_id = 9755329; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755330 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755353, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755330; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755353 and b.mtr_portfolio_id = 9755330; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092613, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755330; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092613 and b.mtr_portfolio_id = 9755330; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755331 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755354, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755331; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755354 and b.mtr_portfolio_id = 9755331; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092614, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755331; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092614 and b.mtr_portfolio_id = 9755331; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755332 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755355, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755332; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755355 and b.mtr_portfolio_id = 9755332; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092615, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755332; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092615 and b.mtr_portfolio_id = 9755332; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755333 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755356, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755333; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755356 and b.mtr_portfolio_id = 9755333; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092616, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755333; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092616 and b.mtr_portfolio_id = 9755333; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755334 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755357, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755334; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755357 and b.mtr_portfolio_id = 9755334; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092617, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755334; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092617 and b.mtr_portfolio_id = 9755334; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755335 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755358, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755335; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755358 and b.mtr_portfolio_id = 9755335; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092618, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755335; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092618 and b.mtr_portfolio_id = 9755335; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755336 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755359, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755336; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755359 and b.mtr_portfolio_id = 9755336; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092619, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755336; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092619 and b.mtr_portfolio_id = 9755336; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755337 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755360, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755337; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755360 and b.mtr_portfolio_id = 9755337; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092620, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755337; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092620 and b.mtr_portfolio_id = 9755337; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755338 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755361, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755338; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755361 and b.mtr_portfolio_id = 9755338; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092621, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755338; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092621 and b.mtr_portfolio_id = 9755338; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755339 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755362, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755339; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755362 and b.mtr_portfolio_id = 9755339; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092622, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755339; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092622 and b.mtr_portfolio_id = 9755339; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755340 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755363, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755340; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755363 and b.mtr_portfolio_id = 9755340; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092623, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755340; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092623 and b.mtr_portfolio_id = 9755340; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755341 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755364, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755341; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755364 and b.mtr_portfolio_id = 9755341; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092624, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755341; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092624 and b.mtr_portfolio_id = 9755341; TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.view_photos_with_urls_250912 ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755342 AND mpp.hide_status=0 ORDER BY ph.size desc insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 9755365, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755342; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =9755365 and b.mtr_portfolio_id = 9755342; insert ignore into MTRUser.mtr_portfolio_photos (mtr_portfolio_id, mtr_photo_id, mtr_user_id) select 10092625, mtr_photo_id, 0 from MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 9755342; update MTRUser.mtr_portfolio_photos as a inner join MTRUser.mtr_portfolio_photos as b on a.mtr_photo_id = b.mtr_photo_id set a.hide_status = b.hide_status where a.mtr_portfolio_id =10092625 and b.mtr_portfolio_id = 9755342; UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (4534333,4534334,4534335,4534336,4534337,4534338,4534339,4534340,4534341,4534342,4534343,4534344,4534345,4534346,4534347,4534348,4534349,4534350,4534351,4534352); UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (4534382,4534383,4534384,4534385,4534386,4534387,4534388,4534389,4534390,4534391,4534392,4534393,4534394,4534395,4534396,4534397,4534398,4534399,4534400,4534401); UPDATE MTRPhoto.mtr_port_to_port_ids set last_updated_at_asc=NOW(), updated_at=NOW() WHERE id in (4533644,4533645,4533646,4533647,4533648,4533649,4533650,4533651,4533652,4533653,4533654,4533655,4533656,4533657,4533658,4533659,4533660,4533661,4533662,4533663); To test ! Use context local managing function ! After datou_step_exec type output : Command terminated by signal 15 141.14user 75.48system 6:37.29elapsed 54%CPU (0avgtext+0avgdata 6261220maxresident)k 6734424inputs+894640outputs (11459major+8659031minor)pagefaults 0swaps