python /home/admin/mtr/script_for_cron.py -j default -m 20 -a 'python3 ~/workarea/git/Velours/python/prod/datou.py -j batch_current -C 2539880' -s traitement_sts -M 0 -S 0 -U 100,80,95 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/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', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 74146 load datou : 0 # 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 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou 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 ! Unexpected type for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? load thcls load pdts Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec no input labels no input values updating current state to 1 list_input_json: {} Current got : datou_id : 4887, datou_cur_ids : ['2539880'] with mtr_portfolio_ids : ['19845380'] and first list_photo_ids : [] new path : /proc/74146/ Inside batchDatouExec : verbose : 0 # 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 : split_time_score over limit max, limiting to limit_max 100 list_input_json : {} origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.020045757293701172 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Mon Feb 3 14:49:35 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 begin split time score 2022-04-13 10:29:59 0 TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 3890, 'mtr_user_id': 31, 'name': 'learn_MM_generique_10122024', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,emr,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '17736100,17736101,17736102,17736103,17736104,18770747,17736106,17736107,17736108,17736109,17736110,18876169', 'photo_hashtag_type': 4984, 'photo_desc_type': 6091, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,616987804,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'}] thcls : [{'id': 3513, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2_tf', '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': 4557, 'photo_desc_type': 5767, 'type_classification': 'tf_classification2', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('10', 6),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 6} 23012025 19845380 Nombre de photos uploadées : 6 / 23040 (0%) 23012025 19845380 Nombre de photos taguées (types de déchets): 6 / 6 (100%) 23012025 19845380 Nombre de photos taguées (volume) : 6 / 6 (100%) elapsed_time : load_data_split_time_score 2.6226043701171875e-06 elapsed_time : order_list_meta_photo_and_scores 1.33514404296875e-05 elapsed_time : fill_and_build_computed_from_old_data 0.0004665851593017578 elapsed_time : insert_dashboard_record_day_entry 0.02261185646057129 Creating list_photo_total elapsed_time : select_descriptors 0.009854316711425781 23012025 19845380 Nombre de photos avec descriptors (type 6091) : 0 / 3 (0%) Missing descriptors for photos 0 and 1330802451 0:00:00|ON:Missing descriptors for photos 1330802451 and 1330802447 Missing descriptors for photos 1330802447 and 1330802442 Missing descriptors for photos 1330802442 and 1330802438 Missing descriptors for photos 1330802438 and 1330802429 Missing descriptors for photos 1330802429 and 1330802416 23012025 Removing 0 photos because of the 'same image' condition Total on : 0 Total off : 0.0 list_time_off Warning in study_and_display_distrib_list : min=max : 0.0 0.0 dist_desc Warning in study_and_display_distrib_list : min=max : -1 -1 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 6 time used for this insertion : 0.012843847274780273 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.041236162185668945 Creating list_photo_total elapsed_time : count_sum_diff_and_build_graph 0.0005953311920166016 Total photos : 6 ....can't find max_score_info .can't find max_score_info .can't find max_score_info Total photos : 6 Number of lists : 1 counter photos in port : 3 hashtag : aluminium(493546845) : 0 photos in 0 portfolios ! hashtag : ela(492741797) : 0 photos in 0 portfolios ! hashtag : emr(616987804) : 0 photos in 0 portfolios ! hashtag : film_pedb(2107760237) : 0 photos in 0 portfolios ! hashtag : flux_dev(2107760238) : 0 photos in 0 portfolios ! hashtag : jrm(495916461) : 0 photos in 0 portfolios ! hashtag : pcm(560181804) : 0 photos in 0 portfolios ! hashtag : pcnc(1284539308) : 0 photos in 0 portfolios ! hashtag : pehd_pp(2107760239) : 0 photos in 0 portfolios ! hashtag : pet_clair(2107755846) : 3 photos in 1 portfolios ! hashtag : refus(538914404) : 0 photos in 0 portfolios ! hashtag : tapis_vide(2107748999) : 0 photos in 0 portfolios ! elapsed_time : group_photo_by_moyenne_exp 0.0004305839538574219 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 2.6226043701171875e-06 today str has not a value , we define it as the date of the first image todaystr_first : 23012025 attention , prev_timestamp is 0 , we do nothing Count Time bigger than 30s : 0 #Number Photos for regression : {'23012025': {493546845: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 492741797: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 616987804: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107760237: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107760238: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 495916461: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 560181804: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 1284539308: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107760239: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107755846: {2107751013: 0, 2107751014: 0, 2107751015: 11.999935150146484, 2107751016: 0, 2107751017: 0}, 538914404: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107748999: {2107751013: 0, 2107751014: 0, 2107751015: 16.998584985733032, 2107751016: 0, 2107751017: 0}}} 23012025|aluminium, 05102018_papier_non_papier_dense:0 23012025|aluminium, 05102018_papier_non_papier_peu_dense:0 23012025|aluminium, 05102018_papier_non_papier_presque_vide:0 23012025|aluminium, 05102018_papier_non_papier_tres_dense:0 23012025|aluminium, 05102018_papier_non_papier_tres_peu_dense:0 23012025|ela, 05102018_papier_non_papier_dense:0 23012025|ela, 05102018_papier_non_papier_peu_dense:0 23012025|ela, 05102018_papier_non_papier_presque_vide:0 23012025|ela, 05102018_papier_non_papier_tres_dense:0 23012025|ela, 05102018_papier_non_papier_tres_peu_dense:0 23012025|emr, 05102018_papier_non_papier_dense:0 23012025|emr, 05102018_papier_non_papier_peu_dense:0 23012025|emr, 05102018_papier_non_papier_presque_vide:0 23012025|emr, 05102018_papier_non_papier_tres_dense:0 23012025|emr, 05102018_papier_non_papier_tres_peu_dense:0 23012025|film_pedb, 05102018_papier_non_papier_dense:0 23012025|film_pedb, 05102018_papier_non_papier_peu_dense:0 23012025|film_pedb, 05102018_papier_non_papier_presque_vide:0 23012025|film_pedb, 05102018_papier_non_papier_tres_dense:0 23012025|film_pedb, 05102018_papier_non_papier_tres_peu_dense:0 23012025|flux_dev, 05102018_papier_non_papier_dense:0 23012025|flux_dev, 05102018_papier_non_papier_peu_dense:0 23012025|flux_dev, 05102018_papier_non_papier_presque_vide:0 23012025|flux_dev, 05102018_papier_non_papier_tres_dense:0 23012025|flux_dev, 05102018_papier_non_papier_tres_peu_dense:0 23012025|jrm, 05102018_papier_non_papier_dense:0 23012025|jrm, 05102018_papier_non_papier_peu_dense:0 23012025|jrm, 05102018_papier_non_papier_presque_vide:0 23012025|jrm, 05102018_papier_non_papier_tres_dense:0 23012025|jrm, 05102018_papier_non_papier_tres_peu_dense:0 23012025|pcm, 05102018_papier_non_papier_dense:0 23012025|pcm, 05102018_papier_non_papier_peu_dense:0 23012025|pcm, 05102018_papier_non_papier_presque_vide:0 23012025|pcm, 05102018_papier_non_papier_tres_dense:0 23012025|pcm, 05102018_papier_non_papier_tres_peu_dense:0 23012025|pcnc, 05102018_papier_non_papier_dense:0 23012025|pcnc, 05102018_papier_non_papier_peu_dense:0 23012025|pcnc, 05102018_papier_non_papier_presque_vide:0 23012025|pcnc, 05102018_papier_non_papier_tres_dense:0 23012025|pcnc, 05102018_papier_non_papier_tres_peu_dense:0 23012025|pehd_pp, 05102018_papier_non_papier_dense:0 23012025|pehd_pp, 05102018_papier_non_papier_peu_dense:0 23012025|pehd_pp, 05102018_papier_non_papier_presque_vide:0 23012025|pehd_pp, 05102018_papier_non_papier_tres_dense:0 23012025|pehd_pp, 05102018_papier_non_papier_tres_peu_dense:0 23012025|pet_clair, 05102018_papier_non_papier_dense:0 23012025|pet_clair, 05102018_papier_non_papier_peu_dense:0 23012025|pet_clair, 05102018_papier_non_papier_presque_vide:11.999935150146484 23012025|pet_clair, 05102018_papier_non_papier_tres_dense:0 23012025|pet_clair, 05102018_papier_non_papier_tres_peu_dense:0 23012025|refus, 05102018_papier_non_papier_dense:0 23012025|refus, 05102018_papier_non_papier_peu_dense:0 23012025|refus, 05102018_papier_non_papier_presque_vide:0 23012025|refus, 05102018_papier_non_papier_tres_dense:0 23012025|refus, 05102018_papier_non_papier_tres_peu_dense:0 23012025|tapis_vide, 05102018_papier_non_papier_dense:0 23012025|tapis_vide, 05102018_papier_non_papier_peu_dense:0 23012025|tapis_vide, 05102018_papier_non_papier_presque_vide:16.998584985733032 23012025|tapis_vide, 05102018_papier_non_papier_tres_dense:0 23012025|tapis_vide, 05102018_papier_non_papier_tres_peu_dense:0 #Number Photos for regression amount gros magasin papier (time_diff then nb_photo) : We have not displayed the number of photos removed for one material since Rungis_Papier wasn't in the thcl used ! 23012025_time_diff_distrib Number amount portfolio for this type of dechet : aluminium 0 Number amount portfolio for this type of dechet : ela 0 Number amount portfolio for this type of dechet : emr 0 Number amount portfolio for this type of dechet : film_pedb 0 Number amount portfolio for this type of dechet : flux_dev 0 Number amount portfolio for this type of dechet : jrm 0 Number amount portfolio for this type of dechet : pcm 0 Number amount portfolio for this type of dechet : pcnc 0 Number amount portfolio for this type of dechet : pehd_pp 0 Number amount portfolio for this type of dechet : pet_clair 2 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_pet_clair_05102018_papier_non_papier_presque_vide&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179433 with name like 23012025_pet_clair_05102018_papier_non_papier_presque_vide Number amount portfolio for this type of dechet : refus 0 Number amount portfolio for this type of dechet : tapis_vide 3 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_tapis_vide_05102018_papier_non_papier_presque_vide&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179435 with name like 23012025_tapis_vide_05102018_papier_non_papier_presque_vide begin to remove the low_density images haven't found thcl_volume NUMBER BATCH : 1 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['emr', 'pcm', 'pcnc', 'jrm', 'ela', 'pet_clair', 'film_pedb', 'pehd_pp', 'flux_dev', 'aluminium', 'tapis_vide', 'refus'] We have rejected 3 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 0 elapsed_time : count_nb_balles_and_create_portfolio 1.866206169128418 # DISPLAY ALL COLLECTED DATA : {'23012025': {'nb_upload': 6, 'nb_taggue_class': 6, 'nb_taggue_densite': 6, 'nb_descriptors': 0, 'number_port': 1, 'count_photo_in_port': 3, 'nb_port_per_class': {'aluminium': {'nb_photos': 0, 'nb_portfolios': 0}, 'ela': {'nb_photos': 0, 'nb_portfolios': 0}, 'emr': {'nb_photos': 0, 'nb_portfolios': 0}, 'film_pedb': {'nb_photos': 0, 'nb_portfolios': 0}, 'flux_dev': {'nb_photos': 0, 'nb_portfolios': 0}, 'jrm': {'nb_photos': 0, 'nb_portfolios': 0}, 'pcm': {'nb_photos': 0, 'nb_portfolios': 0}, 'pcnc': {'nb_photos': 0, 'nb_portfolios': 0}, 'pehd_pp': {'nb_photos': 0, 'nb_portfolios': 0}, 'pet_clair': {'nb_photos': 3, 'nb_portfolios': 1}, 'refus': {'nb_photos': 0, 'nb_portfolios': 0}, 'tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}}}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1330802451, 1330802447, 1330802442, 1330802438, 1330802429, 1330802416] Looping around the photos to save general results len do output : 1 /19845380Didn'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 ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802451', None, None, None, None, None, '2539880') ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802447', None, None, None, None, None, '2539880') ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802442', None, None, None, None, None, '2539880') ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802438', None, None, None, None, None, '2539880') ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802429', None, None, None, None, None, '2539880') ('4887', None, None, None, None, None, None, None, '2539880') ('4887', '19845380', '1330802416', None, None, None, None, None, '2539880') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 7 time used for this insertion : 0.01890087127685547 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.0133583545684814 time spend to save output : 0.019148826599121094 total time spend for step 1 : 2.0325071811676025 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 1 set_done_treatment 1.04user 0.78system 0:05.24elapsed 34%CPU (0avgtext+0avgdata 100144maxresident)k 0inputs+40outputs (9major+49060minor)pagefaults 0swaps