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 2539881' -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 : 85575 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 : 4893, datou_cur_ids : ['2539881'] with mtr_portfolio_ids : ['19847625'] and first list_photo_ids : [] new path : /proc/85575/ 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 : 0.14303088188171387 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 14:52:41 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 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'}] (('13', 48),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 48} 23012025 19847625 Nombre de photos uploadées : 48 / 23040 (0%) 23012025 19847625 Nombre de photos taguées (types de déchets): 48 / 48 (100%) 23012025 19847625 Nombre de photos taguées (volume) : 48 / 48 (100%) elapsed_time : load_data_split_time_score 3.5762786865234375e-06 elapsed_time : order_list_meta_photo_and_scores 3.409385681152344e-05 elapsed_time : fill_and_build_computed_from_old_data 0.002817392349243164 elapsed_time : insert_dashboard_record_day_entry 0.023374319076538086 Creating list_photo_total elapsed_time : select_descriptors 0.011281728744506836 23012025 19847625 Nombre de photos avec descriptors (type 6091) : 0 / 36 (0%) Missing descriptors for photos 0 and 1330832989 0:00:00|ON:Missing descriptors for photos 1330832989 and 1330832984 Missing descriptors for photos 1330832984 and 1330832977 Missing descriptors for photos 1330832977 and 1330832974 Missing descriptors for photos 1330832974 and 1330833136 Missing descriptors for photos 1330833136 and 1330833081 Missing descriptors for photos 1330833081 and 1330833076 Missing descriptors for photos 1330833076 and 1330833070 Missing descriptors for photos 1330833070 and 1330833064 Missing descriptors for photos 1330833064 and 1330833037 Missing descriptors for photos 1330833037 and 1330833345 Missing descriptors for photos 1330833345 and 1330833340 Missing descriptors for photos 1330833340 and 1330833333 Missing descriptors for photos 1330833333 and 1330833327 Missing descriptors for photos 1330833327 and 1330833194 Missing descriptors for photos 1330833194 and 1330833158 Missing descriptors for photos 1330833158 and 1330833413 Missing descriptors for photos 1330833413 and 1330833405 Missing descriptors for photos 1330833405 and 1330833397 Missing descriptors for photos 1330833397 and 1330833390 Missing descriptors for photos 1330833390 and 1330833381 Missing descriptors for photos 1330833381 and 1330833376 Missing descriptors for photos 1330833376 and 1330833581 Missing descriptors for photos 1330833581 and 1330833575 Missing descriptors for photos 1330833575 and 1330833571 Missing descriptors for photos 1330833571 and 1330833566 Missing descriptors for photos 1330833566 and 1330833560 Missing descriptors for photos 1330833560 and 1330833555 Missing descriptors for photos 1330833555 and 1330833624 Missing descriptors for photos 1330833624 and 1330833619 Missing descriptors for photos 1330833619 and 1330833614 Missing descriptors for photos 1330833614 and 1330833610 Missing descriptors for photos 1330833610 and 1330833608 Missing descriptors for photos 1330833608 and 1330833602 Missing descriptors for photos 1330833602 and 1330833917 Missing descriptors for photos 1330833917 and 1330833910 Missing descriptors for photos 1330833910 and 1330833899 Missing descriptors for photos 1330833899 and 1330833892 Missing descriptors for photos 1330833892 and 1330833886 Missing descriptors for photos 1330833886 and 1330833879 Missing descriptors for photos 1330833879 and 1330833871 Missing descriptors for photos 1330833871 and 1330833838 Missing descriptors for photos 1330833838 and 1330833834 Missing descriptors for photos 1330833834 and 1330833828 Missing descriptors for photos 1330833828 and 1330833816 Missing descriptors for photos 1330833816 and 1330833805 Missing descriptors for photos 1330833805 and 1330833795 Missing descriptors for photos 1330833795 and 1330833865 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 : 48 time used for this insertion : 0.019902467727661133 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.058531761169433594 Creating list_photo_total time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the 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moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average elapsed_time : count_sum_diff_and_build_graph 0.013613224029541016 Total photos : 48 .can't find max_score_info .Change port : 0 hashtag : 1284539308 photo_id =1330832984 : pcnc ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .....can't find max_score_info .can't find max_score_info ...........Change port : 16 hashtag : 616987804 photo_id =1330833575 : emr .Change port : 1 hashtag : 1284539308 photo_id =1330833571 : pcnc .......can't find max_score_info .can't find max_score_info ..can't find max_score_info ......can't find max_score_info ...can't find max_score_info .... Total photos : 48 Number of lists : 4 counter photos in port : 36 hashtag : aluminium(493546845) : 0 photos in 0 portfolios ! hashtag : ela(492741797) : 0 photos in 0 portfolios ! hashtag : emr(616987804) : 1 photos in 1 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) : 35 photos in 2 portfolios ! hashtag : pehd_pp(2107760239) : 0 photos in 0 portfolios ! hashtag : pet_clair(2107755846) : 0 photos in 0 portfolios ! hashtag : refus(538914404) : 0 photos in 0 portfolios ! hashtag : tapis_vide(2107748999) : 0 photos in 1 portfolios ! elapsed_time : group_photo_by_moyenne_exp 0.001653909683227539 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 3.814697265625e-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 : 3 #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: 11.000710010528564, 2107751015: 78.99692797660828, 2107751016: 0, 2107751017: 11.00131893157959}, 2107760237: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107760238: {2107751013: 0, 2107751014: 0, 2107751015: 10.999999046325684, 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: 69.0001151561737, 2107751015: 260.0023121833801, 2107751016: 20.999884843826294, 2107751017: 28.999303102493286}, 2107760239: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107755846: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 538914404: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107748999: {2107751013: 0, 2107751014: 0, 2107751015: 110.00041675567627, 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:11.000710010528564 23012025|emr, 05102018_papier_non_papier_presque_vide:78.99692797660828 23012025|emr, 05102018_papier_non_papier_tres_dense:0 23012025|emr, 05102018_papier_non_papier_tres_peu_dense:11.00131893157959 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:10.999999046325684 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:69.0001151561737 23012025|pcnc, 05102018_papier_non_papier_presque_vide:260.0023121833801 23012025|pcnc, 05102018_papier_non_papier_tres_dense:20.999884843826294 23012025|pcnc, 05102018_papier_non_papier_tres_peu_dense:28.999303102493286 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:0 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:110.00041675567627 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 10 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_emr_05102018_papier_non_papier_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179685 with name like 23012025_emr_05102018_papier_non_papier_peu_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_emr_05102018_papier_non_papier_presque_vide&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179686 with name like 23012025_emr_05102018_papier_non_papier_presque_vide https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_emr_05102018_papier_non_papier_tres_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179687 with name like 23012025_emr_05102018_papier_non_papier_tres_peu_dense Number amount portfolio for this type of dechet : film_pedb 0 Number amount portfolio for this type of dechet : flux_dev 1 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_flux_dev_05102018_papier_non_papier_presque_vide&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179689 with name like 23012025_flux_dev_05102018_papier_non_papier_presque_vide 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 25 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_pcnc_05102018_papier_non_papier_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179690 with name like 23012025_pcnc_05102018_papier_non_papier_peu_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_pcnc_05102018_papier_non_papier_presque_vide&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179691 with name like 23012025_pcnc_05102018_papier_non_papier_presque_vide https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_pcnc_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179693 with name like 23012025_pcnc_05102018_papier_non_papier_tres_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=23012025_pcnc_05102018_papier_non_papier_tres_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20179694 with name like 23012025_pcnc_05102018_papier_non_papier_tres_peu_dense Number amount portfolio for this type of dechet : pehd_pp 0 Number amount portfolio for this type of dechet : pet_clair 0 Number amount portfolio for this type of dechet : refus 0 Number amount portfolio for this type of dechet : tapis_vide 11 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 : 20179695 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 : 4 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 filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_pcnc:{'day': '23012025', 'map_nb_amount': {0: 0, 1: 12, 2: 1, 3: 3, 4: 0}, 'map_time_amount': {0: 0, 1: 121.00063920021057, 2: 11.000549793243408, 3: 28.999303102493286, 4: 0}, 'duration': 208.99934315681458, 'nb_balles_papier': 0.16100049209594727, 'begin_time_port': 'image_23012025_13_48_25_10661.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0.16100049209594727 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_pcnc:{'day': '23012025', 'map_nb_amount': {0: 3, 1: 14, 2: 1, 3: 1, 4: 0}, 'map_time_amount': {0: 80.00082516670227, 1: 217.99797296524048, 2: 9.999335050582886, 3: 11.00131893157959, 4: 0}, 'duration': 361.0015380382538, 'nb_balles_papier': 0.31899945211410524, 'begin_time_port': 'image_23012025_13_52_14_9561.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0.31899945211410524 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We have rejected 1 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 2 list_same_port_ids : [] https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=pcnc_diff_batch__23012025_13_48_25_010661&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 list_same_port_ids : [] https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=pcnc_diff_batch__23012025_13_52_14_009561&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 # 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=20179696 AND mptpi.`type`=4207 To do # 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 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 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`=20179698 AND mptpi.`type`=4207 To do elapsed_time : count_nb_balles_and_create_portfolio 11.48966646194458 # DISPLAY ALL COLLECTED DATA : {'23012025': {'nb_upload': 48, 'nb_taggue_class': 48, 'nb_taggue_densite': 48, 'nb_descriptors': 0, 'number_port': 4, 'count_photo_in_port': 36, 'nb_port_per_class': {'aluminium': {'nb_photos': 0, 'nb_portfolios': 0}, 'ela': {'nb_photos': 0, 'nb_portfolios': 0}, 'emr': {'nb_photos': 1, 'nb_portfolios': 1}, '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': 35, 'nb_portfolios': 2}, 'pehd_pp': {'nb_photos': 0, 'nb_portfolios': 0}, 'pet_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'refus': {'nb_photos': 0, 'nb_portfolios': 0}, 'tapis_vide': {'nb_photos': 0, 'nb_portfolios': 1}}}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1330833917, 1330833910, 1330833899, 1330833892, 1330833886, 1330833879, 1330833871, 1330833865, 1330833838, 1330833834, 1330833828, 1330833816, 1330833805, 1330833795, 1330833624, 1330833619, 1330833614, 1330833610, 1330833608, 1330833602, 1330833581, 1330833575, 1330833571, 1330833566, 1330833560, 1330833555, 1330833413, 1330833405, 1330833397, 1330833390, 1330833381, 1330833376, 1330833345, 1330833340, 1330833333, 1330833327, 1330833194, 1330833158, 1330833136, 1330833081, 1330833076, 1330833070, 1330833064, 1330833037, 1330832989, 1330832984, 1330832977, 1330832974] Looping around the photos to save general results len do output : 1 /19847625Didn'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 ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833917', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833910', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833899', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833892', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833886', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833879', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833871', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833865', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833838', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833834', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833828', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833816', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833805', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833795', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833624', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833619', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833614', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833610', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833608', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833602', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833581', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833575', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833571', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833566', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833560', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833555', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833413', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833405', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833397', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833390', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833381', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833376', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833345', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833340', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833333', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833327', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833194', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833158', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833136', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833081', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833076', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833070', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833064', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330833037', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330832989', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330832984', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330832977', None, None, None, None, None, '2539881') ('4893', None, None, None, None, None, None, None, '2539881') ('4893', '19847625', '1330832974', None, None, None, None, None, '2539881') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 49 time used for this insertion : 0.17136096954345703 save_final save missing photos in datou_result : time spend for datou_step_exec : 11.681493282318115 time spend to save output : 0.17184853553771973 total time spend for step 1 : 11.853341817855835 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 1.16user 0.77system 0:14.32elapsed 13%CPU (0avgtext+0avgdata 101040maxresident)k 0inputs+104outputs (17major+48900minor)pagefaults 0swaps