python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 8 -a ' -a 4323 -l 20 --fifo' -s datou_current_sts -M 0 -S 0 -U 95,95,120 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/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', '/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 : 1392779 load datou : 4323 # 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 for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] 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 we have a portfolio with more photos than limit : 34>20 please execute split_portfolio.py -i 24795299 -l 20 size over we load limit photo not treated list_input_json: {} Current got : datou_id : 4323, datou_cur_ids : ['3265355'] with mtr_portfolio_ids : ['24795299'] and first list_photo_ids : [] new path : /proc/1392779/ 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 list_input_json : {} origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.01470804214477539 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Thu Jul 10 12:08:07 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': 3847, 'mtr_user_id': 31, 'name': 'learn_MM_generique_050224', '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': '13096157,13096155,13096163,13096159,13301956,13095886,13096162,13096160,13358264,13096158,5515868,13276803', 'photo_hashtag_type': 4932, 'photo_desc_type': 6032, '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'}] (('06', 22), ('00', 12)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 28} 10072025 24795299 Nombre de photos uploadées : 34 / 23040 (0%) 10072025 24795299 Nombre de photos taguées (types de déchets): 28 / 34 (82%) 10072025 24795299 Nombre de photos taguées (volume) : 28 / 34 (82%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 2.1219253540039062e-05 ?????? elapsed_time : fill_and_build_computed_from_old_data 0.0021491050720214844 elapsed_time : insert_dashboard_record_day_entry 0.02269434928894043 Creating list_photo_total elapsed_time : select_descriptors 1.0583364963531494 10072025 24795299 Nombre de photos avec descriptors (type 6032) : 23 / 29 (79%) Missing descriptors for photos 0 and 1371498206 0:00:00|ON:Missing descriptors for photos 1371498206 and 1371498268 Missing descriptors for photos 1371498268 and 1371498350 Missing descriptors for photos 1371498350 and 1371498431 Missing descriptors for photos 1371498431 and 1371498514 ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 1280 vs 0 photo_id : 1371499704 photo_id_prec : 1371499595 Missing descriptors for photos 1371499704 and 1371499700 Missing descriptors for photos 1371499700 and 1371499696 Missing descriptors for photos 1371499696 and 1371499685 Missing descriptors for photos 1371499685 and 1371499674 Missing descriptors for photos 1371499674 and 1371499670 ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1371499552 photo_id_prec : 1371499670 6:44:38.999717|OFF:0:00:10.999901|ON:0:00:00|OFF:0:00:09.999898|ON:0:00:00|OFF:0:00:10.000100|ON:0:00:00|OFF:0:00:10.000088|ON:0:00:00|OFF:0:00:08.998633|ON:0:00:51.001277|OFF: 10072025 Removing 6 photos because of the 'same image' condition Total on : 24330.000993999998 list_time_on Total off : 49.998619999999995 list_time_off dist_desc begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 34 time used for this insertion : 0.014252901077270508 photos_removed : len 6 elapsed_time : remove_photo_duplicate 0.05561089515686035 Creating list_photo_total XXXXXXWarning list_scores null Warning list_scores null Warning list_scores null Warning list_scores null Warning list_scores null Warning list_scores null 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 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 ERROR ! ERROR ! elapsed_time : count_sum_diff_and_build_graph 0.007437467575073242 Total photos : 34 .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 : 0 hashtag : 1284539308 photo_id =1371498599 : pcnc .......Change port : 7 hashtag : 2107760237 photo_id =1371499552 : film_pedb .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 Total photos : 34 Number of lists : 3 counter photos in port : 17 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) : 10 photos in 1 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) : 7 photos in 1 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 0.0011930465698242188 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 2.1457672119140625e-06 today str has not a value , we define it as the date of the first image todaystr_first : 10072025 attention , prev_timestamp is 0 , we do nothing Unexpected type of data : ({'photo_id': 1371499704, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/ea40f11663b35301075c13335dd66374.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_43_44_10182.jpg', 'time': 1752129824.010182}, 'different') Unexpected type of data : ({'photo_id': 1371499700, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/9241222504ed13b0699249777c1387e2.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_43_55_10232.jpg', 'time': 1752129835.010232}, 'different') Unexpected type of data : ({'photo_id': 1371499696, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/d58381940a88bfc8bd7c8ce63f2df891.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_44_05_10216.jpg', 'time': 1752129845.010216}, 'different') Unexpected type of data : ({'photo_id': 1371499685, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/a79d754814b75bde993a29d2562bd084.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_44_15_10149.jpg', 'time': 1752129855.010149}, 'different') Unexpected type of data : ({'photo_id': 1371499674, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/bcf1c033a6788f146fe9f5413f0d41d6.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_44_25_10129.jpg', 'time': 1752129865.010129}, 'different') Unexpected type of data : ({'photo_id': 1371499670, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2025/7/10/1c3da5de573444ce2c07d446753704ad.jpg', 'username': None, 'uploaded_at': 1752141983, 'text': 'image_10072025_06_44_35_10105.jpg', 'time': 1752129875.010105}, 'different') * BIG TIME 24158.99872303009 (60.00011396408081, 7, 0, 0, 0, 0, 0, 0, 0, 0.80377775, 0, 0, 0, 0, 0.01099996190071106, 0.0012, 0.0, 1.9, 0.05000025701522827, -0.06666701992352804) on 7 1371499552 2025-07-10 06:44:44.008918 id_data : 18 ooooCount Time bigger than 30s : 1 #Number Photos for regression : {'10072025': {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: 9.999928951263428, 2107751016: 0, 2107751017: 0}, 2107760237: {2107751013: 0, 2107751014: 0, 2107751015: 49.99862217903137, 2107751016: 41.001200914382935, 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: 10.000056028366089, 2107751015: 40.00020909309387, 2107751016: 10.000037908554077, 2107751017: 0}, 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: 39.99938702583313, 2107751016: 0, 2107751017: 0}}} 10072025|aluminium, 05102018_papier_non_papier_dense:0 10072025|aluminium, 05102018_papier_non_papier_peu_dense:0 10072025|aluminium, 05102018_papier_non_papier_presque_vide:0 10072025|aluminium, 05102018_papier_non_papier_tres_dense:0 10072025|aluminium, 05102018_papier_non_papier_tres_peu_dense:0 10072025|ela, 05102018_papier_non_papier_dense:0 10072025|ela, 05102018_papier_non_papier_peu_dense:0 10072025|ela, 05102018_papier_non_papier_presque_vide:0 10072025|ela, 05102018_papier_non_papier_tres_dense:0 10072025|ela, 05102018_papier_non_papier_tres_peu_dense:0 10072025|emr, 05102018_papier_non_papier_dense:0 10072025|emr, 05102018_papier_non_papier_peu_dense:0 10072025|emr, 05102018_papier_non_papier_presque_vide:9.999928951263428 10072025|emr, 05102018_papier_non_papier_tres_dense:0 10072025|emr, 05102018_papier_non_papier_tres_peu_dense:0 10072025|film_pedb, 05102018_papier_non_papier_dense:0 10072025|film_pedb, 05102018_papier_non_papier_peu_dense:0 10072025|film_pedb, 05102018_papier_non_papier_presque_vide:49.99862217903137 10072025|film_pedb, 05102018_papier_non_papier_tres_dense:41.001200914382935 10072025|film_pedb, 05102018_papier_non_papier_tres_peu_dense:0 10072025|flux_dev, 05102018_papier_non_papier_dense:0 10072025|flux_dev, 05102018_papier_non_papier_peu_dense:0 10072025|flux_dev, 05102018_papier_non_papier_presque_vide:0 10072025|flux_dev, 05102018_papier_non_papier_tres_dense:0 10072025|flux_dev, 05102018_papier_non_papier_tres_peu_dense:0 10072025|jrm, 05102018_papier_non_papier_dense:0 10072025|jrm, 05102018_papier_non_papier_peu_dense:0 10072025|jrm, 05102018_papier_non_papier_presque_vide:0 10072025|jrm, 05102018_papier_non_papier_tres_dense:0 10072025|jrm, 05102018_papier_non_papier_tres_peu_dense:0 10072025|pcm, 05102018_papier_non_papier_dense:0 10072025|pcm, 05102018_papier_non_papier_peu_dense:0 10072025|pcm, 05102018_papier_non_papier_presque_vide:0 10072025|pcm, 05102018_papier_non_papier_tres_dense:0 10072025|pcm, 05102018_papier_non_papier_tres_peu_dense:0 10072025|pcnc, 05102018_papier_non_papier_dense:0 10072025|pcnc, 05102018_papier_non_papier_peu_dense:10.000056028366089 10072025|pcnc, 05102018_papier_non_papier_presque_vide:40.00020909309387 10072025|pcnc, 05102018_papier_non_papier_tres_dense:10.000037908554077 10072025|pcnc, 05102018_papier_non_papier_tres_peu_dense:0 10072025|pehd_pp, 05102018_papier_non_papier_dense:0 10072025|pehd_pp, 05102018_papier_non_papier_peu_dense:0 10072025|pehd_pp, 05102018_papier_non_papier_presque_vide:0 10072025|pehd_pp, 05102018_papier_non_papier_tres_dense:0 10072025|pehd_pp, 05102018_papier_non_papier_tres_peu_dense:0 10072025|pet_clair, 05102018_papier_non_papier_dense:0 10072025|pet_clair, 05102018_papier_non_papier_peu_dense:0 10072025|pet_clair, 05102018_papier_non_papier_presque_vide:0 10072025|pet_clair, 05102018_papier_non_papier_tres_dense:0 10072025|pet_clair, 05102018_papier_non_papier_tres_peu_dense:0 10072025|refus, 05102018_papier_non_papier_dense:0 10072025|refus, 05102018_papier_non_papier_peu_dense:0 10072025|refus, 05102018_papier_non_papier_presque_vide:0 10072025|refus, 05102018_papier_non_papier_tres_dense:0 10072025|refus, 05102018_papier_non_papier_tres_peu_dense:0 10072025|tapis_vide, 05102018_papier_non_papier_dense:0 10072025|tapis_vide, 05102018_papier_non_papier_peu_dense:0 10072025|tapis_vide, 05102018_papier_non_papier_presque_vide:39.99938702583313 10072025|tapis_vide, 05102018_papier_non_papier_tres_dense:0 10072025|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 ! 10072025_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 1 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_emr_05102018_papier_non_papier_presque_vide&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795797 with name like 10072025_emr_05102018_papier_non_papier_presque_vide Number amount portfolio for this type of dechet : film_pedb 9 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_film_pedb_05102018_papier_non_papier_presque_vide&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795798 with name like 10072025_film_pedb_05102018_papier_non_papier_presque_vide https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_film_pedb_05102018_papier_non_papier_tres_dense&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795799 with name like 10072025_film_pedb_05102018_papier_non_papier_tres_dense 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 6 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_pcnc_05102018_papier_non_papier_peu_dense&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795800 with name like 10072025_pcnc_05102018_papier_non_papier_peu_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_pcnc_05102018_papier_non_papier_presque_vide&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795801 with name like 10072025_pcnc_05102018_papier_non_papier_presque_vide https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_pcnc_05102018_papier_non_papier_tres_dense&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795802 with name like 10072025_pcnc_05102018_papier_non_papier_tres_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 4 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=10072025_tapis_vide_05102018_papier_non_papier_presque_vide&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 Created to study and clean : 24795804 with name like 10072025_tapis_vide_05102018_papier_non_papier_presque_vide NUMBER BATCH : 3 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 : ['pcnc', 'gm', 'emr', 'ela', 'pet_clair', 'film_pedb', 'pehd_pp', 'flux_dev_rigide', 'aluminium', 'tapis_vide', 'refus', 'gros_cartons', 'gm', 'flux_dev_rigide', 'gros_cartons'] We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! hashtag non trouvé ! We filter photos on hashtag condition ! hashtag non trouvé ! hashtag non trouvé ! 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_gros_cartons:{'day': '10072025', 'map_nb_amount': {0: 1, 1: 5, 2: 1, 3: 0, 4: 0}, 'map_time_amount': {0: 10.000056028366089, 1: 50.0001380443573, 2: 10.000037908554077, 3: 0, 4: 0}, 'duration': 60.0001859664917, 'nb_balles_papier': 0.07000023198127747, 'begin_time_port': 'image_10072025_00_01_05_10009.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0.07000023198127747 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_film_pedb:{'day': '10072025', 'map_nb_amount': {0: 1, 1: 5, 2: 4, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 49.99862217903137, 2: 41.001200914382935, 3: 0, 4: 0}, 'duration': 101.00119805335999, 'nb_balles_papier': 0.0919998230934143, 'begin_time_port': 'image_10072025_06_44_44_8918.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0.0919998230934143 hashtag non trouvé ! We filter photos on hashtag condition ! hashtag non trouvé ! hashtag non trouvé ! 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 have rejected 0 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=gros_cartons_diff_batch__10072025_00_01_05_010009&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 list_same_port_ids : [] https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=film_pedb_diff_batch__10072025_06_44_44_008918&access_token=3e00c8f3e5af383c48e3c68940ba6fe7 # 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`=24795806 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 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 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 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 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 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 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`=24795808 AND mptpi.`type`=4461 To do elapsed_time : count_nb_balles_and_create_portfolio 41.70286464691162 # DISPLAY ALL COLLECTED DATA : {'10072025': {'nb_upload': 34, 'nb_taggue_class': 28, 'nb_taggue_densite': 28, 'nb_descriptors': 23, 'number_port': 3, 'count_photo_in_port': 17, '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': 10, 'nb_portfolios': 1}, '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': 7, 'nb_portfolios': 1}, '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 [1371499704, 1371499700, 1371499696, 1371499685, 1371499674, 1371499670, 1371499639, 1371499636, 1371499632, 1371499622, 1371499595, 1371499592, 1371499581, 1371499576, 1371499574, 1371499572, 1371499552, 1371499536, 1371499533, 1371499528] Looping around the photos to save general results len do output : 1 /24795299Didn'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 ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499704', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499700', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499696', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499685', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499674', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499670', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499639', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499636', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499632', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499622', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499595', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499592', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499581', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499576', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499574', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499572', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499552', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499536', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499533', None, None, None, None, None, '3265355') ('4323', None, None, None, None, None, None, None, '3265355') ('4323', '24795299', '1371499528', None, None, None, None, None, '3265355') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.07155799865722656 save_final save missing photos in datou_result : time spend for datou_step_exec : 42.92408990859985 time spend to save output : 0.07183957099914551 total time spend for step 1 : 42.995929479599 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 1.22user 0.99system 0:46.08elapsed 4%CPU (0avgtext+0avgdata 103860maxresident)k 40inputs+264outputs (2major+49060minor)pagefaults 0swaps