python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 4891' -s datou_current_4891 -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 : 1764408 load datou : 4891 # 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 updating current state to 1 list_input_json: [] Current got : datou_id : 4891, datou_cur_ids : ['2918337'] with mtr_portfolio_ids : ['23093913'] and first list_photo_ids : [] new path : /proc/1764408/ 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 : 0.03579354286193848 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Wed May 21 08:40:28 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': 3892, 'mtr_user_id': 31, 'name': 'learn_MM_generique_26022025', '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': '17736100,17736101,17736102,17736103,17736104,20837895,20837896,17736107,17736108,17736109,17736110,18876169', 'photo_hashtag_type': 4989, 'photo_desc_type': 6092, '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'}] (('00', 6), ('01', 3), ('02', 6), ('03', 1), ('06', 5), ('07', 3), ('08', 4), ('09', 7), ('10', 6), ('13', 6), ('14', 6), ('12', 1), ('15', 3), ('16', 4), ('17', 2), ('18', 2), ('19', 4), ('20', 7), ('22', 1)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 77} 18052025 23093913 Nombre de photos uploadées : 77 / 23040 (0%) 18052025 23093913 Nombre de photos taguées (types de déchets): 77 / 77 (100%) 18052025 23093913 Nombre de photos taguées (volume) : 77 / 77 (100%) elapsed_time : load_data_split_time_score 1.6689300537109375e-06 elapsed_time : order_list_meta_photo_and_scores 3.6716461181640625e-05 elapsed_time : fill_and_build_computed_from_old_data 0.0034813880920410156 elapsed_time : insert_dashboard_record_day_entry 0.02973318099975586 Creating list_photo_total elapsed_time : select_descriptors 0.007048606872558594 18052025 23093913 Nombre de photos avec descriptors (type 6092) : 0 / 0 (0%) Missing descriptors for photos 0 and 1359125626 0:00:00|ON:Missing descriptors for photos 1359125626 and 1359125830 Missing descriptors for photos 1359125830 and 1359126040 Missing descriptors for photos 1359126040 and 1359132384 Missing descriptors for photos 1359132384 and 1359126774 Missing descriptors for photos 1359126774 and 1359126997 Missing descriptors for photos 1359126997 and 1359128587 Missing descriptors for photos 1359128587 and 1359128812 Missing descriptors for photos 1359128812 and 1359129217 Missing descriptors for photos 1359129217 and 1359131573 Missing descriptors for photos 1359131573 and 1359147681 Missing descriptors for photos 1359147681 and 1359132443 Missing descriptors for photos 1359132443 and 1359132736 Missing descriptors for photos 1359132736 and 1359134784 Missing descriptors for photos 1359134784 and 1359135423 Missing descriptors for photos 1359135423 and 1359135875 Missing descriptors for photos 1359135875 and 1359142423 Missing descriptors for photos 1359142423 and 1359142683 Missing descriptors for photos 1359142683 and 1359142940 Missing descriptors for photos 1359142940 and 1359143152 Missing descriptors for photos 1359143152 and 1359143584 Missing descriptors for photos 1359143584 and 1359144295 Missing descriptors for photos 1359144295 and 1359144963 Missing descriptors for photos 1359144963 and 1359145553 Missing descriptors for photos 1359145553 and 1359165631 Missing descriptors for photos 1359165631 and 1359151201 Missing descriptors for photos 1359151201 and 1359151701 Missing descriptors for photos 1359151701 and 1359152378 Missing descriptors for photos 1359152378 and 1359153147 Missing descriptors for photos 1359153147 and 1359153605 Missing descriptors for photos 1359153605 and 1359154306 Missing descriptors for photos 1359154306 and 1359154612 Missing descriptors for photos 1359154612 and 1359155062 Missing descriptors for photos 1359155062 and 1359155391 Missing descriptors for photos 1359155391 and 1359155839 Missing descriptors for photos 1359155839 and 1359156714 Missing descriptors for photos 1359156714 and 1359157043 Missing descriptors for photos 1359157043 and 1359158726 Missing descriptors for photos 1359158726 and 1359159231 Missing descriptors for photos 1359159231 and 1359159807 Missing descriptors for photos 1359159807 and 1359160329 Missing descriptors for photos 1359160329 and 1359189896 Missing descriptors for photos 1359189896 and 1359166441 Missing descriptors for photos 1359166441 and 1359166628 Missing descriptors for photos 1359166628 and 1359166794 Missing descriptors for photos 1359166794 and 1359168793 Missing descriptors for photos 1359168793 and 1359170590 Missing descriptors for photos 1359170590 and 1359171149 Missing descriptors for photos 1359171149 and 1359172268 Missing descriptors for photos 1359172268 and 1359174942 Missing descriptors for photos 1359174942 and 1359177678 Missing descriptors for photos 1359177678 and 1359179237 Missing descriptors for photos 1359179237 and 1359181339 Missing descriptors for photos 1359181339 and 1359182922 Missing descriptors for photos 1359182922 and 1359208691 Missing descriptors for photos 1359208691 and 1359194244 Missing descriptors for photos 1359194244 and 1359194426 Missing descriptors for photos 1359194426 and 1359198399 Missing descriptors for photos 1359198399 and 1359200134 Missing descriptors for photos 1359200134 and 1359202252 Missing descriptors for photos 1359202252 and 1359203592 Missing descriptors for photos 1359203592 and 1359240877 Missing descriptors for photos 1359240877 and 1359217547 Missing descriptors for photos 1359217547 and 1359221499 Missing descriptors for photos 1359221499 and 1359223280 Missing descriptors for photos 1359223280 and 1359236469 Missing descriptors for photos 1359236469 and 1359239152 Missing descriptors for photos 1359239152 and 1359254521 Missing descriptors for photos 1359254521 and 1359242504 Missing descriptors for photos 1359242504 and 1359246845 Missing descriptors for photos 1359246845 and 1359247417 Missing descriptors for photos 1359247417 and 1359249067 Missing descriptors for photos 1359249067 and 1359249511 Missing descriptors for photos 1359249511 and 1359250773 Missing descriptors for photos 1359250773 and 1359252857 Missing descriptors for photos 1359252857 and 1359254355 Missing descriptors for photos 1359254355 and 1359278057 18052025 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 : 77 time used for this insertion : 0.021634578704833984 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.04579877853393555 Creating list_photo_total elapsed_time : count_sum_diff_and_build_graph 0.000514984130859375 Total photos : 77 .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 .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 .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 .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 .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 .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 .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 .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 .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 .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 .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 .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 .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 : 77 Number of lists : 0 counter photos in port : 0 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) : 0 photos in 0 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 0.0030879974365234375 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 3.5762786865234375e-06 today str has not a value , we define it as the date of the first image todaystr_first : 18052025 attention , prev_timestamp is 0 , we do nothing ****************************************************************************Count Time bigger than 30s : 76 #Number Photos for regression : {'18052025': {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: 0, 2107751016: 0, 2107751017: 0}, 538914404: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107748999: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}}} 18052025|aluminium, 05102018_papier_non_papier_dense:0 18052025|aluminium, 05102018_papier_non_papier_peu_dense:0 18052025|aluminium, 05102018_papier_non_papier_presque_vide:0 18052025|aluminium, 05102018_papier_non_papier_tres_dense:0 18052025|aluminium, 05102018_papier_non_papier_tres_peu_dense:0 18052025|ela, 05102018_papier_non_papier_dense:0 18052025|ela, 05102018_papier_non_papier_peu_dense:0 18052025|ela, 05102018_papier_non_papier_presque_vide:0 18052025|ela, 05102018_papier_non_papier_tres_dense:0 18052025|ela, 05102018_papier_non_papier_tres_peu_dense:0 18052025|emr, 05102018_papier_non_papier_dense:0 18052025|emr, 05102018_papier_non_papier_peu_dense:0 18052025|emr, 05102018_papier_non_papier_presque_vide:0 18052025|emr, 05102018_papier_non_papier_tres_dense:0 18052025|emr, 05102018_papier_non_papier_tres_peu_dense:0 18052025|film_pedb, 05102018_papier_non_papier_dense:0 18052025|film_pedb, 05102018_papier_non_papier_peu_dense:0 18052025|film_pedb, 05102018_papier_non_papier_presque_vide:0 18052025|film_pedb, 05102018_papier_non_papier_tres_dense:0 18052025|film_pedb, 05102018_papier_non_papier_tres_peu_dense:0 18052025|flux_dev, 05102018_papier_non_papier_dense:0 18052025|flux_dev, 05102018_papier_non_papier_peu_dense:0 18052025|flux_dev, 05102018_papier_non_papier_presque_vide:0 18052025|flux_dev, 05102018_papier_non_papier_tres_dense:0 18052025|flux_dev, 05102018_papier_non_papier_tres_peu_dense:0 18052025|jrm, 05102018_papier_non_papier_dense:0 18052025|jrm, 05102018_papier_non_papier_peu_dense:0 18052025|jrm, 05102018_papier_non_papier_presque_vide:0 18052025|jrm, 05102018_papier_non_papier_tres_dense:0 18052025|jrm, 05102018_papier_non_papier_tres_peu_dense:0 18052025|pcm, 05102018_papier_non_papier_dense:0 18052025|pcm, 05102018_papier_non_papier_peu_dense:0 18052025|pcm, 05102018_papier_non_papier_presque_vide:0 18052025|pcm, 05102018_papier_non_papier_tres_dense:0 18052025|pcm, 05102018_papier_non_papier_tres_peu_dense:0 18052025|pcnc, 05102018_papier_non_papier_dense:0 18052025|pcnc, 05102018_papier_non_papier_peu_dense:0 18052025|pcnc, 05102018_papier_non_papier_presque_vide:0 18052025|pcnc, 05102018_papier_non_papier_tres_dense:0 18052025|pcnc, 05102018_papier_non_papier_tres_peu_dense:0 18052025|pehd_pp, 05102018_papier_non_papier_dense:0 18052025|pehd_pp, 05102018_papier_non_papier_peu_dense:0 18052025|pehd_pp, 05102018_papier_non_papier_presque_vide:0 18052025|pehd_pp, 05102018_papier_non_papier_tres_dense:0 18052025|pehd_pp, 05102018_papier_non_papier_tres_peu_dense:0 18052025|pet_clair, 05102018_papier_non_papier_dense:0 18052025|pet_clair, 05102018_papier_non_papier_peu_dense:0 18052025|pet_clair, 05102018_papier_non_papier_presque_vide:0 18052025|pet_clair, 05102018_papier_non_papier_tres_dense:0 18052025|pet_clair, 05102018_papier_non_papier_tres_peu_dense:0 18052025|refus, 05102018_papier_non_papier_dense:0 18052025|refus, 05102018_papier_non_papier_peu_dense:0 18052025|refus, 05102018_papier_non_papier_presque_vide:0 18052025|refus, 05102018_papier_non_papier_tres_dense:0 18052025|refus, 05102018_papier_non_papier_tres_peu_dense:0 18052025|tapis_vide, 05102018_papier_non_papier_dense:0 18052025|tapis_vide, 05102018_papier_non_papier_peu_dense:0 18052025|tapis_vide, 05102018_papier_non_papier_presque_vide:0 18052025|tapis_vide, 05102018_papier_non_papier_tres_dense:0 18052025|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 ! 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 0 Number amount portfolio for this type of dechet : refus 0 Number amount portfolio for this type of dechet : tapis_vide 0 NUMBER BATCH : 0 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', 'gm', 'jrm', 'ela', 'pet_clair', 'film_pedb', 'pehd_pp', 'flux_dev', 'aluminium', 'tapis_vide', 'refus', 'emr', 'gm'] We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 0 elapsed_time : count_nb_balles_and_create_portfolio 0.04727959632873535 # DISPLAY ALL COLLECTED DATA : {'18052025': {'nb_upload': 77, 'nb_taggue_class': 77, 'nb_taggue_densite': 77, 'nb_descriptors': 0, 'number_port': 0, 'count_photo_in_port': 0, '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': 0, 'nb_portfolios': 0}, '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 [1359278057, 1359254521, 1359254355, 1359252857, 1359250773, 1359249511, 1359249067, 1359247417, 1359246845, 1359242504, 1359240877, 1359239152, 1359236469, 1359223280, 1359221499, 1359217547, 1359208691, 1359203592, 1359202252, 1359200134, 1359198399, 1359194426, 1359194244, 1359189896, 1359182922, 1359181339, 1359179237, 1359177678, 1359174942, 1359172268, 1359171149, 1359170590, 1359168793, 1359166794, 1359166628, 1359166441, 1359165631, 1359160329, 1359159807, 1359159231, 1359158726, 1359157043, 1359156714, 1359155839, 1359155391, 1359155062, 1359154612, 1359154306, 1359153605, 1359153147, 1359152378, 1359151701, 1359151201, 1359147681, 1359145553, 1359144963, 1359144295, 1359143584, 1359143152, 1359142940, 1359142683, 1359142423, 1359135875, 1359135423, 1359134784, 1359132736, 1359132443, 1359132384, 1359131573, 1359129217, 1359128812, 1359128587, 1359126997, 1359126774, 1359126040, 1359125830, 1359125626] Looping around the photos to save general results len do output : 1 /23093913Didn'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 ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359278057', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359254521', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359254355', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359252857', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359250773', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359249511', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359249067', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359247417', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359246845', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359242504', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359240877', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359239152', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359236469', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359223280', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359221499', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359217547', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359208691', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359203592', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359202252', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359200134', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359198399', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359194426', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359194244', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359189896', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359182922', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359181339', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359179237', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359177678', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359174942', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359172268', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359171149', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359170590', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359168793', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359166794', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359166628', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359166441', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359165631', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359160329', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359159807', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359159231', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359158726', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359157043', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359156714', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359155839', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359155391', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359155062', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359154612', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359154306', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359153605', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359153147', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359152378', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359151701', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359151201', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359147681', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359145553', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359144963', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359144295', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359143584', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359143152', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359142940', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359142683', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359142423', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359135875', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359135423', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359134784', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359132736', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359132443', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359132384', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359131573', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359129217', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359128812', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359128587', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359126997', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359126774', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359126040', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359125830', None, None, None, None, None, '2918337') ('4891', None, None, None, None, None, None, None, '2918337') ('4891', '23093913', '1359125626', None, None, None, None, None, '2918337') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 78 time used for this insertion : 0.6331138610839844 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.21155905723571777 time spend to save output : 0.6339616775512695 total time spend for step 1 : 0.8455207347869873 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 1.61user 0.60system 0:05.20elapsed 42%CPU (0avgtext+0avgdata 99200maxresident)k 0inputs+72outputs (0major+56617minor)pagefaults 0swaps