python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 4189' -s datou_current_4189 -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 : 1451698 load datou : 4189 # 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 list_input_json: {} Current got : datou_id : 4189, datou_cur_ids : ['3771178'] with mtr_portfolio_ids : ['27176671'] and first list_photo_ids : [] new path : /proc/1451698/ 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 : 0.017624855041503906 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Wed Sep 24 12:00:28 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': 3379, 'mtr_user_id': 31, 'name': 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '5515864,5515840,5515844,5515850,6244400,6237996,6237998,5515847,5515841,5515868,5515866', 'photo_hashtag_type': 4374, 'photo_desc_type': 5680, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'}] thcls : [{'id': 3513, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2_tf', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 4557, 'photo_desc_type': 5767, 'type_classification': 'tf_classification2', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('10', 89),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 84} 24092025 27176671 Nombre de photos uploadées : 89 / 23040 (0%) 24092025 27176671 Nombre de photos taguées (types de déchets): 84 / 89 (94%) 24092025 27176671 Nombre de photos taguées (volume) : 84 / 89 (94%) elapsed_time : load_data_split_time_score 2.6226043701171875e-06 elapsed_time : order_list_meta_photo_and_scores 4.649162292480469e-05 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL????? elapsed_time : fill_and_build_computed_from_old_data 0.006348609924316406 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.4277358055114746 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL Creating list_photo_by_hashtags Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None elapsed_time : list_photo_by_hashtags 0.023238420486450195 Creating list_photo_total elapsed_time : select_descriptors 1.23826265335083 24092025 27176671 Nombre de photos avec descriptors (type 5680) : 12 / 17 (70%) ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1385837061 photo_id_prec : 0 0:00:00|ON:LMissing descriptors for photos 1385840722 and 1385840795 LMissing descriptors for photos 1385840795 and 1385840863 LMissing descriptors for photos 1385840863 and 1385844865 LMissing descriptors for photos 1385844865 and 1385844867 LMissing descriptors for photos 1385844867 and 1385844866 LMissing descriptors for photos 1385844866 and 1385844864 LMissing descriptors for photos 1385844864 and 1385844863 LMissing descriptors for photos 1385844863 and 1385844855 LMissing descriptors for photos 1385844855 and 1385848924 LMissing descriptors for photos 1385848924 and 1385849028 LMissing descriptors for photos 1385849028 and 1385849107 LMissing descriptors for photos 1385849107 and 1385849193 LMissing descriptors for photos 1385849193 and 1385849284 LMissing descriptors for photos 1385849284 and 1385849362 LMissing descriptors for photos 1385849362 and 1385853719 LMissing descriptors for photos 1385853719 and 1385854060 LMissing descriptors for photos 1385854060 and 1385853961 LMissing descriptors for photos 1385853961 and 1385853892 LMissing descriptors for photos 1385853892 and 1385853774 LMissing descriptors for photos 1385853774 and 1385853958 LMissing descriptors for photos 1385853958 and 1385859582 LMissing descriptors for photos 1385859582 and 1385859617 LMissing descriptors for photos 1385859617 and 1385859679 LMissing descriptors for photos 1385859679 and 1385859809 LMissing descriptors for photos 1385859809 and 1385859937 LMissing descriptors for photos 1385859937 and 1385860059 LMissing descriptors for photos 1385860059 and 1385862343 LMissing descriptors for photos 1385862343 and 1385862545 LMissing descriptors for photos 1385862545 and 1385862500 LMissing descriptors for photos 1385862500 and 1385862455 LMissing descriptors for photos 1385862455 and 1385862418 LMissing descriptors for photos 1385862418 and 1385862379 LMissing descriptors for photos 1385862379 and 1385866226 LMissing descriptors for photos 1385866226 and 1385866158 LMissing descriptors for photos 1385866158 and 1385866057 LMissing descriptors for photos 1385866057 and 1385865987 LMissing descriptors for photos 1385865987 and 1385866114 LMissing descriptors for photos 1385866114 and 1385865948 LMissing descriptors for photos 1385865948 and 1385869353 LMissing descriptors for photos 1385869353 and 1385869403 LMissing descriptors for photos 1385869403 and 1385869438 LMissing descriptors for photos 1385869438 and 1385869451 LMissing descriptors for photos 1385869451 and 1385869453 LMissing descriptors for photos 1385869453 and 1385869457 LMissing descriptors for photos 1385869457 and 1385872179 LMissing descriptors for photos 1385872179 and 1385872227 LMissing descriptors for photos 1385872227 and 1385872218 LMissing descriptors for photos 1385872218 and 1385872141 LMissing descriptors for photos 1385872141 and 1385872107 LMissing descriptors for photos 1385872107 and 1385872070 LMissing descriptors for photos 1385872070 and 1385873105 LMissing descriptors for photos 1385873105 and 1385873142 LMissing descriptors for photos 1385873142 and 1385873178 LMissing descriptors for photos 1385873178 and 1385873206 LMissing descriptors for photos 1385873206 and 1385873208 LMissing descriptors for photos 1385873208 and 1385873209 LMissing descriptors for photos 1385873209 and 1385873535 LMissing descriptors for photos 1385873535 and 1385873538 LMissing descriptors for photos 1385873538 and 1385873541 LMissing descriptors for photos 1385873541 and 1385873546 LMissing descriptors for photos 1385873546 and 1385873551 LMissing descriptors for photos 1385873551 and 1385873554 LMissing descriptors for photos 1385873554 and 1385874074 LMissing descriptors for photos 1385874074 and 1385874080 LMissing descriptors for photos 1385874080 and 1385874118 LMissing descriptors for photos 1385874118 and 1385874157 LMissing descriptors for photos 1385874157 and 1385874167 LLLLLMissing descriptors for photos 1385874648 and 1385874662 LMissing descriptors for photos 1385874662 and 1385874668 LMissing descriptors for photos 1385874668 and 1385874685 LMissing descriptors for photos 1385874685 and 1385875014 LMissing descriptors for photos 1385875014 and 1385875021 LMissing descriptors for photos 1385875021 and 1385875031 LMissing descriptors for photos 1385875031 and 1385875036 LMissing descriptors for photos 1385875036 and 1385875042 L 24092025 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 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 89 time used for this insertion : 0.026932239532470703 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.05838918685913086 To do, maybe not at the correct place ! ..........L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.Lforce hashtag to JRM elapsed_time : CREATE_PORT_BATCH_BY_HOUR 0.008285045623779297 NUMBER BATCH : 1 list_ponderation used : [1e-05, 1e-05, 1e-05, 1e-05, 1e-05] , list_hashtag_class_create_as_list : ['jrm'] LLLLLLLLLLLERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info Lresult_one_balle_Type_JRM:{'day': '24092025', 'map_nb_amount': {0: 0, 1: 12, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 839.4558608531952, 'nb_balles_papier': 0.00012, 'begin_time_port': 'image_24092025_10_00_02_743190m0.jpg 1e-05 for time 1, id_amount 2 this amount prod time diff : 1e-05'} Production hashtag (incorrect ponderation at 20-10-18) : 0.00012 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 1 list_same_port_ids : [] # 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 ! 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 12489 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 12499 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12500 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 12492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 12492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! WARNING : number of outputs for step 12493 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 12494 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12494 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 12502 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 12502 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 12496 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12496 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 12495 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 12495 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 2 of step 12492 doesn't seem to be define in the database( WARNING : output 1 of step 12489 have datatype=2 whereas input 1 of step 12493 have datatype=7 WARNING : type of output 2 of step 12493 doesn't seem to be define in the database( WARNING : type of input 1 of step 12494 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 12493 doesn't seem to be define in the database( WARNING : type of input 1 of step 12496 doesn't seem to be define in the database( WARNING : type of output 1 of step 12496 doesn't seem to be define in the database( WARNING : type of input 3 of step 12495 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 1 of step 12500 doesn't seem to be define in the database( WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 1 of step 12499 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 12496 have datatype=10 whereas input 3 of step 12498 have datatype=6 WARNING : type of input 5 of step 12498 doesn't seem to be define in the database( WARNING : output 0 of step 12501 have datatype=11 whereas input 5 of step 12498 have datatype=None WARNING : output 0 of step 12496 have datatype=10 whereas input 0 of step 12501 have datatype=18 WARNING : type of input 2 of step 12502 doesn't seem to be define in the database( WARNING : output 1 of step 12494 have datatype=7 whereas input 2 of step 12502 have datatype=None WARNING : type of output 3 of step 12502 doesn't seem to be define in the database( WARNING : type of input 2 of step 12496 doesn't seem to be define in the database( WARNING : type of output 1 of step 12499 doesn't seem to be define in the database( WARNING : type of input 3 of step 12492 doesn't seem to be define in the database( WARNING : type of output 1 of step 12500 doesn't seem to be define in the database( WARNING : type of input 3 of step 12492 doesn't seem to be define in the database( WARNING : output 0 of step 12493 have datatype=1 whereas input 0 of step 12494 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`=27182526 AND mptpi.`type`=3726 To do elapsed_time : count_nb_balles_and_create_portfolio 5.3460917472839355 # DISPLAY ALL COLLECTED DATA : {'24092025': {'nb_upload': 89, 'nb_taggue_class': 84, 'nb_taggue_densite': 84, 'nb_descriptors': 12}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1385875042, 1385875036, 1385875031, 1385875021, 1385875014, 1385874685, 1385874668, 1385874662, 1385874648, 1385874639, 1385874636, 1385874170, 1385874167, 1385874157, 1385874118, 1385874080, 1385874074, 1385873554, 1385873551, 1385873546, 1385873541, 1385873538, 1385873535, 1385873209, 1385873208, 1385873206, 1385873178, 1385873142, 1385873105, 1385872227, 1385872218, 1385872179, 1385872141, 1385872107, 1385872070, 1385869457, 1385869453, 1385869451, 1385869438, 1385869403, 1385869353, 1385866226, 1385866158, 1385866114, 1385866057, 1385865987, 1385865948, 1385862545, 1385862500, 1385862455, 1385862418, 1385862379, 1385862343, 1385860059, 1385859937, 1385859809, 1385859679, 1385859617, 1385859582, 1385854060, 1385853961, 1385853958, 1385853892, 1385853774, 1385853719, 1385849362, 1385849284, 1385849193, 1385849107, 1385849028, 1385848924, 1385844867, 1385844866, 1385844865, 1385844864, 1385844863, 1385844855, 1385840863, 1385840795, 1385840722, 1385840654, 1385840585, 1385840526, 1385837273, 1385837222, 1385837175, 1385837133, 1385837061, 1385836984] Looping around the photos to save general results len do output : 1 /27176671Didn'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 ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385875042', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385875036', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385875031', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385875021', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385875014', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874685', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874668', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874662', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874648', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874639', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874636', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874170', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874167', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874157', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874118', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874080', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385874074', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873554', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873551', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873546', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873541', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873538', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873535', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873209', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873208', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873206', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873178', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873142', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385873105', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872227', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872218', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872179', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872141', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872107', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385872070', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869457', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869453', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869451', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869438', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869403', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385869353', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385866226', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385866158', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385866114', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385866057', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385865987', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385865948', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862545', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862500', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862455', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862418', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862379', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385862343', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385860059', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385859937', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385859809', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385859679', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385859617', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385859582', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385854060', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385853961', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385853958', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385853892', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385853774', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385853719', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385849362', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385849284', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385849193', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385849107', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385849028', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385848924', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844867', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844866', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844865', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844864', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844863', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385844855', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840863', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840795', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840722', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840654', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840585', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385840526', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385837273', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385837222', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385837175', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385837133', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385837061', None, None, None, None, None, '3771178') ('4189', None, None, None, None, None, None, None, '3771178') ('4189', '27176671', '1385836984', None, None, None, None, None, '3771178') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 90 time used for this insertion : 0.025557518005371094 save_final save missing photos in datou_result : time spend for datou_step_exec : 7.197668552398682 time spend to save output : 0.026350021362304688 total time spend for step 1 : 7.224018573760986 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 1.64user 0.84system 0:10.04elapsed 24%CPU (0avgtext+0avgdata 101416maxresident)k 0inputs+176outputs (4major+49063minor)pagefaults 0swaps