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 : 3252590 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: {} Date 2026-04-16 14:00:28.890517 Current got : datou_id : 4189, datou_cur_ids : ['4375130'] with mtr_portfolio_ids : ['30990357'] and first list_photo_ids : [] new path : /proc/3252590/ 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 , 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 : 0.0220487117767334 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Thu Apr 16 14:00:29 2026 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', 166),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 120} 16042026 30990357 Nombre de photos uploadées : 166 / 23040 (0%) 16042026 30990357 Nombre de photos taguées (types de déchets): 120 / 166 (72%) 16042026 30990357 Nombre de photos taguées (volume) : 120 / 166 (72%) elapsed_time : load_data_split_time_score 3.814697265625e-06 elapsed_time : order_list_meta_photo_and_scores 6.818771362304688e-05 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL?????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.009663105010986328 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.2762932777404785 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL Creating list_photo_by_hashtags Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None Hashtag is None elapsed_time : list_photo_by_hashtags 0.02708888053894043 Creating list_photo_total elapsed_time : select_descriptors 6.231720685958862 16042026 30990357 Nombre de photos avec descriptors (type 5680) : 104 / 150 (69%) ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1415904812 photo_id_prec : 0 0:00:00|ON:ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 1280 vs 0 photo_id : 1415906644 photo_id_prec : 1415904852 LMissing descriptors for photos 1415906644 and 1415906688 LMissing descriptors for photos 1415906688 and 1415906827 LMissing descriptors for photos 1415906827 and 1415906828 LMissing descriptors for photos 1415906828 and 1415906829 LMissing descriptors for photos 1415906829 and 1415907011 LMissing descriptors for photos 1415907011 and 1415907310 LMissing descriptors for photos 1415907310 and 1415907311 LMissing descriptors for photos 1415907311 and 1415907312 LMissing descriptors for photos 1415907312 and 1415907314 LMissing descriptors for photos 1415907314 and 1415907316 LMissing descriptors for photos 1415907316 and 1415907317 LMissing descriptors for photos 1415907317 and 1415907329 LMissing descriptors for photos 1415907329 and 1415907330 LMissing descriptors for photos 1415907330 and 1415907331 LMissing descriptors for photos 1415907331 and 1415907332 LMissing descriptors for photos 1415907332 and 1415907333 LMissing descriptors for photos 1415907333 and 1415907334 LMissing descriptors for photos 1415907334 and 1415907345 LMissing descriptors for photos 1415907345 and 1415907347 LMissing descriptors for photos 1415907347 and 1415907348 LMissing descriptors for photos 1415907348 and 1415907349 LMissing descriptors for photos 1415907349 and 1415907350 LMissing descriptors for photos 1415907350 and 1415907351 LERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1415907355 photo_id_prec : 1415907351 LL0:06:00.064734|OFF:0:00:59.858809|ON:LL0:00:00|OFF:0:00:00|ON:ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 1280 vs 0 photo_id : 1415909187 photo_id_prec : 1415908877 LMissing descriptors for photos 1415909187 and 1415909188 LMissing descriptors for photos 1415909188 and 1415909189 LMissing descriptors for photos 1415909189 and 1415909190 LMissing descriptors for photos 1415909190 and 1415909191 LMissing descriptors for photos 1415909191 and 1415909192 LMissing descriptors for photos 1415909192 and 1415909202 LMissing descriptors for photos 1415909202 and 1415909203 LMissing descriptors for photos 1415909203 and 1415909204 LMissing descriptors for photos 1415909204 and 1415909205 LMissing descriptors for photos 1415909205 and 1415909206 LMissing descriptors for photos 1415909206 and 1415909207 LERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1415909211 photo_id_prec : 1415909207 LL0:06:59.874278|OFF:0:01:00.797362|ON:LL0:03:59.370488|OFF:0:00:59.847973|ON:LLLMissing descriptors for photos 1415913996 and 1415913997 LMissing descriptors for photos 1415913997 and 1415913998 LMissing descriptors for photos 1415913998 and 1415913999 LMissing descriptors for photos 1415913999 and 1415915616 LLLMissing descriptors for photos 1415915618 and 1415915619 LMissing descriptors for photos 1415915619 and 1415915620 LMissing descriptors for photos 1415915620 and 1415915795 LMissing descriptors for photos 1415915795 and 1415916213 LMissing descriptors for photos 1415916213 and 1415916214 LMissing descriptors for photos 1415916214 and 1415916215 LMissing descriptors for photos 1415916215 and 1415916216 LMissing descriptors for photos 1415916216 and 1415916217 LMissing descriptors for photos 1415916217 and 1415916219 LMissing descriptors for photos 1415916219 and 1415917123 LMissing descriptors for photos 1415917123 and 1415917124 LMissing descriptors for photos 1415917124 and 1415917125 LMissing descriptors for photos 1415917125 and 1415917126 LMissing descriptors for photos 1415917126 and 1415917127 LMissing descriptors for photos 1415917127 and 1415917128 LMissing descriptors for photos 1415917128 and 1415917440 LMissing descriptors for photos 1415917440 and 1415917441 LMissing descriptors for photos 1415917441 and 1415917443 LMissing descriptors for photos 1415917443 and 1415917445 L 16042026 Removing 4 photos because of the 'same image' condition Total on : 1019.3095000000001 list_time_on Total off : 180.504144 list_time_off dist_desc begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 166 time used for this insertion : 0.02913808822631836 photos_removed : len 4 elapsed_time : remove_photo_duplicate 0.06711030006408691 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.Lforce hashtag to JRM elapsed_time : CREATE_PORT_BATCH_BY_HOUR 0.010185956954956055 NUMBER BATCH : 2 list_ponderation used : [1e-05, 1e-05, 1e-05, 1e-05, 1e-05] , list_hashtag_class_create_as_list : ['jrm'] LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_JRM:{'day': '16042026', 'map_nb_amount': {0: 5, 1: 48, 2: 0, 3: 1, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 839.7978208065033, 'nb_balles_papier': 0.0005400000000000008, 'begin_time_port': 'image_16042026_10_00_02_411842m0.jpg 1e-05 for time 1, id_amount 2 this amount prod time diff : 1e-05'} Production hashtag (incorrect ponderation at 20-10-18) : 0.0005400000000000008 LLLLLLLLLLLLLLERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR 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': '16042026', 'map_nb_amount': {0: 9, 1: 35, 2: 2, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 659.7896990776062, 'nb_balles_papier': 0.00046000000000000056, 'begin_time_port': 'image_16042026_10_15_03_007025m0.jpg 1e-05 for time 1, id_amount 1 this amount prod time diff : 1e-05'} Production hashtag (incorrect ponderation at 20-10-18) : 0.00046000000000000056 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 2 list_same_port_ids : [30990864] find same portfolio which already exist 30990864 , we will use it list_same_port_ids : [] Qualite : 0.09147429322419966 # 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`=30990864 AND mptpi.`type`=3726 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 ! 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`=30991350 AND mptpi.`type`=3726 To do elapsed_time : count_nb_balles_and_create_portfolio 2.7209784984588623 # DISPLAY ALL COLLECTED DATA : {'16042026': {'nb_upload': 166, 'nb_taggue_class': 120, 'nb_taggue_densite': 120, 'nb_descriptors': 104}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1415917445, 1415917443, 1415917441, 1415917440, 1415917128, 1415917127, 1415917126, 1415917125, 1415917124, 1415917123, 1415916219, 1415916217, 1415916216, 1415916215, 1415916214, 1415916213, 1415915795, 1415915620, 1415915619, 1415915618, 1415915617, 1415915616, 1415913999, 1415913998, 1415913997, 1415913996, 1415913994, 1415913993, 1415913964, 1415913963, 1415913962, 1415913961, 1415913960, 1415913959, 1415913872, 1415913871, 1415913870, 1415913869, 1415913868, 1415913866, 1415913857, 1415913855, 1415913854, 1415913853, 1415913483, 1415913482, 1415913481, 1415913480, 1415913479, 1415913478, 1415910557, 1415910555, 1415910554, 1415910553, 1415910552, 1415910551, 1415910538, 1415910537, 1415910536, 1415910535, 1415910533, 1415910532, 1415910235, 1415910234, 1415910233, 1415910232, 1415910229, 1415910228, 1415910203, 1415910202, 1415910201, 1415910200, 1415910199, 1415910198, 1415909211, 1415909207, 1415909206, 1415909205, 1415909204, 1415909203, 1415909202, 1415909192, 1415909191, 1415909190, 1415909189, 1415909188, 1415909187, 1415908877, 1415908876, 1415908875, 1415908874, 1415908873, 1415908872, 1415908563, 1415908561, 1415908560, 1415908552, 1415908486, 1415908484, 1415907760] Looping around the photos to save general results len do output : 1 /30990357Didn'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, '4375130') ('4189', '30990357', '1415917445', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917443', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917441', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917440', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917128', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917127', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917126', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917125', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917124', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415917123', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916219', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916217', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916216', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916215', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916214', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415916213', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915795', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915620', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915619', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915618', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915617', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415915616', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913999', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913998', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913997', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913996', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913994', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913993', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913964', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913963', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913962', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913961', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913960', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913959', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913872', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913871', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913870', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913869', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913868', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913866', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913857', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913855', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913854', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913853', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913483', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913482', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913481', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913480', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913479', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415913478', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910557', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910555', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910554', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910553', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910552', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910551', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910538', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910537', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910536', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910535', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910533', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910532', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910235', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910234', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910233', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910232', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910229', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910228', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910203', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910202', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910201', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910200', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910199', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415910198', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909211', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909207', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909206', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909205', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909204', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909203', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909202', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909192', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909191', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909190', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909189', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909188', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415909187', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908877', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908876', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908875', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908874', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908873', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908872', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908563', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908561', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908560', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908552', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908486', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415908484', None, None, None, None, None, '4375130') ('4189', None, None, None, None, None, None, None, '4375130') ('4189', '30990357', '1415907760', None, None, None, None, None, '4375130') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 101 time used for this insertion : 0.026680707931518555 save_final save missing photos in datou_result : time spend for datou_step_exec : 9.444742918014526 time spend to save output : 0.027402877807617188 total time spend for step 1 : 9.472145795822144 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 2.00user 0.62system 0:13.33elapsed 19%CPU (0avgtext+0avgdata 113084maxresident)k 184inputs+912outputs (1major+53083minor)pagefaults 0swaps