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 : 2089446 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 no input labels no input values updating current state to 1 list_input_json: {} Current got : datou_id : 4891, datou_cur_ids : ['4342645'] with mtr_portfolio_ids : ['30360684'] and first list_photo_ids : [] new path : /proc/2089446/ 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 : 0.02352595329284668 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Wed Feb 11 08:30:29 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': 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', 8), ('02', 5), ('03', 9), ('04', 6), ('05', 10), ('06', 8), ('07', 4), ('08', 4)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 59} 11022026 30360684 Nombre de photos uploadées : 60 / 23040 (0%) 11022026 30360684 Nombre de photos taguées (types de déchets): 59 / 60 (98%) 11022026 30360684 Nombre de photos taguées (volume) : 59 / 60 (98%) elapsed_time : load_data_split_time_score 1.6689300537109375e-06 elapsed_time : order_list_meta_photo_and_scores 2.956390380859375e-05 ? elapsed_time : fill_and_build_computed_from_old_data 0.004345893859863281 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.24282383918762207 Creating list_photo_total elapsed_time : select_descriptors 0.8641831874847412 11022026 30360684 Nombre de photos avec descriptors (type 6092) : 8 / 9 (88%) Missing descriptors for photos 0 and 1407523708 0:00:00|ON:Missing descriptors for photos 1407523708 and 1407525362 Missing descriptors for photos 1407525362 and 1407526107 Missing descriptors for photos 1407526107 and 1407526941 Missing descriptors for photos 1407526941 and 1407528746 Missing descriptors for photos 1407528746 and 1407531006 Missing descriptors for photos 1407531006 and 1407531238 Missing descriptors for photos 1407531238 and 1407532210 Missing descriptors for photos 1407532210 and 1407533243 Missing descriptors for photos 1407533243 and 1407533246 Missing descriptors for photos 1407533246 and 1407533249 Missing descriptors for photos 1407533249 and 1407533250 Missing descriptors for photos 1407533250 and 1407533253 Missing descriptors for photos 1407533253 and 1407533254 Missing descriptors for photos 1407533254 and 1407533879 Missing descriptors for photos 1407533879 and 1407535043 Missing descriptors for photos 1407535043 and 1407535046 Missing descriptors for photos 1407535046 and 1407535049 Missing descriptors for photos 1407535049 and 1407535745 Missing descriptors for photos 1407535745 and 1407538243 Missing descriptors for photos 1407538243 and 1407538244 Missing descriptors for photos 1407538244 and 1407538247 Missing descriptors for photos 1407538247 and 1407538248 Missing descriptors for photos 1407538248 and 1407538249 Missing descriptors for photos 1407538249 and 1407538252 Missing descriptors for photos 1407538252 and 1407538253 Missing descriptors for photos 1407538253 and 1407538256 Missing descriptors for photos 1407538256 and 1407538257 Missing descriptors for photos 1407538257 and 1407539892 Missing descriptors for photos 1407539892 and 1407540199 Missing descriptors for photos 1407540199 and 1407540321 Missing descriptors for photos 1407540321 and 1407540353 Missing descriptors for photos 1407540353 and 1407541167 Missing descriptors for photos 1407541167 and 1407541210 Missing descriptors for photos 1407541210 and 1407543559 Missing descriptors for photos 1407543559 and 1407543601 Missing descriptors for photos 1407543601 and 1407543629 Missing descriptors for photos 1407543629 and 1407543858 Missing descriptors for photos 1407543858 and 1407543869 Missing descriptors for photos 1407543869 and 1407543880 Missing descriptors for photos 1407545476 and 1407545493 Missing descriptors for photos 1407545493 and 1407545503 Missing descriptors for photos 1407545544 and 1407545553 Missing descriptors for photos 1407545553 and 1407545563 Missing descriptors for photos 1407548564 and 1407550218 Missing descriptors for photos 1407550218 and 1407550230 Missing descriptors for photos 1407550230 and 1407550249 11022026 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 : 60 time used for this insertion : 0.07468104362487793 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.15661025047302246 Creating list_photo_total Warning list_scores null time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average time_diff is bigger than the limit of interval, we ignore the result of this image in moving average ERROR ! elapsed_time : count_sum_diff_and_build_graph 0.002853870391845703 Total photos : 60 .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 .Change port : 0 hashtag : 495916461 photo_id =1407543890 : jrm .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info .Change port : 3 hashtag : 493546845 photo_id =1407545511 : aluminium .Change port : 1 hashtag : 495916461 photo_id =1407545534 : jrm .can't find max_score_info .can't find max_score_info .can't find max_score_info .Change port : 1 hashtag : 492741797 photo_id =1407547881 : ela .Change port : 1 hashtag : 495916461 photo_id =1407548132 : jrm .can't find max_score_info .Change port : 1 hashtag : 493546845 photo_id =1407548167 : aluminium .can't find max_score_info .can't find max_score_info .can't find max_score_info Total photos : 60 Number of lists : 7 counter photos in port : 8 hashtag : aluminium(493546845) : 2 photos in 2 portfolios ! hashtag : ela(492741797) : 1 photos in 1 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) : 5 photos in 3 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 1 portfolios ! elapsed_time : group_photo_by_moyenne_exp 0.0030984878540039062 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 2.384185791015625e-06 today str has not a value , we define it as the date of the first image todaystr_first : 11022026 attention , prev_timestamp is 0 , we do nothing **********************************************************Unexpected type of data : ({'photo_id': 1407550249, 'url': 'https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/2026/2/11/1a0b807968202b138d0444a0501786ef.jpg', 'username': None, 'uploaded_at': 1770794962, 'text': 'image_11022026_08_28_15_5317.jpg', 'time': 1770798495.005317}, 'different') Count Time bigger than 30s : 58 #Number Photos for regression : {'11022026': {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}}} 11022026|aluminium, 05102018_papier_non_papier_dense:0 11022026|aluminium, 05102018_papier_non_papier_peu_dense:0 11022026|aluminium, 05102018_papier_non_papier_presque_vide:0 11022026|aluminium, 05102018_papier_non_papier_tres_dense:0 11022026|aluminium, 05102018_papier_non_papier_tres_peu_dense:0 11022026|ela, 05102018_papier_non_papier_dense:0 11022026|ela, 05102018_papier_non_papier_peu_dense:0 11022026|ela, 05102018_papier_non_papier_presque_vide:0 11022026|ela, 05102018_papier_non_papier_tres_dense:0 11022026|ela, 05102018_papier_non_papier_tres_peu_dense:0 11022026|emr, 05102018_papier_non_papier_dense:0 11022026|emr, 05102018_papier_non_papier_peu_dense:0 11022026|emr, 05102018_papier_non_papier_presque_vide:0 11022026|emr, 05102018_papier_non_papier_tres_dense:0 11022026|emr, 05102018_papier_non_papier_tres_peu_dense:0 11022026|film_pedb, 05102018_papier_non_papier_dense:0 11022026|film_pedb, 05102018_papier_non_papier_peu_dense:0 11022026|film_pedb, 05102018_papier_non_papier_presque_vide:0 11022026|film_pedb, 05102018_papier_non_papier_tres_dense:0 11022026|film_pedb, 05102018_papier_non_papier_tres_peu_dense:0 11022026|flux_dev, 05102018_papier_non_papier_dense:0 11022026|flux_dev, 05102018_papier_non_papier_peu_dense:0 11022026|flux_dev, 05102018_papier_non_papier_presque_vide:0 11022026|flux_dev, 05102018_papier_non_papier_tres_dense:0 11022026|flux_dev, 05102018_papier_non_papier_tres_peu_dense:0 11022026|jrm, 05102018_papier_non_papier_dense:0 11022026|jrm, 05102018_papier_non_papier_peu_dense:0 11022026|jrm, 05102018_papier_non_papier_presque_vide:0 11022026|jrm, 05102018_papier_non_papier_tres_dense:0 11022026|jrm, 05102018_papier_non_papier_tres_peu_dense:0 11022026|pcm, 05102018_papier_non_papier_dense:0 11022026|pcm, 05102018_papier_non_papier_peu_dense:0 11022026|pcm, 05102018_papier_non_papier_presque_vide:0 11022026|pcm, 05102018_papier_non_papier_tres_dense:0 11022026|pcm, 05102018_papier_non_papier_tres_peu_dense:0 11022026|pcnc, 05102018_papier_non_papier_dense:0 11022026|pcnc, 05102018_papier_non_papier_peu_dense:0 11022026|pcnc, 05102018_papier_non_papier_presque_vide:0 11022026|pcnc, 05102018_papier_non_papier_tres_dense:0 11022026|pcnc, 05102018_papier_non_papier_tres_peu_dense:0 11022026|pehd_pp, 05102018_papier_non_papier_dense:0 11022026|pehd_pp, 05102018_papier_non_papier_peu_dense:0 11022026|pehd_pp, 05102018_papier_non_papier_presque_vide:0 11022026|pehd_pp, 05102018_papier_non_papier_tres_dense:0 11022026|pehd_pp, 05102018_papier_non_papier_tres_peu_dense:0 11022026|pet_clair, 05102018_papier_non_papier_dense:0 11022026|pet_clair, 05102018_papier_non_papier_peu_dense:0 11022026|pet_clair, 05102018_papier_non_papier_presque_vide:0 11022026|pet_clair, 05102018_papier_non_papier_tres_dense:0 11022026|pet_clair, 05102018_papier_non_papier_tres_peu_dense:0 11022026|refus, 05102018_papier_non_papier_dense:0 11022026|refus, 05102018_papier_non_papier_peu_dense:0 11022026|refus, 05102018_papier_non_papier_presque_vide:0 11022026|refus, 05102018_papier_non_papier_tres_dense:0 11022026|refus, 05102018_papier_non_papier_tres_peu_dense:0 11022026|tapis_vide, 05102018_papier_non_papier_dense:0 11022026|tapis_vide, 05102018_papier_non_papier_peu_dense:0 11022026|tapis_vide, 05102018_papier_non_papier_presque_vide:0 11022026|tapis_vide, 05102018_papier_non_papier_tres_dense:0 11022026|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 : 7 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 8 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 0 elapsed_time : count_nb_balles_and_create_portfolio 0.07224416732788086 # DISPLAY ALL COLLECTED DATA : {'11022026': {'nb_upload': 60, 'nb_taggue_class': 59, 'nb_taggue_densite': 59, 'nb_descriptors': 8, 'number_port': 7, 'count_photo_in_port': 8, 'nb_port_per_class': {'aluminium': {'nb_photos': 2, 'nb_portfolios': 2}, 'ela': {'nb_photos': 1, 'nb_portfolios': 1}, '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': 5, 'nb_portfolios': 3}, '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': 1}}}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1407550249, 1407550230, 1407550218, 1407548564, 1407548167, 1407548157, 1407548132, 1407547881, 1407545563, 1407545553, 1407545544, 1407545534, 1407545511, 1407545503, 1407545493, 1407545476, 1407543916, 1407543910, 1407543902, 1407543890, 1407543880, 1407543869, 1407543858, 1407543629, 1407543601, 1407543559, 1407541210, 1407541167, 1407540353, 1407540321, 1407540199, 1407539892, 1407538257, 1407538256, 1407538253, 1407538252, 1407538249, 1407538248, 1407538247, 1407538244, 1407538243, 1407535745, 1407535049, 1407535046, 1407535043, 1407533879, 1407533254, 1407533253, 1407533250, 1407533249, 1407533246, 1407533243, 1407532210, 1407531238, 1407531006, 1407528746, 1407526941, 1407526107, 1407525362, 1407523708] Looping around the photos to save general results len do output : 1 /30360684Didn'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, '4342645') ('4891', '30360684', '1407550249', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407550230', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407550218', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407548564', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407548167', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407548157', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407548132', None, None, None, None, None, '4342645') ('4891', None, 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None, '4342645') ('4891', '30360684', '1407545493', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407545476', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543916', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543910', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543902', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543890', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543880', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543869', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543858', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543629', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543601', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407543559', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407541210', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407541167', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407540353', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407540321', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407540199', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407539892', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538257', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538256', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538253', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538252', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538249', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538248', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538247', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538244', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407538243', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407535745', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407535049', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407535046', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407535043', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533879', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533254', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533253', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533250', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533249', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533246', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407533243', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407532210', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407531238', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407531006', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407528746', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407526941', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407526107', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407525362', None, None, None, None, None, '4342645') ('4891', None, None, None, None, None, None, None, '4342645') ('4891', '30360684', '1407523708', None, None, None, None, None, '4342645') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 61 time used for this insertion : 0.036963462829589844 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.4597558975219727 time spend to save output : 0.03749585151672363 total time spend for step 1 : 1.4972517490386963 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 1.29user 0.76system 0:05.23elapsed 39%CPU (0avgtext+0avgdata 109156maxresident)k 288inputs+136outputs (41major+52394minor)pagefaults 0swaps