python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 8 -a ' --fifo -a 533 -l 100 ' -s datou_current_533 -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 : 2576548 load datou : 533 # 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 ! 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 ! 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 ! DataTypes for each output/input checked ! 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 : chemin de la photo was removed should we ? [ (photo_id, hashtag_id_0, score_0), (photo_id, hashtag_id_1, score_1), ...] was removed should we ? [ (photo_id, hashtag_id_0, score_0), (photo_id, hashtag_id_1, score_1), ...] was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? load thcls load pdts Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec no input labels no input values updating current state to 1 we have a portfolio with more photos than limit : 3036>100 please execute split_portfolio.py -i 26046584 -l 100 size over we load limit photo not treated list_input_json: {} Current got : datou_id : 533, datou_cur_ids : ['3551871'] with mtr_portfolio_ids : ['26046584'] and first list_photo_ids : [] new path : /proc/2576548/ 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) 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 ! 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 ! DataTypes for each output/input checked ! List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : {} origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 57 ; length of list_pids : 57 ; length of list_args : 57 time to download the photos : 9.609082698822021 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 2 step1:tfhub_classification2 Tue Aug 19 13:04:37 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 Beginning of datou_step TFHub with tf2 ! nombre de thcls : 3 we are using the classfication for multi_thcl [3513, 3379, 3847] begin to check gpu status inside check gpu memory 2025-08-19 13:04:40.260073: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-08-19 13:04:40.309813: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-08-19 13:04:40.310155: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 13:04:40.312283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 13:04:40.314436: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-19 13:04:40.314763: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-19 13:04:40.317114: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-19 13:04:40.318206: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-19 13:04:40.322693: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-19 13:04:40.324206: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-19 13:04:40.324740: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-08-19 13:04:40.352546: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-08-19 13:04:40.355039: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f801c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-08-19 13:04:40.355090: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-08-19 13:04:40.484799: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x59635b0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-08-19 13:04:40.484860: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-08-19 13:04:40.486504: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-08-19 13:04:40.486640: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 13:04:40.486677: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 13:04:40.486711: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-19 13:04:40.486743: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-19 13:04:40.486777: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-19 13:04:40.486809: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-19 13:04:40.486842: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-19 13:04:40.489113: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-19 13:04:40.489191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 13:04:40.490507: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-08-19 13:04:40.490532: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-08-19 13:04:40.490547: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-08-19 13:04:40.492891: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3096 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) l 3637 free memory gpu now : 10617 max_wait_temp : 1 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3513 To do loadFromThcl(), then load ParamDescType : thcl3513 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'}] thcl {'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'} Update svm_hashtag_type_desc : 5767 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5767, 'Rungis_amount_dechets_fall_2018_v2_tf', 2048, 2048, 'Rungis_amount_dechets_fall_2018_v2_tf', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 3, 16, 15, 52, 10), datetime.datetime(2023, 3, 16, 15, 52, 10)) model_name : Rungis_amount_dechets_fall_2018_v2_tf model_param file didn't exist model_name : Rungis_amount_dechets_fall_2018_v2_tf model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_05102018_Papier_non_papier_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_05102018_Papier_non_papier_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Confusion_Matrix.png size_local : 67810 size in s3 : 67810 create time local : 2023-10-30 16:21:37 create time in s3 : 2023-10-30 14:09:29 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_dense.jpg size_local : 73949 size in s3 : 73949 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:30 Precision_Recall_05102018_Papier_non_papier_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg size_local : 85572 size in s3 : 85572 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:39 Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg size_local : 72361 size in s3 : 72361 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:37 Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg size_local : 83567 size in s3 : 83567 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:48 Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg size_local : 71611 size in s3 : 71611 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:29 Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Result_Summary.txt size_local : 1058 size in s3 : 1058 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:30 Result_Summary.txt already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:36 checkpoint already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00000-of-00001 size_local : 188538519 size in s3 : 188538519 create time local : 2023-10-30 16:21:41 create time in s3 : 2023-10-30 14:09:40 model_checkpoint.ckpt.data-00000-of-00001 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216572 size in s3 : 216572 create time local : 2023-10-30 16:21:41 create time in s3 : 2023-03-16 14:52:09 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279708 size in s3 : 32279708 create time local : 2023-10-30 16:21:42 create time in s3 : 2023-03-16 14:52:07 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.index size_local : 28001 size in s3 : 28001 create time local : 2023-10-30 16:21:42 create time in s3 : 2023-10-30 14:09:30 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_weights.h5 size_local : 94501976 size in s3 : 94501976 create time local : 2023-10-30 16:21:44 create time in s3 : 2023-10-30 14:09:37 model_weights.h5 already exist and didn't need to update desc size : 2048 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 2048) 23561152 _________________________________________________________________ Rungis_amount_dechets_fall_2 (None, 5) 10245 ================================================================= Total params: 23,571,397 Trainable params: 10,245 Non-trainable params: 23,561,152 _________________________________________________________________ Loading Weights... time used to create the model : 7.526554107666016 time used to load_weights : 0.14552974700927734 0it [00:00, ?it/s] 57it [00:00, 889.89it/s]2025-08-19 13:04:50.105129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 13:04:50.360866: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 temp/1755601467_2576548_1377879447_bc50d4771bc81a534bc797fef1e660cb.jpg temp/1755601467_2576548_1377879438_0cd19f46bc4074220460042398100e17.jpg temp/1755601467_2576548_1377879436_3673d17f281daebd5b1dc014f601f7cc.jpg temp/1755601467_2576548_1377879435_cc36343e3f177b10d9db86023a27b5a6.jpg temp/1755601467_2576548_1377879434_4bbba7f905fd0923f0843e9cea0cb493.jpg temp/1755601467_2576548_1377879427_74780ca066fb9780ce4f02aeb876e3c4.jpg 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temp/1755601467_2576548_1377877640_fcc5216414761a730de570471bfeb0b5.jpg temp/1755601467_2576548_1377877544_904f001a5fcb1147acdcd9917965108a.jpg temp/1755601467_2576548_1377877516_cfee506125657a95bd44070e30f5d8d3.jpg temp/1755601467_2576548_1377877166_0aeccdde04d79bcee5f4e834c9cefe60.jpg temp/1755601467_2576548_1377877157_34c85c1250a81ade50d7b402eff0cd13.jpg temp/1755601467_2576548_1377877121_d524090a0900a38a1fe9eaae220ecb62.jpg temp/1755601467_2576548_1377877118_f0374692cb35be0772d749e1e613c3f4.jpg temp/1755601467_2576548_1377877115_75913dfdf11e0a1de62a564f856644b5.jpg temp/1755601467_2576548_1377877090_3d05025c034867373f739636b8d29198.jpg temp/1755601467_2576548_1377877074_5bd77d8ed1d76ea58e7f8751dafaf43c.jpg temp/1755601467_2576548_1377877072_b5de5aa9f44e65a74e726171a0bd647e.jpg temp/1755601467_2576548_1377877023_c4bb856e3a803b8f30d5579b9957f975.jpg temp/1755601467_2576548_1377877011_af73eea6eddf71fdb138080342b5608d.jpg temp/1755601467_2576548_1377877007_dd05b4c6d6cc71703409f5a6b4049a76.jpg temp/1755601467_2576548_1377877004_14e51c58d779bc2b232bc769b22a1e5e.jpg temp/1755601467_2576548_1377876979_4faa4505ea74815005ed91302a76cca4.jpg temp/1755601467_2576548_1377876923_7dbaa604197b0807fc46fe4167d8fd70.jpg temp/1755601467_2576548_1377876920_7af3ec7931c48ac1a0f03c6a99f20b32.jpg temp/1755601467_2576548_1377876918_1a892ec642acbbfd380815e170ec2622.jpg temp/1755601467_2576548_1377876916_0700ad65a38cfa534bb9386ce2a32f71.jpg temp/1755601467_2576548_1377876912_99297aee9891e83f9092be4a75912222.jpg temp/1755601467_2576548_1377876910_f83c5f94b492aa6a0a433f019e2ca186.jpg temp/1755601467_2576548_1377876908_821e58e3c5ec70e06bc98a2e44c6cd19.jpg temp/1755601467_2576548_1377876900_d2d07e61949c8e9b15c140b1498a91d5.jpg temp/1755601467_2576548_1377876819_56455c3c8a49988ab3589665d8631ce5.jpg temp/1755601467_2576548_1377876805_97718ed688f5422a43ad46e713f19317.jpg temp/1755601467_2576548_1377876516_c01f0fd68e09d75dcebd8fe88348dba4.jpg temp/1755601467_2576548_1377876508_ff627b024ca940a00e87844a96633488.jpg temp/1755601467_2576548_1377876499_328551180049c094ae34e2bc4445dc85.jpg temp/1755601467_2576548_1377876496_fd547b0347bae7dca12b413905ea32e0.jpg temp/1755601467_2576548_1377876493_76497c2e9592faa1a9c5aa827074efc0.jpg temp/1755601467_2576548_1377876477_45d028601b37618de90da59d913a6ba2.jpg temp/1755601467_2576548_1377876476_29ff173ff30d3be7780128c4698ff72b.jpg temp/1755601467_2576548_1377876474_01346c435a672102b2d94ac0f85f0424.jpg temp/1755601467_2576548_1377876464_8ccee62a9ba83e359f0f76adcca63e77.jpg temp/1755601467_2576548_1377876463_ec52b54576d0bf60b6f1a65c8cf035d0.jpg temp/1755601467_2576548_1377876461_5c4e11629da633f507fc3764407c03b2.jpg temp/1755601467_2576548_1377876454_4fda3be10dca9e0db2a0284a69986090.jpg Found 57 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 6.1458916664123535 (57,) (57, 5) (57, 2048) shape of features : (57, 2048) shape of new features : (1, 57, 2048) save descriptor for thcl : 3513 time to traite the descriptors : 0.32056665420532227 storage_type for insertDescriptorsMulti : 3 To insert : 1377879447 To insert : 1377879438 To insert : 1377879436 To insert : 1377879435 To insert : 1377879434 To insert : 1377879427 To insert : 1377879419 To insert : 1377879409 To insert : 1377879406 To insert : 1377879405 To insert : 1377879404 To insert : 1377879397 To insert : 1377879395 To insert : 1377879393 To insert : 1377879389 To insert : 1377879380 To insert : 1377877724 To insert : 1377877660 To insert : 1377877641 To insert : 1377877640 To insert : 1377877544 To insert : 1377877516 To insert : 1377877166 To insert : 1377877157 To insert : 1377877121 To insert : 1377877118 To insert : 1377877115 To insert : 1377877090 To insert : 1377877074 To insert : 1377877072 To insert : 1377877023 To insert : 1377877011 To insert : 1377877007 To insert : 1377877004 To insert : 1377876979 To insert : 1377876923 To insert : 1377876920 To insert : 1377876918 To insert : 1377876916 To insert : 1377876912 To insert : 1377876910 To insert : 1377876908 To insert : 1377876900 To insert : 1377876819 To insert : 1377876805 To insert : 1377876516 To insert : 1377876508 To insert : 1377876499 To insert : 1377876496 To insert : 1377876493 To insert : 1377876477 To insert : 1377876476 To insert : 1377876474 To insert : 1377876464 To insert : 1377876463 To insert : 1377876461 To insert : 1377876454 time to insert the descriptors : 13.415279865264893 tagging for thcl : 3379 To do loadFromThcl(), then load ParamDescType : thcl3379 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'}] thcl {'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'} Update svm_hashtag_type_desc : 5680 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5680, 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 1280, 1280, 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 4, 1, 31, 10), datetime.datetime(2022, 6, 4, 1, 31, 10)) model_name : learn_classif_flux_maj_generique_effnet_v2_s_02062022 model_param file didn't exist model_name : learn_classif_flux_maj_generique_effnet_v2_s_02062022 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022 /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Confusion_Matrix.png size_local : 82527 size in s3 : 82527 create time local : 2022-06-06 13:01:24 create time in s3 : 2022-06-03 23:31:09 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_aluminium.jpg size_local : 67602 size in s3 : 67602 create time local : 2022-06-06 13:01:24 create time in s3 : 2022-06-03 23:23:41 Precision_Recall_aluminium.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_ela.jpg size_local : 67189 size in s3 : 67189 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:26:13 Precision_Recall_ela.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_film_pedb.jpg size_local : 71280 size in s3 : 71280 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:26:14 Precision_Recall_film_pedb.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_flux_dev.jpg size_local : 59936 size in s3 : 59936 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:23:41 Precision_Recall_flux_dev.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_jrm.jpg size_local : 67657 size in s3 : 67657 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:31:06 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pcm.jpg size_local : 83042 size in s3 : 83042 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:23:40 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pcnc.jpg size_local : 69972 size in s3 : 69972 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:05 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pehd_pp.jpg size_local : 67313 size in s3 : 67313 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:45 Precision_Recall_pehd_pp.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pet_clair.jpg size_local : 67320 size in s3 : 67320 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:04 Precision_Recall_pet_clair.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_refus.jpg size_local : 59936 size in s3 : 59936 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:08 Precision_Recall_refus.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_tapis_vide.jpg size_local : 80244 size in s3 : 80244 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:45 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Result_Summary.txt size_local : 1018 size in s3 : 1018 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:08 Result_Summary.txt already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/checkpoint size_local : 99 size in s3 : 99 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:06 checkpoint already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216640 size in s3 : 216640 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:43 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32341196 size in s3 : 32341196 create time local : 2022-06-06 13:01:28 create time in s3 : 2022-06-03 23:26:15 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2022-06-06 13:01:28 create time in s3 : 2022-06-03 23:26:13 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_weights.h5 size_local : 16531224 size in s3 : 16531224 create time local : 2022-06-06 13:01:29 create time in s3 : 2022-06-03 23:23:46 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ learn_classif_flux_maj_gener (None, 11) 14091 ================================================================= Total params: 4,063,655 Trainable params: 14,091 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 7.354351758956909 time used to load_weights : 0.11366057395935059 0it [00:00, ?it/s] 57it [00:00, 877.79it/s]temp/1755601467_2576548_1377879447_bc50d4771bc81a534bc797fef1e660cb.jpg temp/1755601467_2576548_1377879438_0cd19f46bc4074220460042398100e17.jpg temp/1755601467_2576548_1377879436_3673d17f281daebd5b1dc014f601f7cc.jpg temp/1755601467_2576548_1377879435_cc36343e3f177b10d9db86023a27b5a6.jpg temp/1755601467_2576548_1377879434_4bbba7f905fd0923f0843e9cea0cb493.jpg temp/1755601467_2576548_1377879427_74780ca066fb9780ce4f02aeb876e3c4.jpg temp/1755601467_2576548_1377879419_cae077f5122f88751e47873bdf152401.jpg temp/1755601467_2576548_1377879409_467e8b11e06232b0126b63bfe0ef3399.jpg temp/1755601467_2576548_1377879406_31c3f384c04e88dceb6d12e6fd5ea297.jpg temp/1755601467_2576548_1377879405_c82d89285e4ce99673a89fc25fad0c79.jpg temp/1755601467_2576548_1377879404_2346eeb6e9aedba1f62a370565991543.jpg temp/1755601467_2576548_1377879397_798ac8efae283ad3e443d9b0e7684130.jpg temp/1755601467_2576548_1377879395_bae044741b1247542a77fe1920fad667.jpg temp/1755601467_2576548_1377879393_629e6d89ab5197ca998210a9623c3c66.jpg temp/1755601467_2576548_1377879389_6465dc629b3585ef0ca901638ef42597.jpg temp/1755601467_2576548_1377879380_1f6bf5698ce1f075b91d021b0c96092c.jpg temp/1755601467_2576548_1377877724_4fdd207d4012ebe1e1e9cb0eb6b5cb89.jpg temp/1755601467_2576548_1377877660_920b3eee08cfa1dec4000c56370d3f19.jpg temp/1755601467_2576548_1377877641_453fc67dae820a82d52d550fc0f51e24.jpg temp/1755601467_2576548_1377877640_fcc5216414761a730de570471bfeb0b5.jpg temp/1755601467_2576548_1377877544_904f001a5fcb1147acdcd9917965108a.jpg temp/1755601467_2576548_1377877516_cfee506125657a95bd44070e30f5d8d3.jpg temp/1755601467_2576548_1377877166_0aeccdde04d79bcee5f4e834c9cefe60.jpg temp/1755601467_2576548_1377877157_34c85c1250a81ade50d7b402eff0cd13.jpg temp/1755601467_2576548_1377877121_d524090a0900a38a1fe9eaae220ecb62.jpg temp/1755601467_2576548_1377877118_f0374692cb35be0772d749e1e613c3f4.jpg temp/1755601467_2576548_1377877115_75913dfdf11e0a1de62a564f856644b5.jpg temp/1755601467_2576548_1377877090_3d05025c034867373f739636b8d29198.jpg temp/1755601467_2576548_1377877074_5bd77d8ed1d76ea58e7f8751dafaf43c.jpg temp/1755601467_2576548_1377877072_b5de5aa9f44e65a74e726171a0bd647e.jpg temp/1755601467_2576548_1377877023_c4bb856e3a803b8f30d5579b9957f975.jpg temp/1755601467_2576548_1377877011_af73eea6eddf71fdb138080342b5608d.jpg temp/1755601467_2576548_1377877007_dd05b4c6d6cc71703409f5a6b4049a76.jpg temp/1755601467_2576548_1377877004_14e51c58d779bc2b232bc769b22a1e5e.jpg temp/1755601467_2576548_1377876979_4faa4505ea74815005ed91302a76cca4.jpg temp/1755601467_2576548_1377876923_7dbaa604197b0807fc46fe4167d8fd70.jpg temp/1755601467_2576548_1377876920_7af3ec7931c48ac1a0f03c6a99f20b32.jpg temp/1755601467_2576548_1377876918_1a892ec642acbbfd380815e170ec2622.jpg temp/1755601467_2576548_1377876916_0700ad65a38cfa534bb9386ce2a32f71.jpg temp/1755601467_2576548_1377876912_99297aee9891e83f9092be4a75912222.jpg temp/1755601467_2576548_1377876910_f83c5f94b492aa6a0a433f019e2ca186.jpg temp/1755601467_2576548_1377876908_821e58e3c5ec70e06bc98a2e44c6cd19.jpg temp/1755601467_2576548_1377876900_d2d07e61949c8e9b15c140b1498a91d5.jpg temp/1755601467_2576548_1377876819_56455c3c8a49988ab3589665d8631ce5.jpg temp/1755601467_2576548_1377876805_97718ed688f5422a43ad46e713f19317.jpg temp/1755601467_2576548_1377876516_c01f0fd68e09d75dcebd8fe88348dba4.jpg temp/1755601467_2576548_1377876508_ff627b024ca940a00e87844a96633488.jpg temp/1755601467_2576548_1377876499_328551180049c094ae34e2bc4445dc85.jpg temp/1755601467_2576548_1377876496_fd547b0347bae7dca12b413905ea32e0.jpg temp/1755601467_2576548_1377876493_76497c2e9592faa1a9c5aa827074efc0.jpg temp/1755601467_2576548_1377876477_45d028601b37618de90da59d913a6ba2.jpg temp/1755601467_2576548_1377876476_29ff173ff30d3be7780128c4698ff72b.jpg temp/1755601467_2576548_1377876474_01346c435a672102b2d94ac0f85f0424.jpg temp/1755601467_2576548_1377876464_8ccee62a9ba83e359f0f76adcca63e77.jpg temp/1755601467_2576548_1377876463_ec52b54576d0bf60b6f1a65c8cf035d0.jpg temp/1755601467_2576548_1377876461_5c4e11629da633f507fc3764407c03b2.jpg temp/1755601467_2576548_1377876454_4fda3be10dca9e0db2a0284a69986090.jpg Found 57 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 4.8734235763549805 (57,) (57, 11) (57, 1280) shape of features : (57, 1280) shape of new features : (1, 57, 1280) save descriptor for thcl : 3379 time to traite the descriptors : 0.22259759902954102 storage_type for insertDescriptorsMulti : 3 To insert : 1377879447 To insert : 1377879438 To insert : 1377879436 To insert : 1377879435 To insert : 1377879434 To insert : 1377879427 To insert : 1377879419 To insert : 1377879409 To insert : 1377879406 To insert : 1377879405 To insert : 1377879404 To insert : 1377879397 To insert : 1377879395 To insert : 1377879393 To insert : 1377879389 To insert : 1377879380 To insert : 1377877724 To insert : 1377877660 To insert : 1377877641 To insert : 1377877640 To insert : 1377877544 To insert : 1377877516 To insert : 1377877166 To insert : 1377877157 To insert : 1377877121 To insert : 1377877118 To insert : 1377877115 To insert : 1377877090 To insert : 1377877074 To insert : 1377877072 To insert : 1377877023 To insert : 1377877011 To insert : 1377877007 To insert : 1377877004 To insert : 1377876979 To insert : 1377876923 To insert : 1377876920 To insert : 1377876918 To insert : 1377876916 To insert : 1377876912 To insert : 1377876910 To insert : 1377876908 To insert : 1377876900 To insert : 1377876819 To insert : 1377876805 To insert : 1377876516 To insert : 1377876508 To insert : 1377876499 To insert : 1377876496 To insert : 1377876493 To insert : 1377876477 To insert : 1377876476 To insert : 1377876474 To insert : 1377876464 To insert : 1377876463 To insert : 1377876461 To insert : 1377876454 time to insert the descriptors : 11.592253684997559 tagging for thcl : 3847 To do loadFromThcl(), then load ParamDescType : thcl3847 thcls : [{'id': 3847, 'mtr_user_id': 31, 'name': 'learn_MM_generique_050224', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,emr,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '13096157,13096155,13096163,13096159,13301956,13095886,13096162,13096160,13358264,13096158,5515868,13276803', 'photo_hashtag_type': 4932, 'photo_desc_type': 6032, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,616987804,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'}] thcl {'id': 3847, 'mtr_user_id': 31, 'name': 'learn_MM_generique_050224', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,emr,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '13096157,13096155,13096163,13096159,13301956,13095886,13096162,13096160,13358264,13096158,5515868,13276803', 'photo_hashtag_type': 4932, 'photo_desc_type': 6032, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,616987804,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'} Update svm_hashtag_type_desc : 6032 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (6032, 'learn_MM_generique_050224', 1280, 1280, 'learn_MM_generique_050224', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2024, 2, 5, 21, 42, 4), datetime.datetime(2024, 2, 5, 21, 42, 4)) model_name : learn_MM_generique_050224 model_param file didn't exist model_name : learn_MM_generique_050224 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_emr.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_emr.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/learn_MM_generique_050224 /data/models_weight/learn_MM_generique_050224/Confusion_Matrix.png size_local : 88145 size in s3 : 88145 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:54 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_aluminium.jpg size_local : 67983 size in s3 : 67983 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:42:02 Precision_Recall_aluminium.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_ela.jpg size_local : 68484 size in s3 : 68484 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_ela.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_emr.jpg size_local : 77930 size in s3 : 77930 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:55 Precision_Recall_emr.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_film_pedb.jpg size_local : 66701 size in s3 : 66701 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:55 Precision_Recall_film_pedb.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_flux_dev.jpg size_local : 59936 size in s3 : 59936 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_flux_dev.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_jrm.jpg size_local : 72890 size in s3 : 72890 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pcm.jpg size_local : 93916 size in s3 : 93916 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:02 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pcnc.jpg size_local : 74701 size in s3 : 74701 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pehd_pp.jpg size_local : 68765 size in s3 : 68765 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:03 Precision_Recall_pehd_pp.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pet_clair.jpg size_local : 69649 size in s3 : 69649 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:03 Precision_Recall_pet_clair.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_refus.jpg size_local : 59936 size in s3 : 59936 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:59 Precision_Recall_refus.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_tapis_vide.jpg size_local : 71529 size in s3 : 71529 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:54 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Result_Summary.txt size_local : 1076 size in s3 : 1076 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:55 Result_Summary.txt already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/checkpoint size_local : 99 size in s3 : 99 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:00 checkpoint already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_checkpoint.ckpt.data-00000-of-00001 size_local : 32591049 size in s3 : 32591049 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:42:02 model_checkpoint.ckpt.data-00000-of-00001 already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_checkpoint.ckpt.index size_local : 42495 size in s3 : 42495 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:41:55 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_weights.h5 size_local : 16536200 size in s3 : 16536200 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:42:00 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ learn_MM_generique_050224den (None, 12) 15372 ================================================================= Total params: 4,064,936 Trainable params: 15,372 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 7.071617126464844 time used to load_weights : 0.12401080131530762 0it [00:00, ?it/s] 57it [00:00, 850.09it/s]temp/1755601467_2576548_1377879447_bc50d4771bc81a534bc797fef1e660cb.jpg temp/1755601467_2576548_1377879438_0cd19f46bc4074220460042398100e17.jpg temp/1755601467_2576548_1377879436_3673d17f281daebd5b1dc014f601f7cc.jpg temp/1755601467_2576548_1377879435_cc36343e3f177b10d9db86023a27b5a6.jpg temp/1755601467_2576548_1377879434_4bbba7f905fd0923f0843e9cea0cb493.jpg temp/1755601467_2576548_1377879427_74780ca066fb9780ce4f02aeb876e3c4.jpg temp/1755601467_2576548_1377879419_cae077f5122f88751e47873bdf152401.jpg temp/1755601467_2576548_1377879409_467e8b11e06232b0126b63bfe0ef3399.jpg temp/1755601467_2576548_1377879406_31c3f384c04e88dceb6d12e6fd5ea297.jpg temp/1755601467_2576548_1377879405_c82d89285e4ce99673a89fc25fad0c79.jpg temp/1755601467_2576548_1377879404_2346eeb6e9aedba1f62a370565991543.jpg temp/1755601467_2576548_1377879397_798ac8efae283ad3e443d9b0e7684130.jpg temp/1755601467_2576548_1377879395_bae044741b1247542a77fe1920fad667.jpg temp/1755601467_2576548_1377879393_629e6d89ab5197ca998210a9623c3c66.jpg temp/1755601467_2576548_1377879389_6465dc629b3585ef0ca901638ef42597.jpg temp/1755601467_2576548_1377879380_1f6bf5698ce1f075b91d021b0c96092c.jpg temp/1755601467_2576548_1377877724_4fdd207d4012ebe1e1e9cb0eb6b5cb89.jpg temp/1755601467_2576548_1377877660_920b3eee08cfa1dec4000c56370d3f19.jpg temp/1755601467_2576548_1377877641_453fc67dae820a82d52d550fc0f51e24.jpg temp/1755601467_2576548_1377877640_fcc5216414761a730de570471bfeb0b5.jpg temp/1755601467_2576548_1377877544_904f001a5fcb1147acdcd9917965108a.jpg temp/1755601467_2576548_1377877516_cfee506125657a95bd44070e30f5d8d3.jpg temp/1755601467_2576548_1377877166_0aeccdde04d79bcee5f4e834c9cefe60.jpg temp/1755601467_2576548_1377877157_34c85c1250a81ade50d7b402eff0cd13.jpg temp/1755601467_2576548_1377877121_d524090a0900a38a1fe9eaae220ecb62.jpg temp/1755601467_2576548_1377877118_f0374692cb35be0772d749e1e613c3f4.jpg temp/1755601467_2576548_1377877115_75913dfdf11e0a1de62a564f856644b5.jpg temp/1755601467_2576548_1377877090_3d05025c034867373f739636b8d29198.jpg temp/1755601467_2576548_1377877074_5bd77d8ed1d76ea58e7f8751dafaf43c.jpg temp/1755601467_2576548_1377877072_b5de5aa9f44e65a74e726171a0bd647e.jpg temp/1755601467_2576548_1377877023_c4bb856e3a803b8f30d5579b9957f975.jpg temp/1755601467_2576548_1377877011_af73eea6eddf71fdb138080342b5608d.jpg temp/1755601467_2576548_1377877007_dd05b4c6d6cc71703409f5a6b4049a76.jpg temp/1755601467_2576548_1377877004_14e51c58d779bc2b232bc769b22a1e5e.jpg temp/1755601467_2576548_1377876979_4faa4505ea74815005ed91302a76cca4.jpg temp/1755601467_2576548_1377876923_7dbaa604197b0807fc46fe4167d8fd70.jpg temp/1755601467_2576548_1377876920_7af3ec7931c48ac1a0f03c6a99f20b32.jpg temp/1755601467_2576548_1377876918_1a892ec642acbbfd380815e170ec2622.jpg temp/1755601467_2576548_1377876916_0700ad65a38cfa534bb9386ce2a32f71.jpg temp/1755601467_2576548_1377876912_99297aee9891e83f9092be4a75912222.jpg temp/1755601467_2576548_1377876910_f83c5f94b492aa6a0a433f019e2ca186.jpg temp/1755601467_2576548_1377876908_821e58e3c5ec70e06bc98a2e44c6cd19.jpg temp/1755601467_2576548_1377876900_d2d07e61949c8e9b15c140b1498a91d5.jpg temp/1755601467_2576548_1377876819_56455c3c8a49988ab3589665d8631ce5.jpg temp/1755601467_2576548_1377876805_97718ed688f5422a43ad46e713f19317.jpg temp/1755601467_2576548_1377876516_c01f0fd68e09d75dcebd8fe88348dba4.jpg temp/1755601467_2576548_1377876508_ff627b024ca940a00e87844a96633488.jpg temp/1755601467_2576548_1377876499_328551180049c094ae34e2bc4445dc85.jpg temp/1755601467_2576548_1377876496_fd547b0347bae7dca12b413905ea32e0.jpg temp/1755601467_2576548_1377876493_76497c2e9592faa1a9c5aa827074efc0.jpg temp/1755601467_2576548_1377876477_45d028601b37618de90da59d913a6ba2.jpg temp/1755601467_2576548_1377876476_29ff173ff30d3be7780128c4698ff72b.jpg temp/1755601467_2576548_1377876474_01346c435a672102b2d94ac0f85f0424.jpg temp/1755601467_2576548_1377876464_8ccee62a9ba83e359f0f76adcca63e77.jpg temp/1755601467_2576548_1377876463_ec52b54576d0bf60b6f1a65c8cf035d0.jpg temp/1755601467_2576548_1377876461_5c4e11629da633f507fc3764407c03b2.jpg temp/1755601467_2576548_1377876454_4fda3be10dca9e0db2a0284a69986090.jpg Found 57 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 4.517495632171631 (57,) (57, 12) (57, 1280) shape of features : (57, 1280) shape of new features : (1, 57, 1280) save descriptor for thcl : 3847 time to traite the descriptors : 0.23266029357910156 storage_type for insertDescriptorsMulti : 3 To insert : 1377879447 To insert : 1377879438 To insert : 1377879436 To insert : 1377879435 To insert : 1377879434 To insert : 1377879427 To insert : 1377879419 To insert : 1377879409 To insert : 1377879406 To insert : 1377879405 To insert : 1377879404 To insert : 1377879397 To insert : 1377879395 To insert : 1377879393 To insert : 1377879389 To insert : 1377879380 To insert : 1377877724 To insert : 1377877660 To insert : 1377877641 To insert : 1377877640 To insert : 1377877544 To insert : 1377877516 To insert : 1377877166 To insert : 1377877157 To insert : 1377877121 To insert : 1377877118 To insert : 1377877115 To insert : 1377877090 To insert : 1377877074 To insert : 1377877072 To insert : 1377877023 To insert : 1377877011 To insert : 1377877007 To insert : 1377877004 To insert : 1377876979 To insert : 1377876923 To insert : 1377876920 To insert : 1377876918 To insert : 1377876916 To insert : 1377876912 To insert : 1377876910 To insert : 1377876908 To insert : 1377876900 To insert : 1377876819 To insert : 1377876805 To insert : 1377876516 To insert : 1377876508 To insert : 1377876499 To insert : 1377876496 To insert : 1377876493 To insert : 1377876477 To insert : 1377876476 To insert : 1377876474 To insert : 1377876464 To insert : 1377876463 To insert : 1377876461 To insert : 1377876454 time to insert the descriptors : 12.160932779312134 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1377879447, 1377879438, 1377879436, 1377879435, 1377879434, 1377879427, 1377879419, 1377879409, 1377879406, 1377879405, 1377879404, 1377879397, 1377879395, 1377879393, 1377879389, 1377879380, 1377877724, 1377877660, 1377877641, 1377877640, 1377877544, 1377877516, 1377877166, 1377877157, 1377877121, 1377877118, 1377877115, 1377877090, 1377877074, 1377877072, 1377877023, 1377877011, 1377877007, 1377877004, 1377876979, 1377876923, 1377876920, 1377876918, 1377876916, 1377876912, 1377876910, 1377876908, 1377876900, 1377876819, 1377876805, 1377876516, 1377876508, 1377876499, 1377876496, 1377876493, 1377876477, 1377876476, 1377876474, 1377876464, 1377876463, 1377876461, 1377876454] Looping around the photos to save general results len do output : 57 /1377879447Didn't retrieve data . /1377879438Didn't retrieve data . /1377879436Didn't retrieve data . /1377879435Didn't retrieve data . /1377879434Didn't retrieve data . /1377879427Didn't retrieve data . /1377879419Didn't retrieve data . /1377879409Didn't retrieve data . /1377879406Didn't retrieve data . /1377879405Didn't retrieve data . /1377879404Didn't retrieve data . /1377879397Didn't retrieve data . /1377879395Didn't retrieve data . /1377879393Didn't retrieve data . /1377879389Didn't retrieve data . /1377879380Didn't retrieve data . /1377877724Didn't retrieve data . /1377877660Didn't retrieve data . /1377877641Didn't retrieve data . /1377877640Didn't retrieve data . /1377877544Didn't retrieve data . /1377877516Didn't retrieve data . /1377877166Didn't retrieve data . /1377877157Didn't retrieve data . /1377877121Didn't retrieve data . /1377877118Didn't retrieve data . /1377877115Didn't retrieve data . /1377877090Didn't retrieve data . /1377877074Didn't retrieve data . /1377877072Didn't retrieve data . /1377877023Didn't retrieve data . /1377877011Didn't retrieve data . /1377877007Didn't retrieve data . /1377877004Didn't retrieve data . /1377876979Didn't retrieve data . /1377876923Didn't retrieve data . /1377876920Didn't retrieve data . /1377876918Didn't retrieve data . /1377876916Didn't retrieve data . /1377876912Didn't retrieve data . /1377876910Didn't retrieve data . /1377876908Didn't retrieve data . /1377876900Didn't retrieve data . /1377876819Didn't retrieve data . /1377876805Didn't retrieve data . /1377876516Didn't retrieve data . /1377876508Didn't retrieve data . /1377876499Didn't retrieve data . /1377876496Didn't retrieve data . /1377876493Didn't retrieve data . /1377876477Didn't retrieve data . /1377876476Didn't retrieve data . /1377876474Didn't retrieve data . /1377876464Didn't retrieve data . /1377876463Didn't retrieve data . /1377876461Didn't retrieve data . /1377876454Didn'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 ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879447', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879438', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879436', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879435', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879434', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879427', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879419', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879409', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879406', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879405', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879404', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879397', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879395', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879393', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879389', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', '26046584', '1377879380', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877724', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877660', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877641', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877640', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877544', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877516', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877166', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877157', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877121', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877118', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877115', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877090', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877074', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877072', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877023', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877011', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877007', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377877004', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876979', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876923', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876920', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876918', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876916', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876912', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876910', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876908', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876900', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876819', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876805', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876516', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876508', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876499', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876496', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876493', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876477', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876476', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876474', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876464', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876463', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876461', None, None, None, None, None, '3551871') ('533', None, None, None, None, None, None, None, '3551871') ('533', None, '1377876454', None, None, None, None, None, '3551871') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 114 time used for this insertion : 0.12293839454650879 save_final save missing photos in datou_result : time spend for datou_step_exec : 84.91379594802856 time spend to save output : 0.12477445602416992 total time spend for step 1 : 85.03857040405273 step2:argmax Tue Aug 19 13:06:02 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 Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou_step Argmax ! Inside saveOutput : final : True verbose : 0 photo_id : 1377879447 output[photo_id] : [[(1377879447, '05102018_Papier_non_papier_presque_vide', 0.9308216, 4557, 3513), (1377879447, 'tapis_vide', 0.6104337, 4374, 3379), (1377879447, 'tapis_vide', 0.87041277, 4932, 3847)], 'temp/1755601467_2576548_1377879447_bc50d4771bc81a534bc797fef1e660cb.jpg'] photo_id : 1377879438 output[photo_id] : [[(1377879438, '05102018_Papier_non_papier_presque_vide', 0.937921, 4557, 3513), (1377879438, 'tapis_vide', 0.5991319, 4374, 3379), (1377879438, 'tapis_vide', 0.86905575, 4932, 3847)], 'temp/1755601467_2576548_1377879438_0cd19f46bc4074220460042398100e17.jpg'] photo_id : 1377879436 output[photo_id] : [[(1377879436, '05102018_Papier_non_papier_presque_vide', 0.95112854, 4557, 3513), (1377879436, 'tapis_vide', 0.5968668, 4374, 3379), (1377879436, 'tapis_vide', 0.8544383, 4932, 3847)], 'temp/1755601467_2576548_1377879436_3673d17f281daebd5b1dc014f601f7cc.jpg'] photo_id : 1377879435 output[photo_id] : [[(1377879435, '05102018_Papier_non_papier_presque_vide', 0.9660744, 4557, 3513), (1377879435, 'tapis_vide', 0.5390787, 4374, 3379), (1377879435, 'tapis_vide', 0.83440614, 4932, 3847)], 'temp/1755601467_2576548_1377879435_cc36343e3f177b10d9db86023a27b5a6.jpg'] photo_id : 1377879434 output[photo_id] : [[(1377879434, '05102018_Papier_non_papier_presque_vide', 0.9250971, 4557, 3513), (1377879434, 'tapis_vide', 0.6167749, 4374, 3379), (1377879434, 'tapis_vide', 0.87500817, 4932, 3847)], 'temp/1755601467_2576548_1377879434_4bbba7f905fd0923f0843e9cea0cb493.jpg'] photo_id : 1377879427 output[photo_id] : [[(1377879427, '05102018_Papier_non_papier_presque_vide', 0.9710295, 4557, 3513), (1377879427, 'tapis_vide', 0.5060334, 4374, 3379), (1377879427, 'tapis_vide', 0.7990532, 4932, 3847)], 'temp/1755601467_2576548_1377879427_74780ca066fb9780ce4f02aeb876e3c4.jpg'] photo_id : 1377879419 output[photo_id] : [[(1377879419, '05102018_Papier_non_papier_presque_vide', 0.92509204, 4557, 3513), (1377879419, 'pet_clair', 0.70001173, 4374, 3379), (1377879419, 'pet_clair', 0.8900896, 4932, 3847)], 'temp/1755601467_2576548_1377879419_cae077f5122f88751e47873bdf152401.jpg'] photo_id : 1377879409 output[photo_id] : [[(1377879409, '05102018_Papier_non_papier_presque_vide', 0.92843205, 4557, 3513), (1377879409, 'tapis_vide', 0.6350414, 4374, 3379), (1377879409, 'tapis_vide', 0.8534887, 4932, 3847)], 'temp/1755601467_2576548_1377879409_467e8b11e06232b0126b63bfe0ef3399.jpg'] photo_id : 1377879406 output[photo_id] : [[(1377879406, '05102018_Papier_non_papier_presque_vide', 0.94353855, 4557, 3513), (1377879406, 'tapis_vide', 0.6646679, 4374, 3379), (1377879406, 'tapis_vide', 0.8517727, 4932, 3847)], 'temp/1755601467_2576548_1377879406_31c3f384c04e88dceb6d12e6fd5ea297.jpg'] photo_id : 1377879405 output[photo_id] : [[(1377879405, '05102018_Papier_non_papier_presque_vide', 0.93032104, 4557, 3513), (1377879405, 'tapis_vide', 0.6844259, 4374, 3379), (1377879405, 'tapis_vide', 0.7997702, 4932, 3847)], 'temp/1755601467_2576548_1377879405_c82d89285e4ce99673a89fc25fad0c79.jpg'] photo_id : 1377879404 output[photo_id] : [[(1377879404, '05102018_Papier_non_papier_presque_vide', 0.92411745, 4557, 3513), (1377879404, 'tapis_vide', 0.6064341, 4374, 3379), (1377879404, 'tapis_vide', 0.872139, 4932, 3847)], 'temp/1755601467_2576548_1377879404_2346eeb6e9aedba1f62a370565991543.jpg'] photo_id : 1377879397 output[photo_id] : [[(1377879397, '05102018_Papier_non_papier_presque_vide', 0.9201298, 4557, 3513), (1377879397, 'tapis_vide', 0.5992001, 4374, 3379), (1377879397, 'tapis_vide', 0.8606086, 4932, 3847)], 'temp/1755601467_2576548_1377879397_798ac8efae283ad3e443d9b0e7684130.jpg'] photo_id : 1377879395 output[photo_id] : [[(1377879395, '05102018_Papier_non_papier_presque_vide', 0.9281895, 4557, 3513), (1377879395, 'tapis_vide', 0.6118695, 4374, 3379), (1377879395, 'tapis_vide', 0.8645329, 4932, 3847)], 'temp/1755601467_2576548_1377879395_bae044741b1247542a77fe1920fad667.jpg'] photo_id : 1377879393 output[photo_id] : [[(1377879393, '05102018_Papier_non_papier_presque_vide', 0.92693937, 4557, 3513), (1377879393, 'tapis_vide', 0.589598, 4374, 3379), (1377879393, 'tapis_vide', 0.86911005, 4932, 3847)], 'temp/1755601467_2576548_1377879393_629e6d89ab5197ca998210a9623c3c66.jpg'] photo_id : 1377879389 output[photo_id] : [[(1377879389, '05102018_Papier_non_papier_presque_vide', 0.9563642, 4557, 3513), (1377879389, 'tapis_vide', 0.5675852, 4374, 3379), (1377879389, 'tapis_vide', 0.84765446, 4932, 3847)], 'temp/1755601467_2576548_1377879389_6465dc629b3585ef0ca901638ef42597.jpg'] photo_id : 1377879380 output[photo_id] : [[(1377879380, '05102018_Papier_non_papier_presque_vide', 0.9192714, 4557, 3513), (1377879380, 'tapis_vide', 0.58842117, 4374, 3379), (1377879380, 'tapis_vide', 0.8699256, 4932, 3847)], 'temp/1755601467_2576548_1377879380_1f6bf5698ce1f075b91d021b0c96092c.jpg'] photo_id : 1377877724 output[photo_id] : [[(1377877724, '05102018_Papier_non_papier_tres_dense', 0.449944, 4557, 3513), (1377877724, 'film_pedb', 0.7955852, 4374, 3379), (1377877724, 'film_pedb', 0.8961125, 4932, 3847)], 'temp/1755601467_2576548_1377877724_4fdd207d4012ebe1e1e9cb0eb6b5cb89.jpg'] photo_id : 1377877660 output[photo_id] : [[(1377877660, '05102018_Papier_non_papier_presque_vide', 0.9723166, 4557, 3513), (1377877660, 'tapis_vide', 0.5016001, 4374, 3379), (1377877660, 'tapis_vide', 0.8191192, 4932, 3847)], 'temp/1755601467_2576548_1377877660_920b3eee08cfa1dec4000c56370d3f19.jpg'] photo_id : 1377877641 output[photo_id] : [[(1377877641, '05102018_Papier_non_papier_presque_vide', 0.9311238, 4557, 3513), (1377877641, 'tapis_vide', 0.5860479, 4374, 3379), (1377877641, 'tapis_vide', 0.873173, 4932, 3847)], 'temp/1755601467_2576548_1377877641_453fc67dae820a82d52d550fc0f51e24.jpg'] photo_id : 1377877640 output[photo_id] : [[(1377877640, '05102018_Papier_non_papier_presque_vide', 0.97234166, 4557, 3513), (1377877640, 'tapis_vide', 0.5016209, 4374, 3379), (1377877640, 'tapis_vide', 0.8191005, 4932, 3847)], 'temp/1755601467_2576548_1377877640_fcc5216414761a730de570471bfeb0b5.jpg'] photo_id : 1377877544 output[photo_id] : [[(1377877544, '05102018_Papier_non_papier_tres_dense', 0.4798971, 4557, 3513), (1377877544, 'film_pedb', 0.80573887, 4374, 3379), (1377877544, 'film_pedb', 0.95663995, 4932, 3847)], 'temp/1755601467_2576548_1377877544_904f001a5fcb1147acdcd9917965108a.jpg'] photo_id : 1377877516 output[photo_id] : [[(1377877516, '05102018_Papier_non_papier_tres_dense', 0.4500813, 4557, 3513), (1377877516, 'film_pedb', 0.79553103, 4374, 3379), (1377877516, 'film_pedb', 0.8961181, 4932, 3847)], 'temp/1755601467_2576548_1377877516_cfee506125657a95bd44070e30f5d8d3.jpg'] photo_id : 1377877166 output[photo_id] : [[(1377877166, '05102018_Papier_non_papier_tres_dense', 0.47985142, 4557, 3513), (1377877166, 'film_pedb', 0.80585015, 4374, 3379), (1377877166, 'film_pedb', 0.95663583, 4932, 3847)], 'temp/1755601467_2576548_1377877166_0aeccdde04d79bcee5f4e834c9cefe60.jpg'] photo_id : 1377877157 output[photo_id] : [[(1377877157, '05102018_Papier_non_papier_tres_dense', 0.4500509, 4557, 3513), (1377877157, 'film_pedb', 0.7955067, 4374, 3379), (1377877157, 'film_pedb', 0.8961707, 4932, 3847)], 'temp/1755601467_2576548_1377877157_34c85c1250a81ade50d7b402eff0cd13.jpg'] photo_id : 1377877121 output[photo_id] : [[(1377877121, '05102018_Papier_non_papier_presque_vide', 0.42486838, 4557, 3513), (1377877121, 'film_pedb', 0.90189034, 4374, 3379), (1377877121, 'film_pedb', 0.95980996, 4932, 3847)], 'temp/1755601467_2576548_1377877121_d524090a0900a38a1fe9eaae220ecb62.jpg'] photo_id : 1377877118 output[photo_id] : [[(1377877118, '05102018_Papier_non_papier_tres_dense', 0.47972193, 4557, 3513), (1377877118, 'film_pedb', 0.80574316, 4374, 3379), (1377877118, 'film_pedb', 0.95664775, 4932, 3847)], 'temp/1755601467_2576548_1377877118_f0374692cb35be0772d749e1e613c3f4.jpg'] photo_id : 1377877115 output[photo_id] : [[(1377877115, '05102018_Papier_non_papier_tres_dense', 0.44970575, 4557, 3513), (1377877115, 'film_pedb', 0.7956703, 4374, 3379), (1377877115, 'film_pedb', 0.8961506, 4932, 3847)], 'temp/1755601467_2576548_1377877115_75913dfdf11e0a1de62a564f856644b5.jpg'] photo_id : 1377877090 output[photo_id] : [[(1377877090, '05102018_Papier_non_papier_presque_vide', 0.9295288, 4557, 3513), (1377877090, 'tapis_vide', 0.6068579, 4374, 3379), (1377877090, 'tapis_vide', 0.869839, 4932, 3847)], 'temp/1755601467_2576548_1377877090_3d05025c034867373f739636b8d29198.jpg'] photo_id : 1377877074 output[photo_id] : [[(1377877074, '05102018_Papier_non_papier_tres_dense', 0.47968334, 4557, 3513), (1377877074, 'film_pedb', 0.80566233, 4374, 3379), (1377877074, 'film_pedb', 0.9566573, 4932, 3847)], 'temp/1755601467_2576548_1377877074_5bd77d8ed1d76ea58e7f8751dafaf43c.jpg'] photo_id : 1377877072 output[photo_id] : [[(1377877072, '05102018_Papier_non_papier_tres_dense', 0.44980475, 4557, 3513), (1377877072, 'film_pedb', 0.7956529, 4374, 3379), (1377877072, 'film_pedb', 0.8961638, 4932, 3847)], 'temp/1755601467_2576548_1377877072_b5de5aa9f44e65a74e726171a0bd647e.jpg'] photo_id : 1377877023 output[photo_id] : [[(1377877023, '05102018_Papier_non_papier_presque_vide', 0.9290715, 4557, 3513), (1377877023, 'tapis_vide', 0.60410994, 4374, 3379), (1377877023, 'tapis_vide', 0.85454875, 4932, 3847)], 'temp/1755601467_2576548_1377877023_c4bb856e3a803b8f30d5579b9957f975.jpg'] photo_id : 1377877011 output[photo_id] : [[(1377877011, '05102018_Papier_non_papier_presque_vide', 0.4248387, 4557, 3513), (1377877011, 'film_pedb', 0.90186703, 4374, 3379), (1377877011, 'film_pedb', 0.95979905, 4932, 3847)], 'temp/1755601467_2576548_1377877011_af73eea6eddf71fdb138080342b5608d.jpg'] photo_id : 1377877007 output[photo_id] : [[(1377877007, '05102018_Papier_non_papier_tres_dense', 0.4797638, 4557, 3513), (1377877007, 'film_pedb', 0.80580664, 4374, 3379), (1377877007, 'film_pedb', 0.95666045, 4932, 3847)], 'temp/1755601467_2576548_1377877007_dd05b4c6d6cc71703409f5a6b4049a76.jpg'] photo_id : 1377877004 output[photo_id] : [[(1377877004, '05102018_Papier_non_papier_tres_dense', 0.44977093, 4557, 3513), (1377877004, 'film_pedb', 0.7954885, 4374, 3379), (1377877004, 'film_pedb', 0.8961814, 4932, 3847)], 'temp/1755601467_2576548_1377877004_14e51c58d779bc2b232bc769b22a1e5e.jpg'] photo_id : 1377876979 output[photo_id] : [[(1377876979, '05102018_Papier_non_papier_presque_vide', 0.91871905, 4557, 3513), (1377876979, 'tapis_vide', 0.5924363, 4374, 3379), (1377876979, 'tapis_vide', 0.86726415, 4932, 3847)], 'temp/1755601467_2576548_1377876979_4faa4505ea74815005ed91302a76cca4.jpg'] photo_id : 1377876923 output[photo_id] : [[(1377876923, '05102018_Papier_non_papier_presque_vide', 0.91466755, 4557, 3513), (1377876923, 'tapis_vide', 0.5864232, 4374, 3379), (1377876923, 'tapis_vide', 0.8708059, 4932, 3847)], 'temp/1755601467_2576548_1377876923_7dbaa604197b0807fc46fe4167d8fd70.jpg'] photo_id : 1377876920 output[photo_id] : [[(1377876920, '05102018_Papier_non_papier_presque_vide', 0.92325217, 4557, 3513), (1377876920, 'tapis_vide', 0.5913418, 4374, 3379), (1377876920, 'tapis_vide', 0.86880183, 4932, 3847)], 'temp/1755601467_2576548_1377876920_7af3ec7931c48ac1a0f03c6a99f20b32.jpg'] photo_id : 1377876918 output[photo_id] : [[(1377876918, '05102018_Papier_non_papier_presque_vide', 0.9149599, 4557, 3513), (1377876918, 'tapis_vide', 0.5787422, 4374, 3379), (1377876918, 'tapis_vide', 0.87508917, 4932, 3847)], 'temp/1755601467_2576548_1377876918_1a892ec642acbbfd380815e170ec2622.jpg'] photo_id : 1377876916 output[photo_id] : [[(1377876916, '05102018_Papier_non_papier_tres_dense', 0.3489214, 4557, 3513), (1377876916, 'film_pedb', 0.6180854, 4374, 3379), (1377876916, 'film_pedb', 0.9219049, 4932, 3847)], 'temp/1755601467_2576548_1377876916_0700ad65a38cfa534bb9386ce2a32f71.jpg'] photo_id : 1377876912 output[photo_id] : [[(1377876912, '05102018_Papier_non_papier_tres_dense', 0.33136502, 4557, 3513), (1377876912, 'film_pedb', 0.9236399, 4374, 3379), (1377876912, 'film_pedb', 0.93331003, 4932, 3847)], 'temp/1755601467_2576548_1377876912_99297aee9891e83f9092be4a75912222.jpg'] photo_id : 1377876910 output[photo_id] : [[(1377876910, '05102018_Papier_non_papier_presque_vide', 0.42481655, 4557, 3513), (1377876910, 'film_pedb', 0.9018421, 4374, 3379), (1377876910, 'film_pedb', 0.9597725, 4932, 3847)], 'temp/1755601467_2576548_1377876910_f83c5f94b492aa6a0a433f019e2ca186.jpg'] photo_id : 1377876908 output[photo_id] : [[(1377876908, '05102018_Papier_non_papier_tres_dense', 0.47985232, 4557, 3513), (1377876908, 'film_pedb', 0.80580896, 4374, 3379), (1377876908, 'film_pedb', 0.9566513, 4932, 3847)], 'temp/1755601467_2576548_1377876908_821e58e3c5ec70e06bc98a2e44c6cd19.jpg'] photo_id : 1377876900 output[photo_id] : [[(1377876900, '05102018_Papier_non_papier_tres_dense', 0.4498486, 4557, 3513), (1377876900, 'film_pedb', 0.795528, 4374, 3379), (1377876900, 'film_pedb', 0.89617413, 4932, 3847)], 'temp/1755601467_2576548_1377876900_d2d07e61949c8e9b15c140b1498a91d5.jpg'] photo_id : 1377876819 output[photo_id] : [[(1377876819, '05102018_Papier_non_papier_tres_dense', 0.47981706, 4557, 3513), (1377876819, 'film_pedb', 0.80578214, 4374, 3379), (1377876819, 'film_pedb', 0.95666, 4932, 3847)], 'temp/1755601467_2576548_1377876819_56455c3c8a49988ab3589665d8631ce5.jpg'] photo_id : 1377876805 output[photo_id] : [[(1377876805, '05102018_Papier_non_papier_tres_dense', 0.4497662, 4557, 3513), (1377876805, 'film_pedb', 0.7956691, 4374, 3379), (1377876805, 'film_pedb', 0.8961681, 4932, 3847)], 'temp/1755601467_2576548_1377876805_97718ed688f5422a43ad46e713f19317.jpg'] photo_id : 1377876516 output[photo_id] : [[(1377876516, '05102018_Papier_non_papier_tres_dense', 0.44981673, 4557, 3513), (1377876516, 'film_pedb', 0.79560566, 4374, 3379), (1377876516, 'film_pedb', 0.8961216, 4932, 3847)], 'temp/1755601467_2576548_1377876516_c01f0fd68e09d75dcebd8fe88348dba4.jpg'] photo_id : 1377876508 output[photo_id] : [[(1377876508, '05102018_Papier_non_papier_presque_vide', 0.9286696, 4557, 3513), (1377876508, 'tapis_vide', 0.60508054, 4374, 3379), (1377876508, 'tapis_vide', 0.86373794, 4932, 3847)], 'temp/1755601467_2576548_1377876508_ff627b024ca940a00e87844a96633488.jpg'] photo_id : 1377876499 output[photo_id] : [[(1377876499, '05102018_Papier_non_papier_presque_vide', 0.92147535, 4557, 3513), (1377876499, 'tapis_vide', 0.59005296, 4374, 3379), (1377876499, 'tapis_vide', 0.8607353, 4932, 3847)], 'temp/1755601467_2576548_1377876499_328551180049c094ae34e2bc4445dc85.jpg'] photo_id : 1377876496 output[photo_id] : [[(1377876496, '05102018_Papier_non_papier_presque_vide', 0.9315977, 4557, 3513), (1377876496, 'tapis_vide', 0.5942023, 4374, 3379), (1377876496, 'tapis_vide', 0.86352503, 4932, 3847)], 'temp/1755601467_2576548_1377876496_fd547b0347bae7dca12b413905ea32e0.jpg'] photo_id : 1377876493 output[photo_id] : [[(1377876493, '05102018_Papier_non_papier_presque_vide', 0.92681044, 4557, 3513), (1377876493, 'tapis_vide', 0.59913385, 4374, 3379), (1377876493, 'tapis_vide', 0.8709297, 4932, 3847)], 'temp/1755601467_2576548_1377876493_76497c2e9592faa1a9c5aa827074efc0.jpg'] photo_id : 1377876477 output[photo_id] : [[(1377876477, '05102018_Papier_non_papier_presque_vide', 0.9314952, 4557, 3513), (1377876477, 'tapis_vide', 0.59427834, 4374, 3379), (1377876477, 'tapis_vide', 0.8635008, 4932, 3847)], 'temp/1755601467_2576548_1377876477_45d028601b37618de90da59d913a6ba2.jpg'] photo_id : 1377876476 output[photo_id] : [[(1377876476, '05102018_Papier_non_papier_presque_vide', 0.91496134, 4557, 3513), (1377876476, 'tapis_vide', 0.5787489, 4374, 3379), (1377876476, 'tapis_vide', 0.8750382, 4932, 3847)], 'temp/1755601467_2576548_1377876476_29ff173ff30d3be7780128c4698ff72b.jpg'] photo_id : 1377876474 output[photo_id] : [[(1377876474, '05102018_Papier_non_papier_presque_vide', 0.92683905, 4557, 3513), (1377876474, 'tapis_vide', 0.59916204, 4374, 3379), (1377876474, 'tapis_vide', 0.8709562, 4932, 3847)], 'temp/1755601467_2576548_1377876474_01346c435a672102b2d94ac0f85f0424.jpg'] photo_id : 1377876464 output[photo_id] : [[(1377876464, '05102018_Papier_non_papier_tres_dense', 0.33136413, 4557, 3513), (1377876464, 'film_pedb', 0.92360246, 4374, 3379), (1377876464, 'film_pedb', 0.9332971, 4932, 3847)], 'temp/1755601467_2576548_1377876464_8ccee62a9ba83e359f0f76adcca63e77.jpg'] photo_id : 1377876463 output[photo_id] : [[(1377876463, '05102018_Papier_non_papier_presque_vide', 0.4249275, 4557, 3513), (1377876463, 'film_pedb', 0.90182483, 4374, 3379), (1377876463, 'film_pedb', 0.9598077, 4932, 3847)], 'temp/1755601467_2576548_1377876463_ec52b54576d0bf60b6f1a65c8cf035d0.jpg'] photo_id : 1377876461 output[photo_id] : [[(1377876461, '05102018_Papier_non_papier_tres_dense', 0.47980896, 4557, 3513), (1377876461, 'film_pedb', 0.80602676, 4374, 3379), (1377876461, 'film_pedb', 0.95664775, 4932, 3847)], 'temp/1755601467_2576548_1377876461_5c4e11629da633f507fc3764407c03b2.jpg'] photo_id : 1377876454 output[photo_id] : [[(1377876454, '05102018_Papier_non_papier_tres_dense', 0.44979224, 4557, 3513), (1377876454, 'film_pedb', 0.7954463, 4374, 3379), (1377876454, 'film_pedb', 0.8961301, 4932, 3847)], 'temp/1755601467_2576548_1377876454_4fda3be10dca9e0db2a0284a69986090.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 171 time used for this insertion : 0.4139087200164795 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 171 time used for this insertion : 0.02091217041015625 len list_finale : 171, len picture : 57 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 171 time used for this insertion : 0.026300907135009766 saving photo_ids in datou_result photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 16 time used for this insertion : 0.017385244369506836 save missing photos in datou_result : time spend for datou_step_exec : 0.011631011962890625 time spend to save output : 0.5003128051757812 total time spend for step 2 : 0.5119438171386719 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 57 set_done_treatment 45.28user 6.62system 1:38.32elapsed 52%CPU (0avgtext+0avgdata 3029184maxresident)k 288inputs+426888outputs (6major+2153261minor)pagefaults 0swaps