python /home/admin/mtr/script_for_cron.py -j default -m 20 -a 'python3 ~/workarea/git/Velours/python/prod/datou.py -j batch_current -C 3777284' -s carac_3318 -M 0 -S 0 -U 100,80,95 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/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', '/home/admin/workarea/git/apy', '/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 : 374033 load datou : 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 ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou is not linked in the step_by_step architecture ! 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 : (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (x0, y0, x1, y1) 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 updating current state to 1 list_input_json: [] Current got : datou_id : 3318, datou_cur_ids : ['3777284'] with mtr_portfolio_ids : ['27223367'] and first list_photo_ids : [] new path : /proc/374033/ 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 ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 8 ; length of list_pids : 8 ; length of list_args : 8 time to download the photos : 1.7904362678527832 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 : 10 step1:mask_detect Tue Sep 30 17:09:10 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 mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10582 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-30 17:09:13.200705: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-30 17:09:13.228574: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-30 17:09:13.230869: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fbb3c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:09:13.230932: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-30 17:09:13.235201: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-30 17:09:13.420840: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x103be960 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:09:13.420895: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-30 17:09:13.422418: 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 2025-09-30 17:09:13.422916: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:09:13.426565: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:09:13.430078: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:09:13.430459: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:09:13.433989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:09:13.435419: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:09:13.440259: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:09:13.441825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:09:13.441921: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:09:13.442683: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:09:13.442700: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:09:13.442708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:09:13.444003: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9801 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-09-30 17:09:13.851243: 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 2025-09-30 17:09:13.851450: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:09:13.851502: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:09:13.851549: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:09:13.851591: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:09:13.851633: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:09:13.851674: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:09:13.851717: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:09:13.854818: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:09:13.856679: 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 2025-09-30 17:09:13.856808: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:09:13.856839: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:09:13.856864: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:09:13.856890: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:09:13.856915: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:09:13.856939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:09:13.856968: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:09:13.859242: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:09:13.859322: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:09:13.859343: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:09:13.859360: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:09:13.861629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9801 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-09-30 17:09:21.626110: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:09:21.816253: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 43.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 11 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 40.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 42.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 10 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 11 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 34.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 29.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 39.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 Detection mask done ! Trying to reset tf kernel 374201 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5290 tf kernel not reseted sub process len(results) : 8 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 8 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10582 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2847 Catched exception ! Connect or reconnect ! thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.0002002716064453125 nb_pixel_total : 7248 time to create 1 rle with old method : 0.008338689804077148 length of segment : 99 time for calcul the mask position with numpy : 0.00021648406982421875 nb_pixel_total : 9061 time to create 1 rle with old method : 0.010398149490356445 length of segment : 180 time for calcul the mask position with numpy : 0.0001609325408935547 nb_pixel_total : 8675 time to create 1 rle with old method : 0.010000467300415039 length of segment : 140 time for calcul the mask position with numpy : 0.0001671314239501953 nb_pixel_total : 9986 time to create 1 rle with old method : 0.011414527893066406 length of segment : 114 time for calcul the mask position with numpy : 0.00020432472229003906 nb_pixel_total : 7493 time to create 1 rle with old method : 0.008753299713134766 length of segment : 147 time for calcul the mask position with numpy : 0.00016117095947265625 nb_pixel_total : 8443 time to create 1 rle with old method : 0.00959467887878418 length of segment : 104 time for calcul the mask position with numpy : 0.0001342296600341797 nb_pixel_total : 6903 time to create 1 rle with old method : 0.007960081100463867 length of segment : 102 time for calcul the mask position with numpy : 0.0002295970916748047 nb_pixel_total : 9641 time to create 1 rle with old method : 0.0111236572265625 length of segment : 166 time for calcul the mask position with numpy : 0.0005252361297607422 nb_pixel_total : 31014 time to create 1 rle with old method : 0.03550362586975098 length of segment : 211 time for calcul the mask position with numpy : 0.0001838207244873047 nb_pixel_total : 10449 time to create 1 rle with old method : 0.011553287506103516 length of segment : 160 time for calcul the mask position with numpy : 0.00012683868408203125 nb_pixel_total : 5504 time to create 1 rle with old method : 0.006382942199707031 length of segment : 205 time for calcul the mask position with numpy : 0.00017499923706054688 nb_pixel_total : 6739 time to create 1 rle with old method : 0.007650613784790039 length of segment : 126 time for calcul the mask position with numpy : 9.226799011230469e-05 nb_pixel_total : 3223 time to create 1 rle with old method : 0.003908872604370117 length of segment : 80 time for calcul the mask position with numpy : 0.0002334117889404297 nb_pixel_total : 16202 time to create 1 rle with old method : 0.01855635643005371 length of segment : 121 time for calcul the mask position with numpy : 0.00010204315185546875 nb_pixel_total : 3490 time to create 1 rle with old method : 0.004161834716796875 length of segment : 102 time for calcul the mask position with numpy : 0.00016117095947265625 nb_pixel_total : 8213 time to create 1 rle with old method : 0.009624242782592773 length of segment : 104 time for calcul the mask position with numpy : 6.222724914550781e-05 nb_pixel_total : 2045 time to create 1 rle with old method : 0.0025844573974609375 length of segment : 38 time for calcul the mask position with numpy : 6.651878356933594e-05 nb_pixel_total : 2172 time to create 1 rle with old method : 0.002550363540649414 length of segment : 59 time for calcul the mask position with numpy : 0.0001010894775390625 nb_pixel_total : 5508 time to create 1 rle with old method : 0.006375312805175781 length of segment : 72 time for calcul the mask position with numpy : 7.510185241699219e-05 nb_pixel_total : 2282 time to create 1 rle with old method : 0.0026352405548095703 length of segment : 72 time for calcul the mask position with numpy : 0.00012731552124023438 nb_pixel_total : 5130 time to create 1 rle with old method : 0.006020069122314453 length of segment : 103 time for calcul the mask position with numpy : 0.0001862049102783203 nb_pixel_total : 8986 time to create 1 rle with old method : 0.010220050811767578 length of segment : 161 time for calcul the mask position with numpy : 0.0002269744873046875 nb_pixel_total : 11033 time to create 1 rle with old method : 0.01215219497680664 length of segment : 185 time for calcul the mask position with numpy : 0.00015401840209960938 nb_pixel_total : 8350 time to create 1 rle with old method : 0.009532451629638672 length of segment : 101 time for calcul the mask position with numpy : 0.00150299072265625 nb_pixel_total : 86498 time to create 1 rle with old method : 0.09600329399108887 length of segment : 483 time for calcul the mask position with numpy : 0.00011014938354492188 nb_pixel_total : 4123 time to create 1 rle with old method : 0.004800319671630859 length of segment : 103 time spent for convertir_results : 1.3897514343261719 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 26 chid ids of type : 3594 Number RLEs to save : 3538 save missing photos in datou_result : time spend for datou_step_exec : 22.891201734542847 time spend to save output : 0.6103992462158203 total time spend for step 1 : 23.501600980758667 step2:crop_condition Tue Sep 30 17:09:33 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure Loading chi in step crop with photo_hashtag_type : 3594 Loading chi in step crop for list_pids : 8 ! batch 1 Loaded 26 chid ids of type : 3594 ++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 21 About to insert : list_path_to_insert length 21 new photo from crops ! About to upload 21 photos upload in portfolio : 3736932 init cache_photo without model_param we have 21 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244975_374033 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055752_f3eba266de0d4b30805a3b3da48814dc_rle_crop_3981111325_0.png', 0, 109, 96, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111326_0.png', 0, 89, 180, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111331_0.png', 0, 87, 102, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111327_0.png', 0, 103, 134, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111330_0.png', 0, 105, 103, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111329_0.png', 0, 115, 147, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111328_0.png', 0, 123, 114, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055735_0a500bdf9ab7ec79e17628249cda89ab_rle_crop_3981111332_0.png', 0, 117, 165, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111335_0.png', 0, 73, 113, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111337_0.png', 0, 78, 80, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111336_0.png', 0, 104, 126, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111341_0.png', 0, 77, 38, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111339_0.png', 0, 56, 100, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111343_0.png', 0, 100, 71, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111338_0.png', 0, 160, 119, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111342_0.png', 0, 49, 59, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111340_0.png', 0, 114, 100, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111347_0.png', 0, 106, 185, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111345_0.png', 0, 115, 94, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111348_0.png', 0, 120, 98, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244979), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055656_454155fa37d98c41d3573652a06392e1_rle_crop_3981111350_0.png', 0, 85, 103, 0, 1759244979,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 21 photos in the portfolio 3736932 time of upload the photos Elapsed time : 7.0139241218566895 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244982_374033 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244983), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111334_0.png', 0, 91, 154, 0, 1759244983,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244983), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111344_0.png', 0, 56, 71, 0, 1759244983,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244983), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111346_0.png', 0, 100, 156, 0, 1759244983,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.418724775314331 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244984_374033 INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244985), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111333_0.png', 0, 225, 210, 0, 1759244985,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! INSERT INTO MTRBack.photos (`timeStamp`, `latitude`, `longitude`, `right_categories`, `tags`, `speed`, `size`, `text`, `altitude`, `width`, `height`, `score`, `created_at`,`source_id`,`place_id`) VALUES (FROM_UNIXTIME(1759244985), 0.0, 0.0, 14, '', 0, 0, '1759244948_374033_1386055660_8ca166e474cde9eb3607617acb81c68e_rle_crop_3981111349_0.png', 0, 323, 481, 0, 1759244985,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.97536301612854 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 26 /1386984413Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984414Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984415Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984416Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984417Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984418Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984419Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984420Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984421Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984422Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984424Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984425Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984426Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984427Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984428Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984429Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984430Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984431Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984432Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984433Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984434Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984436Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984437Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984439Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 86 time used for this insertion : 0.039052724838256836 save_final save missing photos in datou_result : time spend for datou_step_exec : 11.566096067428589 time spend to save output : 0.03983950614929199 total time spend for step 2 : 11.60593557357788 step3:rle_unique_nms_with_priority Tue Sep 30 17:09:45 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 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 26 chid ids of type : 3594 ++++++++++++++++++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.2125380039215088 time for calcul the mask position with numpy : 0.06595826148986816 nb_pixel_total : 2066352 time to create 1 rle with new method : 0.15233731269836426 time for calcul the mask position with numpy : 0.0058863162994384766 nb_pixel_total : 7248 time to create 1 rle with old method : 0.007857084274291992 create new chi : 0.24251008033752441 time to delete rle : 0.11883902549743652 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1278 TO DO : save crop sub photo not yet done ! save time : 0.29364871978759766 nb_obj : 6 nb_hashtags : 1 time to prepare the origin masks : 0.4851839542388916 time for calcul the mask position with numpy : 0.18076705932617188 nb_pixel_total : 2023039 time to create 1 rle with new method : 0.08041858673095703 time for calcul the mask position with numpy : 0.006012916564941406 nb_pixel_total : 6903 time to create 1 rle with old method : 0.007168292999267578 time for calcul the mask position with numpy : 0.010729074478149414 nb_pixel_total : 8443 time to create 1 rle with old method : 0.009239912033081055 time for calcul the mask position with numpy : 0.006545305252075195 nb_pixel_total : 7493 time to create 1 rle with old method : 0.008126258850097656 time for calcul the mask position with numpy : 0.0061795711517333984 nb_pixel_total : 9986 time to create 1 rle with old method : 0.011020183563232422 time for calcul the mask position with numpy : 0.0075457096099853516 nb_pixel_total : 8675 time to create 1 rle with old method : 0.010674476623535156 time for calcul the mask position with numpy : 0.006465911865234375 nb_pixel_total : 9061 time to create 1 rle with old method : 0.009768009185791016 create new chi : 0.3707454204559326 time to delete rle : 0.0003848075866699219 batch 1 Loaded 13 chid ids of type : 3594 ++++++Number RLEs to save : 2654 TO DO : save crop sub photo not yet done ! save time : 0.4452788829803467 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.09278392791748047 time for calcul the mask position with numpy : 0.018567800521850586 nb_pixel_total : 2063959 time to create 1 rle with new method : 0.05412030220031738 time for calcul the mask position with numpy : 0.006349325180053711 nb_pixel_total : 9641 time to create 1 rle with old method : 0.010802745819091797 create new chi : 0.09912252426147461 time to delete rle : 0.00021982192993164062 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1412 TO DO : save crop sub photo not yet done ! save time : 0.2812471389770508 nb_obj : 5 nb_hashtags : 3 time to prepare the origin masks : 0.5701818466186523 time for calcul the mask position with numpy : 0.06390523910522461 nb_pixel_total : 2016671 time to create 1 rle with new method : 0.20546698570251465 time for calcul the mask position with numpy : 0.006058454513549805 nb_pixel_total : 3223 time to create 1 rle with old method : 0.0035448074340820312 time for calcul the mask position with numpy : 0.005911111831665039 nb_pixel_total : 6739 time to create 1 rle with old method : 0.007345676422119141 time for calcul the mask position with numpy : 0.006112337112426758 nb_pixel_total : 5504 time to create 1 rle with old method : 0.006075859069824219 time for calcul the mask position with numpy : 0.005964040756225586 nb_pixel_total : 10449 time to create 1 rle with old method : 0.011399269104003906 time for calcul the mask position with numpy : 0.006409645080566406 nb_pixel_total : 31014 time to create 1 rle with old method : 0.03445601463317871 create new chi : 0.3728804588317871 time to delete rle : 0.0003483295440673828 batch 1 Loaded 11 chid ids of type : 3594 +++++++Number RLEs to save : 2644 TO DO : save crop sub photo not yet done ! save time : 0.45908594131469727 nb_obj : 7 nb_hashtags : 2 time to prepare the origin masks : 0.12677574157714844 time for calcul the mask position with numpy : 0.3390007019042969 nb_pixel_total : 2033688 time to create 1 rle with new method : 0.08630537986755371 time for calcul the mask position with numpy : 0.00832986831665039 nb_pixel_total : 2282 time to create 1 rle with old method : 0.0025348663330078125 time for calcul the mask position with numpy : 0.008111715316772461 nb_pixel_total : 5508 time to create 1 rle with old method : 0.005929708480834961 time for calcul the mask position with numpy : 0.005925416946411133 nb_pixel_total : 2172 time to create 1 rle with old method : 0.0024559497833251953 time for calcul the mask position with numpy : 0.005869865417480469 nb_pixel_total : 2045 time to create 1 rle with old method : 0.0022602081298828125 time for calcul the mask position with numpy : 0.005699634552001953 nb_pixel_total : 8213 time to create 1 rle with old method : 0.008739233016967773 time for calcul the mask position with numpy : 0.006160736083984375 nb_pixel_total : 3490 time to create 1 rle with old method : 0.0037763118743896484 time for calcul the mask position with numpy : 0.006125211715698242 nb_pixel_total : 16202 time to create 1 rle with old method : 0.016968965530395508 create new chi : 0.5248532295227051 time to delete rle : 0.00035500526428222656 batch 1 Loaded 15 chid ids of type : 3594 ++++++++Number RLEs to save : 2216 TO DO : save crop sub photo not yet done ! save time : 0.4182851314544678 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 0.09016561508178711 time for calcul the mask position with numpy : 0.019882678985595703 nb_pixel_total : 2040101 time to create 1 rle with new method : 0.13047528266906738 time for calcul the mask position with numpy : 0.006478786468505859 nb_pixel_total : 8350 time to create 1 rle with old method : 0.009246349334716797 time for calcul the mask position with numpy : 0.0061151981353759766 nb_pixel_total : 11033 time to create 1 rle with old method : 0.013845682144165039 time for calcul the mask position with numpy : 0.006314516067504883 nb_pixel_total : 8986 time to create 1 rle with old method : 0.009768962860107422 time for calcul the mask position with numpy : 0.0061016082763671875 nb_pixel_total : 5130 time to create 1 rle with old method : 0.0058095455169677734 create new chi : 0.22153472900390625 time to delete rle : 0.00037097930908203125 batch 1 Loaded 9 chid ids of type : 3594 +++++Number RLEs to save : 2180 TO DO : save crop sub photo not yet done ! save time : 0.3898122310638428 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04284334182739258 time for calcul the mask position with numpy : 0.06579375267028809 nb_pixel_total : 1987102 time to create 1 rle with new method : 0.10082197189331055 time for calcul the mask position with numpy : 0.0067212581634521484 nb_pixel_total : 86498 time to create 1 rle with old method : 0.12071609497070312 create new chi : 0.3045217990875244 time to delete rle : 0.0002601146697998047 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2046 TO DO : save crop sub photo not yet done ! save time : 0.37854647636413574 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.03248429298400879 time for calcul the mask position with numpy : 0.10147857666015625 nb_pixel_total : 2069477 time to create 1 rle with new method : 0.08202099800109863 time for calcul the mask position with numpy : 0.0058896541595458984 nb_pixel_total : 4123 time to create 1 rle with old method : 0.0046062469482421875 create new chi : 0.20453166961669922 time to delete rle : 0.00027561187744140625 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1286 TO DO : save crop sub photo not yet done ! save time : 0.2824077606201172 map_output_result : {1386055752: (0.0, 'Should be the crop_list due to order', 0), 1386055737: (0.0, 'Should be the crop_list due to order', 0), 1386055735: (0.0, 'Should be the crop_list due to order', 0), 1386055732: (0.0, 'Should be the crop_list due to order', 0), 1386055729: (0.0, 'Should be the crop_list due to order', 0), 1386055726: (0.0, 'Should be the crop_list due to order', 0), 1386055660: (0.0, 'Should be the crop_list due to order', 0), 1386055656: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 8 /1386055752.Didn't retrieve data . /1386055737.Didn't retrieve data . /1386055735.Didn't retrieve data . /1386055732.Didn't retrieve data . /1386055729.Didn't retrieve data . /1386055726.Didn't retrieve data . /1386055660.Didn't retrieve data . /1386055656.Didn't retrieve data . before output type Used above Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.039618492126464844 save_final save missing photos in datou_result : time spend for datou_step_exec : 7.469688653945923 time spend to save output : 0.04002809524536133 total time spend for step 3 : 7.509716749191284 step4:ventilate_hashtags_in_portfolio Tue Sep 30 17:09:53 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 27223367 get user id for portfolio 27223367 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223367 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','metal','mal_croppe','flou','autre','papier','pet_fonce','carton','pet_clair','environnement','pehd')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223367 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','metal','mal_croppe','flou','autre','papier','pet_fonce','carton','pet_clair','environnement','pehd')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223367 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','metal','mal_croppe','flou','autre','papier','pet_fonce','carton','pet_clair','environnement','pehd')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27357295,27357296,27357297,27357298,27357299,27357300,27357301,27357302,27357303,27357304,27357305?tags=background,metal,mal_croppe,flou,autre,papier,pet_fonce,carton,pet_clair,environnement,pehd Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 1 /27223367. 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 ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.036925315856933594 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.517541408538818 time spend to save output : 0.03718161582946777 total time spend for step 4 : 5.554723024368286 step5:final Tue Sep 30 17:09:58 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! Catched exception ! Connect or reconnect ! Inside saveOutput : final : False verbose : 0 original output for save of step final : {1386055752: ('0.017385886863425924',), 1386055737: ('0.017385886863425924',), 1386055735: ('0.017385886863425924',), 1386055732: ('0.017385886863425924',), 1386055729: ('0.017385886863425924',), 1386055726: ('0.017385886863425924',), 1386055660: ('0.017385886863425924',), 1386055656: ('0.017385886863425924',)} new output for save of step final : {1386055752: ('0.017385886863425924',), 1386055737: ('0.017385886863425924',), 1386055735: ('0.017385886863425924',), 1386055732: ('0.017385886863425924',), 1386055729: ('0.017385886863425924',), 1386055726: ('0.017385886863425924',), 1386055660: ('0.017385886863425924',), 1386055656: ('0.017385886863425924',)} [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 8 /1386055752.Didn't retrieve data . /1386055737.Didn't retrieve data . /1386055735.Didn't retrieve data . /1386055732.Didn't retrieve data . /1386055729.Didn't retrieve data . /1386055726.Didn't retrieve data . /1386055660.Didn't retrieve data . /1386055656.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.035646677017211914 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.3683645725250244 time spend to save output : 0.03608560562133789 total time spend for step 5 : 0.4044501781463623 step6:blur_detection Tue Sep 30 17:09:59 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: ratio et variance treat image : temp/1759244948_374033_1386055752_f3eba266de0d4b30805a3b3da48814dc.jpg resize: (1080, 1920) 1386055752 1.3748845545098898 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816.jpg resize: (1080, 1920) 1386055737 -0.7799795048321276 treat image : temp/1759244948_374033_1386055735_0a500bdf9ab7ec79e17628249cda89ab.jpg resize: (1080, 1920) 1386055735 0.3372305637391682 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539.jpg resize: (1080, 1920) 1386055732 2.426683784433482 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e.jpg resize: (1080, 1920) 1386055729 -0.21355381318613753 treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7.jpg resize: (1080, 1920) 1386055726 2.179416440397793 treat image : temp/1759244948_374033_1386055660_8ca166e474cde9eb3607617acb81c68e.jpg resize: (1080, 1920) 1386055660 0.2237804311836582 treat image : temp/1759244948_374033_1386055656_454155fa37d98c41d3573652a06392e1.jpg resize: (1080, 1920) 1386055656 0.5457636679042179 treat image : temp/1759244948_374033_1386055752_f3eba266de0d4b30805a3b3da48814dc_rle_crop_3981111325_0.png resize: (96, 109) 1386984413 -1.3554215286828712 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111326_0.png resize: (180, 89) 1386984414 -0.9031166550255555 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111331_0.png resize: (102, 87) 1386984415 1.4733198919941775 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111327_0.png resize: (134, 103) 1386984416 -1.694800557984502 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111330_0.png resize: (103, 105) 1386984417 0.865125410057396 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111329_0.png resize: (147, 115) 1386984418 -1.4806555522780172 treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111328_0.png resize: (114, 123) 1386984419 -1.8599075846518391 treat image : temp/1759244948_374033_1386055735_0a500bdf9ab7ec79e17628249cda89ab_rle_crop_3981111332_0.png resize: (165, 117) 1386984420 -1.7392117793163662 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111335_0.png resize: (113, 73) 1386984421 -1.6823401879754205 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111337_0.png resize: (80, 78) 1386984422 -0.9537815047706747 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111336_0.png resize: (126, 104) 1386984424 -0.976378624017313 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111341_0.png resize: (38, 77) 1386984425 -0.5476119605998967 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111339_0.png resize: (100, 56) 1386984426 -1.02550324175104 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111343_0.png resize: (71, 100) 1386984427 -1.9863802416313823 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111338_0.png resize: (119, 160) 1386984428 3.135575727876303 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111342_0.png resize: (59, 49) 1386984429 2.0926171245181022 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111340_0.png resize: (100, 114) 1386984430 -1.3059577499104869 treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111347_0.png resize: (185, 106) 1386984431 -1.3083636820762565 treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111345_0.png resize: (94, 115) 1386984432 -1.900255383193227 treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111348_0.png resize: (98, 120) 1386984433 -1.3212326427788987 treat image : temp/1759244948_374033_1386055656_454155fa37d98c41d3573652a06392e1_rle_crop_3981111350_0.png resize: (103, 85) 1386984434 -2.0948503102633773 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111334_0.png resize: (154, 91) 1386984436 -0.9687675505894924 treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111344_0.png resize: (71, 56) 1386984437 -1.198508945580703 treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111346_0.png resize: (156, 100) 1386984438 -1.8461985726830161 treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111333_0.png resize: (210, 225) 1386984439 -0.5692749853870922 treat image : temp/1759244948_374033_1386055660_8ca166e474cde9eb3607617acb81c68e_rle_crop_3981111349_0.png resize: (481, 323) 1386984440 -0.004887269152780788 Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 34 time used for this insertion : 0.03525352478027344 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 34 time used for this insertion : 0.0360257625579834 save missing photos in datou_result : time spend for datou_step_exec : 6.786669015884399 time spend to save output : 0.08821797370910645 total time spend for step 6 : 6.874886989593506 step7:brightness Tue Sep 30 17:10:05 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness treat image : temp/1759244948_374033_1386055752_f3eba266de0d4b30805a3b3da48814dc.jpg treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816.jpg treat image : temp/1759244948_374033_1386055735_0a500bdf9ab7ec79e17628249cda89ab.jpg treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539.jpg treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e.jpg treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7.jpg treat image : temp/1759244948_374033_1386055660_8ca166e474cde9eb3607617acb81c68e.jpg treat image : temp/1759244948_374033_1386055656_454155fa37d98c41d3573652a06392e1.jpg treat image : temp/1759244948_374033_1386055752_f3eba266de0d4b30805a3b3da48814dc_rle_crop_3981111325_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111326_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111331_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111327_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111330_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111329_0.png treat image : temp/1759244948_374033_1386055737_46d465cd32d5f2a66bf6b58c2b237816_rle_crop_3981111328_0.png treat image : temp/1759244948_374033_1386055735_0a500bdf9ab7ec79e17628249cda89ab_rle_crop_3981111332_0.png treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111335_0.png treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111337_0.png treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111336_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111341_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111339_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111343_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111338_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111342_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111340_0.png treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111347_0.png treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111345_0.png treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111348_0.png treat image : temp/1759244948_374033_1386055656_454155fa37d98c41d3573652a06392e1_rle_crop_3981111350_0.png treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111334_0.png treat image : temp/1759244948_374033_1386055729_8a7c33e855d92c326ed84ddba1ac582e_rle_crop_3981111344_0.png treat image : temp/1759244948_374033_1386055726_59cf4cac024cb299655e3e99073aa5b7_rle_crop_3981111346_0.png treat image : temp/1759244948_374033_1386055732_0db8e45f50a5ce3a78c7b1413c777539_rle_crop_3981111333_0.png treat image : temp/1759244948_374033_1386055660_8ca166e474cde9eb3607617acb81c68e_rle_crop_3981111349_0.png Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 34 time used for this insertion : 0.03548288345336914 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 34 time used for this insertion : 0.03713202476501465 save missing photos in datou_result : time spend for datou_step_exec : 1.9629297256469727 time spend to save output : 0.08951973915100098 total time spend for step 7 : 2.0524494647979736 step8:velours_tree Tue Sep 30 17:10:07 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 can't find the photo_desc_type Inside saveOutput : final : False verbose : 0 ouput is None No outpout to save, returning out of save general time spend for datou_step_exec : 0.1628730297088623 time spend to save output : 3.170967102050781e-05 total time spend for step 8 : 0.1629047393798828 step9:send_mail_cod Tue Sep 30 17:10:08 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 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /home/admin in order to get the selector url, please entre the license of selector results_Auto_P27223367_30-09-2025_17_10_08.pdf 27357295 imagette273572951759245008 27357296 imagette273572961759245008 27357297 imagette273572971759245008 27357298 imagette273572981759245008 27357299 imagette273572991759245008 27357300 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273573001759245008 27357301 imagette273573011759245010 27357302 change filename to text .change filename to text .change filename to text .imagette273573021759245010 27357303 change filename to text .change filename to text .imagette273573031759245010 27357305 imagette273573051759245010 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27223367 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27357295,27357296,27357297,27357298,27357299,27357300,27357301,27357302,27357303,27357304,27357305?tags=background,metal,mal_croppe,flou,autre,papier,pet_fonce,carton,pet_clair,environnement,pehd args[1386055752] : ((1386055752, 1.3748845545098898, 492688767), (1386055752, 0.38577927059820327, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055737] : ((1386055737, -0.7799795048321276, 492688767), (1386055737, 0.855914508819441, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055735] : ((1386055735, 0.3372305637391682, 492688767), (1386055735, 0.8111786343194342, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055732] : ((1386055732, 2.426683784433482, 492688767), (1386055732, 0.7804593962284326, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055729] : ((1386055729, -0.21355381318613753, 492688767), (1386055729, 0.2721603280526642, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055726] : ((1386055726, 2.179416440397793, 492688767), (1386055726, 0.4360320894747485, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055660] : ((1386055660, 0.2237804311836582, 492688767), (1386055660, 0.5196546661482369, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com args[1386055656] : ((1386055656, 0.5457636679042179, 492688767), (1386055656, 0.7464964963322004, 2107752395), '0.017385886863425924') We are sending mail with results at report@fotonower.com refus_total : 0.017385886863425924 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos_view ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=27223367 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf results_Auto_P27223367_30-09-2025_17_10_08.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3318','27223367','results_Auto_P27223367_30-09-2025_17_10_08.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf','pdf','','0.12','0.017385886863425924') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27223367

https://www.fotonower.com/image?json=false&list_photos_id=1386055752
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.3748845545098898)
https://www.fotonower.com/image?json=false&list_photos_id=1386055737
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386055735
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386055732
La photo est trop floue, merci de reprendre une photo.(avec le score = 2.426683784433482)
https://www.fotonower.com/image?json=false&list_photos_id=1386055729
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386055726
La photo est trop floue, merci de reprendre une photo.(avec le score = 2.179416440397793)
https://www.fotonower.com/image?json=false&list_photos_id=1386055660
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386055656
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 1.74%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/27357300?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/27357302?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27357303?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27357295,27357296,27357297,27357298,27357299,27357300,27357301,27357302,27357303,27357304,27357305?tags=background,metal,mal_croppe,flou,autre,papier,pet_fonce,carton,pet_clair,environnement,pehd.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 30 Sep 2025 15:10:12 GMT Content-Length: 0 Connection: close X-Message-Id: tmJRs7IFRtGjNr7OCvb1dw Access-Control-Allow-Origin: https://sendgrid.api-docs.io Access-Control-Allow-Methods: POST Access-Control-Allow-Headers: Authorization, Content-Type, On-behalf-of, x-sg-elas-acl Access-Control-Max-Age: 600 X-No-CORS-Reason: https://sendgrid.com/docs/Classroom/Basics/API/cors.html Strict-Transport-Security: max-age=31536000; includeSubDomains Content-Security-Policy: frame-ancestors 'none' Cache-Control: no-cache X-Content-Type-Options: no-sniff Referrer-Policy: strict-origin-when-cross-origin Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : send_mail_cod we use saveGeneral [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 0 before output type Used above Managing all output in save final without adding information in the mtr_datou_result ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.03581404685974121 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.0823750495910645 time spend to save output : 0.036067962646484375 total time spend for step 9 : 4.118443012237549 step10:split_time_score Tue Sep 30 17:10:12 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 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', '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': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('10', 8),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 25092025 27223367 Nombre de photos uploadées : 8 / 23040 (0%) 25092025 27223367 Nombre de photos taguées (types de déchets): 0 / 8 (0%) 25092025 27223367 Nombre de photos taguées (volume) : 0 / 8 (0%) elapsed_time : load_data_split_time_score 2.1457672119140625e-06 elapsed_time : order_list_meta_photo_and_scores 5.4836273193359375e-06 ???????? elapsed_time : fill_and_build_computed_from_old_data 0.0005354881286621094 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6751723289489746 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.09845333397633747 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27221477_30-09-2025_16_57_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27221477 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27221477 AND mptpi.`type`=3594 To do Qualite : 0.13090677358906527 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223364_30-09-2025_17_01_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223364 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223364 AND mptpi.`type`=3594 To do Qualite : 0.017385886863425924 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223367 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223367 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223369 order by id desc limit 1 Qualite : 0.054117082281144785 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27224634_30-09-2025_17_02_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27224634 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! 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 ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27224634 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27224635 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27225428 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27228443 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27253365 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236083 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236085 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236088 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236093 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236096 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236099 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241406 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241410 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241422 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27247505 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27247506 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'25092025': {'nb_upload': 8, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1386055752, 1386055737, 1386055735, 1386055732, 1386055729, 1386055726, 1386055660, 1386055656] Looping around the photos to save general results len do output : 1 /27223367Didn'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 ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055752', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055737', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055735', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055732', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055729', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055726', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055660', None, None, None, None, None, '3777284') ('3318', None, None, None, None, None, None, None, '3777284') ('3318', '27223367', '1386055656', None, None, None, None, None, '3777284') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.036478281021118164 save_final save missing photos in datou_result : time spend for datou_step_exec : 11.995588779449463 time spend to save output : 0.036712646484375 total time spend for step 10 : 12.032301425933838 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 8 set_done_treatment 26.36user 17.66system 1:18.26elapsed 56%CPU (0avgtext+0avgdata 2747724maxresident)k 16368inputs+7048outputs (214major+1350659minor)pagefaults 0swaps