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 3787392' -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 : 392024 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 : ['3787392'] with mtr_portfolio_ids : ['27292772'] and first list_photo_ids : [] new path : /proc/392024/ 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 : 1.639491319656372 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 17:18:30 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 17:18:34.231616: 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 17:18:34.260581: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-30 17:18:34.263692: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4f60000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:18:34.263755: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-30 17:18:34.268999: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-30 17:18:34.436935: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x29fcb5a0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:18:34.437003: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-30 17:18:34.438480: 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 17:18:34.440109: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:18:34.456814: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:18:34.465278: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:18:34.467007: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:18:34.484143: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:18:34.487228: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:18:34.519907: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:18:34.521785: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:18:34.521891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:18:34.522921: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:18:34.522941: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:18:34.522954: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:18:34.525065: 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 17:18:34.971486: 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 17:18:34.971586: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:18:34.971608: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:18:34.971626: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:18:34.971643: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:18:34.971661: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:18:34.971678: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:18:34.971696: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:18:34.973268: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:18:34.974585: 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 17:18:34.974628: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:18:34.974653: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:18:34.974671: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:18:34.974687: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:18:34.974704: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:18:34.974721: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:18:34.974738: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:18:34.976288: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:18:34.976317: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:18:34.976327: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:18:34.976337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:18:34.977949: 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 17:18:44.109071: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:18:44.367145: 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: 38.00000 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: 17.00000 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 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 27.00000 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: 5.00000 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 : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 10.00000 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: 27.00000 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 : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 19.00000 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 : 1 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 25.00000 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 Detection mask done ! Trying to reset tf kernel 392176 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 : 0.0003933906555175781 nb_pixel_total : 7841 time to create 1 rle with old method : 0.009185075759887695 length of segment : 167 time for calcul the mask position with numpy : 0.002054452896118164 nb_pixel_total : 113906 time to create 1 rle with old method : 0.1281142234802246 length of segment : 532 time for calcul the mask position with numpy : 0.0010099411010742188 nb_pixel_total : 80635 time to create 1 rle with old method : 0.09251642227172852 length of segment : 213 time for calcul the mask position with numpy : 0.00055694580078125 nb_pixel_total : 30754 time to create 1 rle with old method : 0.04768943786621094 length of segment : 328 time for calcul the mask position with numpy : 0.0002913475036621094 nb_pixel_total : 16325 time to create 1 rle with old method : 0.018967390060424805 length of segment : 150 time for calcul the mask position with numpy : 0.00037550926208496094 nb_pixel_total : 21028 time to create 1 rle with old method : 0.024652719497680664 length of segment : 130 time for calcul the mask position with numpy : 8.654594421386719e-05 nb_pixel_total : 2391 time to create 1 rle with old method : 0.0028183460235595703 length of segment : 72 time for calcul the mask position with numpy : 0.05592179298400879 nb_pixel_total : 818449 time to create 1 rle with new method : 0.06534814834594727 length of segment : 1024 time for calcul the mask position with numpy : 0.0004458427429199219 nb_pixel_total : 26685 time to create 1 rle with old method : 0.027988195419311523 length of segment : 157 time for calcul the mask position with numpy : 0.00020170211791992188 nb_pixel_total : 4421 time to create 1 rle with old method : 0.0050258636474609375 length of segment : 200 time for calcul the mask position with numpy : 0.00015497207641601562 nb_pixel_total : 4620 time to create 1 rle with old method : 0.0051000118255615234 length of segment : 152 time for calcul the mask position with numpy : 0.010864019393920898 nb_pixel_total : 725516 time to create 1 rle with new method : 0.1768040657043457 length of segment : 943 time for calcul the mask position with numpy : 0.001676321029663086 nb_pixel_total : 110601 time to create 1 rle with old method : 0.11722874641418457 length of segment : 562 time for calcul the mask position with numpy : 0.00015211105346679688 nb_pixel_total : 6088 time to create 1 rle with old method : 0.007174253463745117 length of segment : 82 time for calcul the mask position with numpy : 0.0005517005920410156 nb_pixel_total : 32885 time to create 1 rle with old method : 0.03568124771118164 length of segment : 357 time spent for convertir_results : 2.647430658340454 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 15 chid ids of type : 3594 Number RLEs to save : 5069 save missing photos in datou_result : time spend for datou_step_exec : 27.17460536956787 time spend to save output : 0.7669777870178223 total time spend for step 1 : 27.941583156585693 step2:crop_condition Tue Sep 30 17:18:58 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 ! 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 15 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 ! map_result returned by crop_photo_return_map_crop : length : 5 About to insert : list_path_to_insert length 5 new photo from crops ! About to upload 5 photos upload in portfolio : 3736932 init cache_photo without model_param we have 5 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245539_392024 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(1759245540), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448755_a8b52e518df6e577a7a6b980a0e08b3f_rle_crop_3981121850_0.png', 0, 99, 167, 0, 1759245540,'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(1759245540), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121854_0.png', 0, 144, 149, 0, 1759245540,'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(1759245540), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121856_0.png', 0, 40, 72, 0, 1759245540,'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(1759245540), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121860_0.png', 0, 81, 142, 0, 1759245540,'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(1759245540), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121859_0.png', 0, 123, 200, 0, 1759245540,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 5 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.9805705547332764 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 begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 1 About to insert : list_path_to_insert length 1 new photo from crops ! About to upload 1 photos upload in portfolio : 3736932 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245541_392024 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(1759245541), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121863_0.png', 0, 112, 76, 0, 1759245541,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 1 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.712787389755249 we have finished the crop for the class : metal 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 ! 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 : 6 About to insert : list_path_to_insert length 6 new photo from crops ! About to upload 6 photos upload in portfolio : 3736932 init cache_photo without model_param we have 6 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245550_392024 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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121852_0.png', 0, 578, 185, 0, 1759245551,'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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121851_0.png', 0, 346, 531, 0, 1759245551,'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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121857_0.png', 0, 1228, 971, 0, 1759245551,'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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121858_0.png', 0, 244, 157, 0, 1759245551,'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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448720_2b1e43acce4435e9f7a4b5a222305195_rle_crop_3981121861_0.png', 0, 1081, 940, 0, 1759245551,'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(1759245551), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121862_0.png', 0, 345, 561, 0, 1759245551,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 6 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.1605308055877686 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 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/1759245552_392024 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(1759245553), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121853_0.png', 0, 140, 328, 0, 1759245553,'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(1759245553), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121855_0.png', 0, 200, 130, 0, 1759245553,'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(1759245553), 0.0, 0.0, 14, '', 0, 0, '1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121864_0.png', 0, 143, 357, 0, 1759245553,'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 : 1.3533706665039062 we have finished the crop for the class : autre 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] Looping around the photos to save general results len do output : 15 /1386986067Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986070Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986071Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986072Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986073Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986077Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986104Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986105Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986106Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986107Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986108Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986109Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986111Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986113Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386986114Didn'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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 53 time used for this insertion : 0.03719639778137207 save_final save missing photos in datou_result : time spend for datou_step_exec : 15.518235206604004 time spend to save output : 0.03800344467163086 total time spend for step 2 : 15.556238651275635 step3:rle_unique_nms_with_priority Tue Sep 30 17:19:13 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 15 chid ids of type : 3594 +++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.553863525390625 time for calcul the mask position with numpy : 0.1495952606201172 nb_pixel_total : 2065759 time to create 1 rle with new method : 0.2623565196990967 time for calcul the mask position with numpy : 0.006826877593994141 nb_pixel_total : 7841 time to create 1 rle with old method : 0.008761405944824219 create new chi : 0.43715500831604004 time to delete rle : 0.10225701332092285 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1414 TO DO : save crop sub photo not yet done ! save time : 0.29497694969177246 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.3228161334991455 time for calcul the mask position with numpy : 0.24795866012573242 nb_pixel_total : 1848305 time to create 1 rle with new method : 0.09052777290344238 time for calcul the mask position with numpy : 0.007221221923828125 nb_pixel_total : 30754 time to create 1 rle with old method : 0.032766103744506836 time for calcul the mask position with numpy : 0.006661891937255859 nb_pixel_total : 80635 time to create 1 rle with old method : 0.08788371086120605 time for calcul the mask position with numpy : 0.00705409049987793 nb_pixel_total : 113906 time to create 1 rle with old method : 0.12987542152404785 create new chi : 0.620659351348877 time to delete rle : 0.00044417381286621094 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3226 TO DO : save crop sub photo not yet done ! save time : 0.5433921813964844 No data in photo_id : 1386448750 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.04994678497314453 time for calcul the mask position with numpy : 0.2027137279510498 nb_pixel_total : 2036247 time to create 1 rle with new method : 0.0888676643371582 time for calcul the mask position with numpy : 0.0061686038970947266 nb_pixel_total : 21028 time to create 1 rle with old method : 0.022969484329223633 time for calcul the mask position with numpy : 0.005965232849121094 nb_pixel_total : 16325 time to create 1 rle with old method : 0.017596006393432617 create new chi : 0.3528575897216797 time to delete rle : 0.00027489662170410156 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1640 TO DO : save crop sub photo not yet done ! save time : 0.32811522483825684 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.05640435218811035 time for calcul the mask position with numpy : 0.16051816940307617 nb_pixel_total : 1228466 time to create 1 rle with new method : 0.10724139213562012 time for calcul the mask position with numpy : 0.006388425827026367 nb_pixel_total : 26685 time to create 1 rle with old method : 0.029267311096191406 time for calcul the mask position with numpy : 0.012503385543823242 nb_pixel_total : 816058 time to create 1 rle with new method : 0.16649603843688965 time for calcul the mask position with numpy : 0.005908012390136719 nb_pixel_total : 2391 time to create 1 rle with old method : 0.002727508544921875 create new chi : 0.5008394718170166 time to delete rle : 0.0004432201385498047 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3586 TO DO : save crop sub photo not yet done ! save time : 0.5417625904083252 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.1032712459564209 time for calcul the mask position with numpy : 0.06419086456298828 nb_pixel_total : 2064559 time to create 1 rle with new method : 0.187469482421875 time for calcul the mask position with numpy : 0.006535530090332031 nb_pixel_total : 4620 time to create 1 rle with old method : 0.005170106887817383 time for calcul the mask position with numpy : 0.0060274600982666016 nb_pixel_total : 4421 time to create 1 rle with old method : 0.0049648284912109375 create new chi : 0.2837228775024414 time to delete rle : 0.00046634674072265625 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1784 TO DO : save crop sub photo not yet done ! save time : 0.31429457664489746 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.03893017768859863 time for calcul the mask position with numpy : 0.02095341682434082 nb_pixel_total : 1348084 time to create 1 rle with new method : 0.22873282432556152 time for calcul the mask position with numpy : 0.012579917907714844 nb_pixel_total : 725516 time to create 1 rle with new method : 0.1262657642364502 create new chi : 0.39662957191467285 time to delete rle : 0.000274658203125 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2966 TO DO : save crop sub photo not yet done ! save time : 0.45167088508605957 nb_obj : 3 nb_hashtags : 3 time to prepare the origin masks : 0.4024994373321533 time for calcul the mask position with numpy : 0.0705254077911377 nb_pixel_total : 1924026 time to create 1 rle with new method : 0.12212061882019043 time for calcul the mask position with numpy : 0.006826877593994141 nb_pixel_total : 32885 time to create 1 rle with old method : 0.0370945930480957 time for calcul the mask position with numpy : 0.006546735763549805 nb_pixel_total : 6088 time to create 1 rle with old method : 0.00694584846496582 time for calcul the mask position with numpy : 0.00689697265625 nb_pixel_total : 110601 time to create 1 rle with old method : 0.1278984546661377 create new chi : 0.3957235813140869 time to delete rle : 0.0004990100860595703 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3082 TO DO : save crop sub photo not yet done ! save time : 0.5379636287689209 map_output_result : {1386448755: (0.0, 'Should be the crop_list due to order', 0), 1386448752: (0.0, 'Should be the crop_list due to order', 0), 1386448750: (0.0, 'Should be the crop_list due to order', 0.0), 1386448749: (0.0, 'Should be the crop_list due to order', 0), 1386448746: (0.0, 'Should be the crop_list due to order', 0), 1386448722: (0.0, 'Should be the crop_list due to order', 0), 1386448720: (0.0, 'Should be the crop_list due to order', 0), 1386448717: (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 [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] Looping around the photos to save general results len do output : 8 /1386448755.Didn't retrieve data . /1386448752.Didn't retrieve data . /1386448750.Didn't retrieve data . /1386448749.Didn't retrieve data . /1386448746.Didn't retrieve data . /1386448722.Didn't retrieve data . /1386448720.Didn't retrieve data . /1386448717.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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.036228179931640625 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.052648305892944 time spend to save output : 0.036661624908447266 total time spend for step 3 : 8.089309930801392 step4:ventilate_hashtags_in_portfolio Tue Sep 30 17:19:21 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 : 27292772 get user id for portfolio 27292772 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`=27292772 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','papier','metal','mal_croppe','carton','flou','environnement','background','pet_clair','autre','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`=27292772 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','papier','metal','mal_croppe','carton','flou','environnement','background','pet_clair','autre','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`=27292772 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','papier','metal','mal_croppe','carton','flou','environnement','background','pet_clair','autre','pehd')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27357853,27357854,27357855,27357856,27357857,27357858,27357859,27357860,27357861,27357862,27357863?tags=pet_fonce,papier,metal,mal_croppe,carton,flou,environnement,background,pet_clair,autre,pehd Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] Looping around the photos to save general results len do output : 1 /27292772. 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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.03825020790100098 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.556739330291748 time spend to save output : 0.038533926010131836 total time spend for step 4 : 5.59527325630188 step5:final Tue Sep 30 17:19:27 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 : {1386448755: ('0.12054844232253087',), 1386448752: ('0.12054844232253087',), 1386448750: ('0.12054844232253087',), 1386448749: ('0.12054844232253087',), 1386448746: ('0.12054844232253087',), 1386448722: ('0.12054844232253087',), 1386448720: ('0.12054844232253087',), 1386448717: ('0.12054844232253087',)} new output for save of step final : {1386448755: ('0.12054844232253087',), 1386448752: ('0.12054844232253087',), 1386448750: ('0.12054844232253087',), 1386448749: ('0.12054844232253087',), 1386448746: ('0.12054844232253087',), 1386448722: ('0.12054844232253087',), 1386448720: ('0.12054844232253087',), 1386448717: ('0.12054844232253087',)} [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] Looping around the photos to save general results len do output : 8 /1386448755.Didn't retrieve data . /1386448752.Didn't retrieve data . /1386448750.Didn't retrieve data . /1386448749.Didn't retrieve data . /1386448746.Didn't retrieve data . /1386448722.Didn't retrieve data . /1386448720.Didn't retrieve data . /1386448717.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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.038001060485839844 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.4072585105895996 time spend to save output : 0.03849339485168457 total time spend for step 5 : 0.4457519054412842 step6:blur_detection Tue Sep 30 17:19:27 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/1759245508_392024_1386448755_a8b52e518df6e577a7a6b980a0e08b3f.jpg resize: (1080, 1920) 1386448755 -0.5240211456134054 treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc.jpg resize: (1080, 1920) 1386448752 -3.5446382939505443 treat image : temp/1759245508_392024_1386448750_d1b9791166d250c90d3a3599f4d31536.jpg resize: (1080, 1920) 1386448750 -1.440705140028891 treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669.jpg resize: (1080, 1920) 1386448749 -2.3016936429146666 treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297.jpg resize: (1080, 1920) 1386448746 -0.16080165258496693 treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201.jpg resize: (1080, 1920) 1386448722 -4.522924634356253 treat image : temp/1759245508_392024_1386448720_2b1e43acce4435e9f7a4b5a222305195.jpg resize: (1080, 1920) 1386448720 -1.8947757881855463 treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c.jpg resize: (1080, 1920) 1386448717 -4.976163226536237 treat image : temp/1759245508_392024_1386448755_a8b52e518df6e577a7a6b980a0e08b3f_rle_crop_3981121850_0.png resize: (167, 99) 1386986067 -2.0043684011260154 treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121854_0.png resize: (149, 144) 1386986070 -0.9356017469303876 treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121856_0.png resize: (72, 40) 1386986071 4.639575124798534 treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121860_0.png resize: (142, 81) 1386986072 -2.510896270757096 treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121859_0.png resize: (200, 123) 1386986073 -3.1873057711505317 treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121863_0.png resize: (76, 112) 1386986077 -3.4892547296459098 treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121852_0.png resize: (185, 578) 1386986104 -3.645999823384875 treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121851_0.png resize: (531, 346) 1386986105 0.35940317764663643 treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121857_0.png resize: (971, 1228) 1386986106 -0.13006652289356577 treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121858_0.png resize: (157, 244) 1386986107 -1.6104039557936844 treat image : temp/1759245508_392024_1386448720_2b1e43acce4435e9f7a4b5a222305195_rle_crop_3981121861_0.png resize: (940, 1081) 1386986108 -0.39716321382427444 treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121862_0.png resize: (561, 345) 1386986109 0.19622931100612687 treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121853_0.png resize: (328, 140) 1386986111 -1.288853804238346 treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121855_0.png resize: (130, 200) 1386986113 -0.12117138958429198 treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121864_0.png resize: (357, 143) 1386986114 -1.2766586760317213 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 : 23 time used for this insertion : 0.03752017021179199 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 23 time used for this insertion : 0.0380709171295166 save missing photos in datou_result : time spend for datou_step_exec : 7.650997161865234 time spend to save output : 0.09364914894104004 total time spend for step 6 : 7.744646310806274 step7:brightness Tue Sep 30 17:19:35 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/1759245508_392024_1386448755_a8b52e518df6e577a7a6b980a0e08b3f.jpg treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc.jpg treat image : temp/1759245508_392024_1386448750_d1b9791166d250c90d3a3599f4d31536.jpg treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669.jpg treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297.jpg treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201.jpg treat image : temp/1759245508_392024_1386448720_2b1e43acce4435e9f7a4b5a222305195.jpg treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c.jpg treat image : temp/1759245508_392024_1386448755_a8b52e518df6e577a7a6b980a0e08b3f_rle_crop_3981121850_0.png treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121854_0.png treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121856_0.png treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121860_0.png treat image : temp/1759245508_392024_1386448722_7ee6c96117148fdb2798ec70b831e201_rle_crop_3981121859_0.png treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121863_0.png treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121852_0.png treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121851_0.png treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121857_0.png treat image : temp/1759245508_392024_1386448746_87057387a172c82ab1276de72ee60297_rle_crop_3981121858_0.png treat image : temp/1759245508_392024_1386448720_2b1e43acce4435e9f7a4b5a222305195_rle_crop_3981121861_0.png treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121862_0.png treat image : temp/1759245508_392024_1386448752_71d95081aef26bdf031f4e7bb2c5a8fc_rle_crop_3981121853_0.png treat image : temp/1759245508_392024_1386448749_f2b84c14124ed4c0439374bdee1e3669_rle_crop_3981121855_0.png treat image : temp/1759245508_392024_1386448717_5a73b9420a768968cba6d81bbf38859c_rle_crop_3981121864_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 : 23 time used for this insertion : 0.03995490074157715 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 23 time used for this insertion : 0.036561012268066406 save missing photos in datou_result : time spend for datou_step_exec : 2.2624258995056152 time spend to save output : 0.09552645683288574 total time spend for step 7 : 2.357952356338501 step8:velours_tree Tue Sep 30 17:19:38 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 : 0.16861391067504883 time spend to save output : 4.029273986816406e-05 total time spend for step 8 : 0.168654203414917 step9:send_mail_cod Tue Sep 30 17:19:38 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_P27292772_30-09-2025_17_19_38.pdf 27357853 imagette273578531759245578 27357854 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273578541759245578 27357855 change filename to text .imagette273578551759245578 27357856 imagette273578561759245578 27357857 imagette273578571759245578 27357858 imagette273578581759245578 27357860 imagette273578601759245578 27357861 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273578611759245578 27357862 change filename to text .change filename to text .change filename to text .imagette273578621759245579 27357863 imagette273578631759245579 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27292772 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27357853,27357854,27357855,27357856,27357857,27357858,27357859,27357860,27357861,27357862,27357863?tags=pet_fonce,papier,metal,mal_croppe,carton,flou,environnement,background,pet_clair,autre,pehd args[1386448755] : ((1386448755, -0.5240211456134054, 492688767), (1386448755, 0.6936269137692962, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448752] : ((1386448752, -3.5446382939505443, 492609224), (1386448752, 0.20809625040133023, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448750] : ((1386448750, -1.440705140028891, 492688767), (1386448750, 0.4863885396265319, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448749] : ((1386448749, -2.3016936429146666, 492609224), (1386448749, 0.19633216887740823, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448746] : ((1386448746, -0.16080165258496693, 492688767), (1386448746, 0.23436243995692224, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448722] : ((1386448722, -4.522924634356253, 492609224), (1386448722, 0.4158862913849265, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448720] : ((1386448720, -1.8947757881855463, 492688767), (1386448720, 0.3424347489074694, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com args[1386448717] : ((1386448717, -4.976163226536237, 492609224), (1386448717, 0.317941979200966, 2107752395), '0.12054844232253087') We are sending mail with results at report@fotonower.com refus_total : 0.12054844232253087 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=27292772 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_P27292772_30-09-2025_17_19_38.pdf results_Auto_P27292772_30-09-2025_17_19_38.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27292772_30-09-2025_17_19_38.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','27292772','results_Auto_P27292772_30-09-2025_17_19_38.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27292772_30-09-2025_17_19_38.pdf','pdf','','0.28','0.12054844232253087') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27292772

https://www.fotonower.com/image?json=false&list_photos_id=1386448755
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448752
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448750
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448749
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448746
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448722
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448720
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386448717
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 12.05%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/27357854?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/27357855?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27357861?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27357862?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27292772_30-09-2025_17_19_38.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27357853,27357854,27357855,27357856,27357857,27357858,27357859,27357860,27357861,27357862,27357863?tags=pet_fonce,papier,metal,mal_croppe,carton,flou,environnement,background,pet_clair,autre,pehd.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 30 Sep 2025 15:19:41 GMT Content-Length: 0 Connection: close X-Message-Id: FssIFwdHQyOdHjtpPejCtw 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 [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] 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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.039728403091430664 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.6626675128936768 time spend to save output : 0.0399777889251709 total time spend for step 9 : 3.7026453018188477 step10:split_time_score Tue Sep 30 17:19:41 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'}] (('20', 8),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 26092025 27292772 Nombre de photos uploadées : 8 / 23040 (0%) 26092025 27292772 Nombre de photos taguées (types de déchets): 0 / 8 (0%) 26092025 27292772 Nombre de photos taguées (volume) : 0 / 8 (0%) elapsed_time : load_data_split_time_score 1.9073486328125e-06 elapsed_time : order_list_meta_photo_and_scores 6.4373016357421875e-06 ???????? elapsed_time : fill_and_build_computed_from_old_data 0.0004737377166748047 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6477322578430176 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 : 0.17980704089506166 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27274393_30-09-2025_17_17_43.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27274393 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`=27274393 AND mptpi.`type`=3594 To do Qualite : 0.051351292438271606 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27274396_30-09-2025_17_18_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27274396 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`=27274396 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27277522 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27281338 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27284362 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27284365 order by id desc limit 1 Qualite : 0.12054844232253087 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27292772_30-09-2025_17_19_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27292772 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`=27292772 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'26092025': {'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 [1386448755, 1386448752, 1386448750, 1386448749, 1386448746, 1386448722, 1386448720, 1386448717] Looping around the photos to save general results len do output : 1 /27292772Didn'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, '3787392') ('3318', '27292772', '1386448755', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448752', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448750', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448749', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448746', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448722', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448720', None, None, None, None, None, '3787392') ('3318', None, None, None, None, None, None, None, '3787392') ('3318', '27292772', '1386448717', None, None, None, None, None, '3787392') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.03693675994873047 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.4987499713897705 time spend to save output : 0.03720235824584961 total time spend for step 10 : 4.53595232963562 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 35.80user 19.99system 1:19.98elapsed 69%CPU (0avgtext+0avgdata 2637864maxresident)k 940232inputs+18944outputs (10590major+1316536minor)pagefaults 0swaps