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 3793825' -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 : 371017 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 : ['3793825'] with mtr_portfolio_ids : ['27344240'] and first list_photo_ids : [] new path : /proc/371017/ 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 , BFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 10 ; length of list_pids : 10 ; length of list_args : 10 time to download the photos : 1.9034762382507324 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 17:07:13 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 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 17:07:16.136899: 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 17:07:16.164555: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-30 17:07:16.166783: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f52cc000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:07:16.166826: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-30 17:07:16.170703: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-30 17:07:16.368397: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x34489260 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:07:16.368468: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-30 17:07:16.369994: 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 17:07:16.370925: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:07:16.378157: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:07:16.383134: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:07:16.384025: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:07:16.391013: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:07:16.392613: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:07:16.400312: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:07:16.402182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:07:16.402283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:07:16.403246: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:07:16.403267: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:07:16.403279: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:07:16.404963: 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 17:07:16.838131: 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 17:07:16.838252: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:07:16.838286: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:07:16.838316: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:07:16.838344: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:07:16.838373: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:07:16.838400: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:07:16.838428: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:07:16.840621: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:07:16.841895: 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 17:07:16.841931: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:07:16.841947: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:07:16.841961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:07:16.841975: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:07:16.841989: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:07:16.842003: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:07:16.842017: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:07:16.843302: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:07:16.843332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:07:16.843340: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:07:16.843348: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:07:16.844692: 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 17:07:25.178489: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:07:25.362947: 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 : 10 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 : 3 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 : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 24.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 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: 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 : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 24.00000 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: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 22.00000 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: 31.00000 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: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 Detection mask done ! Trying to reset tf kernel 371200 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5290 tf kernel not reseted sub process len(results) : 10 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 10 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 : 0.00023484230041503906 nb_pixel_total : 6645 time to create 1 rle with old method : 0.007581472396850586 length of segment : 142 time for calcul the mask position with numpy : 0.00011110305786132812 nb_pixel_total : 4822 time to create 1 rle with old method : 0.0055234432220458984 length of segment : 81 time for calcul the mask position with numpy : 0.028080224990844727 nb_pixel_total : 727799 time to create 1 rle with new method : 0.04458737373352051 length of segment : 875 time for calcul the mask position with numpy : 0.00012421607971191406 nb_pixel_total : 3671 time to create 1 rle with old method : 0.0042111873626708984 length of segment : 62 time for calcul the mask position with numpy : 0.0651857852935791 nb_pixel_total : 1244862 time to create 1 rle with new method : 0.07907247543334961 length of segment : 1126 time for calcul the mask position with numpy : 0.00011539459228515625 nb_pixel_total : 3673 time to create 1 rle with old method : 0.0040111541748046875 length of segment : 133 time for calcul the mask position with numpy : 0.015685319900512695 nb_pixel_total : 1153197 time to create 1 rle with new method : 0.06715750694274902 length of segment : 1136 time for calcul the mask position with numpy : 0.001415252685546875 nb_pixel_total : 110365 time to create 1 rle with old method : 0.11613702774047852 length of segment : 506 time for calcul the mask position with numpy : 9.894371032714844e-05 nb_pixel_total : 4311 time to create 1 rle with old method : 0.004815578460693359 length of segment : 64 time for calcul the mask position with numpy : 0.01675581932067871 nb_pixel_total : 1160477 time to create 1 rle with new method : 0.06722044944763184 length of segment : 1657 time for calcul the mask position with numpy : 0.00016498565673828125 nb_pixel_total : 9464 time to create 1 rle with old method : 0.010287284851074219 length of segment : 109 time for calcul the mask position with numpy : 8.058547973632812e-05 nb_pixel_total : 3681 time to create 1 rle with old method : 0.004107475280761719 length of segment : 60 time for calcul the mask position with numpy : 0.011214971542358398 nb_pixel_total : 741173 time to create 1 rle with new method : 0.04675602912902832 length of segment : 987 time for calcul the mask position with numpy : 0.0001494884490966797 nb_pixel_total : 2522 time to create 1 rle with old method : 0.002936840057373047 length of segment : 47 time for calcul the mask position with numpy : 0.0029289722442626953 nb_pixel_total : 109119 time to create 1 rle with old method : 0.11623144149780273 length of segment : 529 time spent for convertir_results : 2.4765737056732178 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 : 7514 save missing photos in datou_result : time spend for datou_step_exec : 24.730287551879883 time spend to save output : 1.0440540313720703 total time spend for step 1 : 25.774341583251953 step2:crop_condition Tue Sep 30 17:07:39 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 : 10 ! 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 ! 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/1759244859_371017 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(1759244859), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108232_0.png', 0, 78, 56, 0, 1759244859,'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 : 0.661339282989502 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 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 ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 13 About to insert : list_path_to_insert length 13 new photo from crops ! About to upload 13 photos upload in portfolio : 3736932 init cache_photo without model_param we have 13 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759244881_371017 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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891922_905acfa1d0c7361b043a50c1eedd7d48_rle_crop_3981108221_0.png', 0, 61, 142, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108223_0.png', 0, 1037, 875, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108222_0.png', 0, 77, 81, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108225_0.png', 0, 1445, 1009, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108224_0.png', 0, 98, 62, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891876_dae20f3c67839d5f1df1b47290e92092_rle_crop_3981108227_0.png', 0, 1331, 1006, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108230_0.png', 0, 1350, 968, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108229_0.png', 0, 93, 64, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108228_0.png', 0, 349, 500, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891872_30890afb608f8ce6255786fcbb493a1e_rle_crop_3981108231_0.png', 0, 105, 109, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108233_0.png', 0, 996, 984, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108234_0.png', 0, 64, 46, 0, 1759244884,'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(1759244884), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108235_0.png', 0, 351, 526, 0, 1759244884,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 13 photos in the portfolio 3736932 time of upload the photos Elapsed time : 4.568855047225952 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 ! 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/1759244886_371017 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(1759244886), 0.0, 0.0, 14, '', 0, 0, '1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108226_0.png', 0, 39, 133, 0, 1759244886,'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 : 0.662663459777832 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 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 [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] Looping around the photos to save general results len do output : 15 /1386983894Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983905Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983906Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983907Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983908Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983909Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983911Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983912Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983913Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983914Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983915Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983916Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983917Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983918Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386983919Didn'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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 55 time used for this insertion : 0.037988901138305664 save_final save missing photos in datou_result : time spend for datou_step_exec : 27.734586477279663 time spend to save output : 0.03881669044494629 total time spend for step 2 : 27.77340316772461 step3:rle_unique_nms_with_priority Tue Sep 30 17:08:06 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 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 : 0.2541964054107666 time for calcul the mask position with numpy : 0.14312338829040527 nb_pixel_total : 2066955 time to create 1 rle with new method : 0.2494966983795166 time for calcul the mask position with numpy : 0.0061244964599609375 nb_pixel_total : 6645 time to create 1 rle with old method : 0.007407426834106445 create new chi : 0.41664576530456543 time to delete rle : 0.11888551712036133 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1364 TO DO : save crop sub photo not yet done ! save time : 0.2883110046386719 No data in photo_id : 1386891917 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.14293980598449707 time for calcul the mask position with numpy : 0.13689899444580078 nb_pixel_total : 1340979 time to create 1 rle with new method : 0.07823657989501953 time for calcul the mask position with numpy : 0.010557174682617188 nb_pixel_total : 727799 time to create 1 rle with new method : 0.1541593074798584 time for calcul the mask position with numpy : 0.005621671676635742 nb_pixel_total : 4822 time to create 1 rle with old method : 0.005212068557739258 create new chi : 0.4002110958099365 time to delete rle : 0.00040340423583984375 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2992 TO DO : save crop sub photo not yet done ! save time : 0.43812060356140137 No data in photo_id : 1386891879 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.05581545829772949 time for calcul the mask position with numpy : 0.011402130126953125 nb_pixel_total : 825903 time to create 1 rle with new method : 0.18726277351379395 time for calcul the mask position with numpy : 0.0057561397552490234 nb_pixel_total : 744 time to create 1 rle with old method : 0.0008132457733154297 time for calcul the mask position with numpy : 0.03914070129394531 nb_pixel_total : 1243282 time to create 1 rle with new method : 0.16791987419128418 time for calcul the mask position with numpy : 0.0061359405517578125 nb_pixel_total : 3671 time to create 1 rle with old method : 0.004216194152832031 create new chi : 0.4379899501800537 time to delete rle : 0.0004551410675048828 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3502 TO DO : save crop sub photo not yet done ! save time : 0.5357859134674072 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.037624359130859375 time for calcul the mask position with numpy : 0.011895179748535156 nb_pixel_total : 920403 time to create 1 rle with new method : 0.07572221755981445 time for calcul the mask position with numpy : 0.013845443725585938 nb_pixel_total : 1153197 time to create 1 rle with new method : 0.030348539352416992 create new chi : 0.13227295875549316 time to delete rle : 0.0003101825714111328 batch 1 Loaded 3 chid ids of type : 3594 ++Number RLEs to save : 3352 TO DO : save crop sub photo not yet done ! save time : 0.45981526374816895 nb_obj : 3 nb_hashtags : 1 time to prepare the origin masks : 0.32582759857177734 time for calcul the mask position with numpy : 0.029097795486450195 nb_pixel_total : 798447 time to create 1 rle with new method : 0.08409905433654785 time for calcul the mask position with numpy : 0.11266732215881348 nb_pixel_total : 1160477 time to create 1 rle with new method : 0.07532906532287598 time for calcul the mask position with numpy : 0.005969524383544922 nb_pixel_total : 4311 time to create 1 rle with old method : 0.00466156005859375 time for calcul the mask position with numpy : 0.006409406661987305 nb_pixel_total : 110365 time to create 1 rle with old method : 0.11790823936462402 create new chi : 0.4522089958190918 time to delete rle : 0.0006833076477050781 batch 1 Loaded 7 chid ids of type : 3594 ++++++Number RLEs to save : 5534 TO DO : save crop sub photo not yet done ! save time : 0.77573561668396 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.05271506309509277 time for calcul the mask position with numpy : 0.019591331481933594 nb_pixel_total : 2064136 time to create 1 rle with new method : 0.22002458572387695 time for calcul the mask position with numpy : 0.006300687789916992 nb_pixel_total : 9464 time to create 1 rle with old method : 0.010514497756958008 create new chi : 0.2637481689453125 time to delete rle : 0.0002446174621582031 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1298 TO DO : save crop sub photo not yet done ! save time : 0.2710690498352051 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.044908761978149414 time for calcul the mask position with numpy : 0.04708218574523926 nb_pixel_total : 1328746 time to create 1 rle with new method : 0.25121402740478516 time for calcul the mask position with numpy : 0.010619401931762695 nb_pixel_total : 741173 time to create 1 rle with new method : 0.0812828540802002 time for calcul the mask position with numpy : 0.00594329833984375 nb_pixel_total : 3681 time to create 1 rle with old method : 0.004008054733276367 create new chi : 0.4162881374359131 time to delete rle : 0.0004589557647705078 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 3174 TO DO : save crop sub photo not yet done ! save time : 0.5176703929901123 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.042522430419921875 time for calcul the mask position with numpy : 0.12731361389160156 nb_pixel_total : 1961959 time to create 1 rle with new method : 0.07764339447021484 time for calcul the mask position with numpy : 0.006848335266113281 nb_pixel_total : 109119 time to create 1 rle with old method : 0.11776041984558105 time for calcul the mask position with numpy : 0.005719661712646484 nb_pixel_total : 2522 time to create 1 rle with old method : 0.0026540756225585938 create new chi : 0.3478984832763672 time to delete rle : 0.0003383159637451172 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2232 TO DO : save crop sub photo not yet done ! save time : 0.39438557624816895 map_output_result : {1386891922: (0.0, 'Should be the crop_list due to order', 0), 1386891917: (0.0, 'Should be the crop_list due to order', 0.0), 1386891913: (0.0, 'Should be the crop_list due to order', 0), 1386891879: (0.0, 'Should be the crop_list due to order', 0.0), 1386891877: (0.0, 'Should be the crop_list due to order', 0), 1386891876: (0.0, 'Should be the crop_list due to order', 0), 1386891874: (0.0, 'Should be the crop_list due to order', 0), 1386891872: (0.0, 'Should be the crop_list due to order', 0), 1386891870: (0.0, 'Should be the crop_list due to order', 0), 1386891855: (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 [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] Looping around the photos to save general results len do output : 10 /1386891922.Didn't retrieve data . /1386891917.Didn't retrieve data . /1386891913.Didn't retrieve data . /1386891879.Didn't retrieve data . /1386891877.Didn't retrieve data . /1386891876.Didn't retrieve data . /1386891874.Didn't retrieve data . /1386891872.Didn't retrieve data . /1386891870.Didn't retrieve data . /1386891855.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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.03645920753479004 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.09071946144104 time spend to save output : 0.03687691688537598 total time spend for step 3 : 8.127596378326416 step4:ventilate_hashtags_in_portfolio Tue Sep 30 17:08:14 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 : 27344240 get user id for portfolio 27344240 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`=27344240 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','carton','pet_clair','metal','papier','autre','pehd','pet_fonce','flou','environnement')) 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`=27344240 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','carton','pet_clair','metal','papier','autre','pehd','pet_fonce','flou','environnement')) 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`=27344240 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','carton','pet_clair','metal','papier','autre','pehd','pet_fonce','flou','environnement')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27357164,27357165,27357166,27357167,27357168,27357169,27357170,27357171,27357172,27357173,27357174?tags=background,mal_croppe,carton,pet_clair,metal,papier,autre,pehd,pet_fonce,flou,environnement Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] Looping around the photos to save general results len do output : 1 /27344240. 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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.037262678146362305 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.43609619140625 time spend to save output : 0.03749585151672363 total time spend for step 4 : 5.473592042922974 step5:final Tue Sep 30 17:08:20 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 : {1386891922: ('0.25469097222222226',), 1386891917: ('0.25469097222222226',), 1386891913: ('0.25469097222222226',), 1386891879: ('0.25469097222222226',), 1386891877: ('0.25469097222222226',), 1386891876: ('0.25469097222222226',), 1386891874: ('0.25469097222222226',), 1386891872: ('0.25469097222222226',), 1386891870: ('0.25469097222222226',), 1386891855: ('0.25469097222222226',)} new output for save of step final : {1386891922: ('0.25469097222222226',), 1386891917: ('0.25469097222222226',), 1386891913: ('0.25469097222222226',), 1386891879: ('0.25469097222222226',), 1386891877: ('0.25469097222222226',), 1386891876: ('0.25469097222222226',), 1386891874: ('0.25469097222222226',), 1386891872: ('0.25469097222222226',), 1386891870: ('0.25469097222222226',), 1386891855: ('0.25469097222222226',)} [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] Looping around the photos to save general results len do output : 10 /1386891922.Didn't retrieve data . /1386891917.Didn't retrieve data . /1386891913.Didn't retrieve data . /1386891879.Didn't retrieve data . /1386891877.Didn't retrieve data . /1386891876.Didn't retrieve data . /1386891874.Didn't retrieve data . /1386891872.Didn't retrieve data . /1386891870.Didn't retrieve data . /1386891855.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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 30 time used for this insertion : 0.03667402267456055 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.36463403701782227 time spend to save output : 0.03716015815734863 total time spend for step 5 : 0.4017941951751709 step6:blur_detection Tue Sep 30 17:08:20 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/1759244831_371017_1386891922_905acfa1d0c7361b043a50c1eedd7d48.jpg resize: (1080, 1920) 1386891922 -0.8565524470403165 treat image : temp/1759244831_371017_1386891917_3c3fb0d6209a634fcc742e83e262a076.jpg resize: (1080, 1920) 1386891917 -2.1287298207485255 treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03.jpg resize: (1080, 1920) 1386891913 -2.27900912984298 treat image : temp/1759244831_371017_1386891879_87b501516e73269732fd9dd70f62a9cf.jpg resize: (1080, 1920) 1386891879 -2.328142765130508 treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4.jpg resize: (1080, 1920) 1386891877 -2.804223534004985 treat image : temp/1759244831_371017_1386891876_dae20f3c67839d5f1df1b47290e92092.jpg resize: (1080, 1920) 1386891876 -2.1288801564402857 treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e.jpg resize: (1080, 1920) 1386891874 -2.1848734664054548 treat image : temp/1759244831_371017_1386891872_30890afb608f8ce6255786fcbb493a1e.jpg resize: (1080, 1920) 1386891872 -2.139045112600492 treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035.jpg resize: (1080, 1920) 1386891870 -1.8159405739429133 treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93.jpg resize: (1080, 1920) 1386891855 -2.778226448867574 treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108232_0.png resize: (56, 78) 1386983894 7.42135934049745 treat image : temp/1759244831_371017_1386891922_905acfa1d0c7361b043a50c1eedd7d48_rle_crop_3981108221_0.png resize: (142, 61) 1386983905 -2.1105879195363735 treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108223_0.png resize: (875, 1037) 1386983906 0.1102395719286528 treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108222_0.png resize: (81, 77) 1386983907 -3.060990398675955 treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108225_0.png resize: (1009, 1445) 1386983908 -3.1569665009001917 treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108224_0.png resize: (62, 98) 1386983909 -4.3644717665339385 treat image : temp/1759244831_371017_1386891876_dae20f3c67839d5f1df1b47290e92092_rle_crop_3981108227_0.png resize: (1006, 1331) 1386983911 -2.4596599102188863 treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108230_0.png resize: (968, 1350) 1386983912 -2.177494570688084 treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108229_0.png resize: (64, 93) 1386983913 -2.0003504331850985 treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108228_0.png resize: (500, 349) 1386983914 0.15903666026672209 treat image : temp/1759244831_371017_1386891872_30890afb608f8ce6255786fcbb493a1e_rle_crop_3981108231_0.png resize: (109, 105) 1386983915 -1.3033085532254223 treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108233_0.png resize: (984, 996) 1386983916 -0.21834846393454363 treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108234_0.png resize: (46, 64) 1386983917 1.9073931265735746 treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108235_0.png resize: (526, 351) 1386983918 -0.03546361404524254 treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108226_0.png resize: (133, 39) 1386983919 -0.5212951398809862 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 : 25 time used for this insertion : 0.03481101989746094 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 25 time used for this insertion : 0.03527712821960449 save missing photos in datou_result : time spend for datou_step_exec : 11.33737063407898 time spend to save output : 0.08751964569091797 total time spend for step 6 : 11.424890279769897 step7:brightness Tue Sep 30 17:08:32 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/1759244831_371017_1386891922_905acfa1d0c7361b043a50c1eedd7d48.jpg treat image : temp/1759244831_371017_1386891917_3c3fb0d6209a634fcc742e83e262a076.jpg treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03.jpg treat image : temp/1759244831_371017_1386891879_87b501516e73269732fd9dd70f62a9cf.jpg treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4.jpg treat image : temp/1759244831_371017_1386891876_dae20f3c67839d5f1df1b47290e92092.jpg treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e.jpg treat image : temp/1759244831_371017_1386891872_30890afb608f8ce6255786fcbb493a1e.jpg treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035.jpg treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93.jpg treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108232_0.png treat image : temp/1759244831_371017_1386891922_905acfa1d0c7361b043a50c1eedd7d48_rle_crop_3981108221_0.png treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108223_0.png treat image : temp/1759244831_371017_1386891913_5687c1a5874f3c454be675b711f86f03_rle_crop_3981108222_0.png treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108225_0.png treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108224_0.png treat image : temp/1759244831_371017_1386891876_dae20f3c67839d5f1df1b47290e92092_rle_crop_3981108227_0.png treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108230_0.png treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108229_0.png treat image : temp/1759244831_371017_1386891874_7663b04eb0ede33291b455e5784fdb1e_rle_crop_3981108228_0.png treat image : temp/1759244831_371017_1386891872_30890afb608f8ce6255786fcbb493a1e_rle_crop_3981108231_0.png treat image : temp/1759244831_371017_1386891870_01d49baf40c0752ba380b1f476ea7035_rle_crop_3981108233_0.png treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108234_0.png treat image : temp/1759244831_371017_1386891855_9c549f96a25ea7604bf84ae67a0dbf93_rle_crop_3981108235_0.png treat image : temp/1759244831_371017_1386891877_9af0b2c0f343bd9395700d6c7dc913a4_rle_crop_3981108226_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 : 25 time used for this insertion : 0.03704357147216797 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 25 time used for this insertion : 0.035756826400756836 save missing photos in datou_result : time spend for datou_step_exec : 3.0009007453918457 time spend to save output : 0.09070110321044922 total time spend for step 7 : 3.091601848602295 step8:velours_tree Tue Sep 30 17:08:35 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 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 : 0.13797235488891602 time spend to save output : 3.361701965332031e-05 total time spend for step 8 : 0.13800597190856934 step9:send_mail_cod Tue Sep 30 17:08:35 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 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_P27344240_30-09-2025_17_08_35.pdf 27357164 imagette273571641759244915 27357165 imagette273571651759244915 27357166 imagette273571661759244915 27357167 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273571671759244915 27357168 imagette273571681759244916 27357169 change filename to text .imagette273571691759244916 27357170 change filename to text .imagette273571701759244916 27357171 imagette273571711759244917 27357172 imagette273571721759244917 27357173 imagette273571731759244917 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27344240 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27357164,27357165,27357166,27357167,27357168,27357169,27357170,27357171,27357172,27357173,27357174?tags=background,mal_croppe,carton,pet_clair,metal,papier,autre,pehd,pet_fonce,flou,environnement args[1386891922] : ((1386891922, -0.8565524470403165, 492688767), (1386891922, 0.5103359252623564, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891917] : ((1386891917, -2.1287298207485255, 492609224), (1386891917, 0.5472027056698575, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891913] : ((1386891913, -2.27900912984298, 492609224), (1386891913, 0.510480698033854, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891879] : ((1386891879, -2.328142765130508, 492609224), (1386891879, 0.6422761188680363, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891877] : ((1386891877, -2.804223534004985, 492609224), (1386891877, 0.4272901517806137, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891876] : ((1386891876, -2.1288801564402857, 492609224), (1386891876, 0.4767395434945175, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891874] : ((1386891874, -2.1848734664054548, 492609224), (1386891874, 0.40761226975141246, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891872] : ((1386891872, -2.139045112600492, 492609224), (1386891872, 0.4107025910705581, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891870] : ((1386891870, -1.8159405739429133, 492688767), (1386891870, 0.6130214967227204, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com args[1386891855] : ((1386891855, -2.778226448867574, 492609224), (1386891855, 0.5318410148906902, 2107752395), '0.25469097222222226') We are sending mail with results at report@fotonower.com refus_total : 0.25469097222222226 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=27344240 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_P27344240_30-09-2025_17_08_35.pdf results_Auto_P27344240_30-09-2025_17_08_35.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344240_30-09-2025_17_08_35.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','27344240','results_Auto_P27344240_30-09-2025_17_08_35.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344240_30-09-2025_17_08_35.pdf','pdf','','0.61','0.25469097222222226') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27344240

https://www.fotonower.com/image?json=false&list_photos_id=1386891922
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891917
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891913
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891879
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891877
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891876
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891874
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891872
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891870
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386891855
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 25.47%
Veuillez trouver les photos des contaminants.

exemples de contaminants: pet_clair: https://www.fotonower.com/view/27357167?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/27357169?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27357170?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344240_30-09-2025_17_08_35.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27357164,27357165,27357166,27357167,27357168,27357169,27357170,27357171,27357172,27357173,27357174?tags=background,mal_croppe,carton,pet_clair,metal,papier,autre,pehd,pet_fonce,flou,environnement.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 30 Sep 2025 15:08:39 GMT Content-Length: 0 Connection: close X-Message-Id: cM3kBbVnRry-m1v3SCJ6sw 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 [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] 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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.036156654357910156 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.9065780639648438 time spend to save output : 0.036366939544677734 total time spend for step 9 : 3.9429450035095215 step10:split_time_score Tue Sep 30 17:08:39 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'}] (('09', 10),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 30092025 27344240 Nombre de photos uploadées : 10 / 23040 (0%) 30092025 27344240 Nombre de photos taguées (types de déchets): 0 / 10 (0%) 30092025 27344240 Nombre de photos taguées (volume) : 0 / 10 (0%) elapsed_time : load_data_split_time_score 2.86102294921875e-06 elapsed_time : order_list_meta_photo_and_scores 6.198883056640625e-06 ?????????? elapsed_time : fill_and_build_computed_from_old_data 0.00052642822265625 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6483380794525146 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 : 0.25469097222222226 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344240_30-09-2025_17_08_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27344240 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`=27344240 AND mptpi.`type`=3594 To do Qualite : 0.1986372843013468 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344242_30-09-2025_17_08_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27344242 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`=27344242 AND mptpi.`type`=3594 To do Qualite : 0.040582133058984914 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27344246_30-09-2025_17_08_25.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27344246 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`=27344246 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27344248 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27344254 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27355641 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27355643 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'30092025': {'nb_upload': 10, '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 [1386891922, 1386891917, 1386891913, 1386891879, 1386891877, 1386891876, 1386891874, 1386891872, 1386891870, 1386891855] Looping around the photos to save general results len do output : 1 /27344240Didn'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, '3793825') ('3318', '27344240', '1386891922', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891917', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891913', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891879', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891877', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891876', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891874', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891872', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891870', None, None, None, None, None, '3793825') ('3318', None, None, None, None, None, None, None, '3793825') ('3318', '27344240', '1386891855', None, None, None, None, None, '3793825') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.040001630783081055 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.67613959312439 time spend to save output : 0.04024195671081543 total time spend for step 10 : 4.716381549835205 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 10 set_done_treatment 53.07user 18.23system 1:35.25elapsed 74%CPU (0avgtext+0avgdata 2685744maxresident)k 112720inputs+46432outputs (1130major+1387770minor)pagefaults 0swaps