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 3779775' -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 : 377493 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 : ['3779775'] with mtr_portfolio_ids : ['27241410'] and first list_photo_ids : [] new path : /proc/377493/ 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 , BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 18 ; length of list_pids : 18 ; length of list_args : 18 time to download the photos : 3.519634246826172 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 17:10:52 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 : 4491 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-30 17:10:55.815625: 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 17:10:55.840613: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-30 17:10:55.843252: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fdd40000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:10:55.843306: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-30 17:10:55.847977: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-30 17:10:56.015469: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x15c9c570 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-30 17:10:56.015526: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-30 17:10:56.016142: 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 17:10:56.016526: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:10:56.018737: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:10:56.020975: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:10:56.021327: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:10:56.024101: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:10:56.025360: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:10:56.031110: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:10:56.032416: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:10:56.032531: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:10:56.033201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:10:56.033219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:10:56.033229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:10:56.034332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4039 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 17:10:56.469736: 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 17:10:56.469877: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:10:56.469895: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:10:56.469911: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:10:56.469925: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:10:56.469940: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:10:56.469953: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:10:56.469967: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:10:56.470829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:10:56.471939: 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 17:10:56.471976: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-30 17:10:56.471991: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:10:56.472005: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-30 17:10:56.472019: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-30 17:10:56.472033: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-30 17:10:56.472047: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-30 17:10:56.472061: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-30 17:10:56.472946: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-30 17:10:56.472989: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-30 17:10:56.472998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-30 17:10:56.473006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-30 17:10:56.473938: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4039 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 17:11:06.625542: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-30 17:11:06.834012: 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 : 18 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 : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 29.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 38.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 63.00000 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 : 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 : 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 : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 18.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 25.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 9 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 : 11 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 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 : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 34.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 35.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 45.00000 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: 0.00000 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: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 27.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 4 Detection mask done ! Trying to reset tf kernel 377786 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 567 tf kernel not reseted sub process len(results) : 18 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 18 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 : 5290 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 : 0.0002148151397705078 nb_pixel_total : 7205 time to create 1 rle with old method : 0.008637189865112305 length of segment : 112 time for calcul the mask position with numpy : 0.0018482208251953125 nb_pixel_total : 109577 time to create 1 rle with old method : 0.12545204162597656 length of segment : 520 time for calcul the mask position with numpy : 9.846687316894531e-05 nb_pixel_total : 2663 time to create 1 rle with old method : 0.0030927658081054688 length of segment : 67 time for calcul the mask position with numpy : 7.462501525878906e-05 nb_pixel_total : 2554 time to create 1 rle with old method : 0.003052949905395508 length of segment : 45 time for calcul the mask position with numpy : 6.842613220214844e-05 nb_pixel_total : 2222 time to create 1 rle with old method : 0.002685546875 length of segment : 48 time for calcul the mask position with numpy : 0.0002512931823730469 nb_pixel_total : 8955 time to create 1 rle with old method : 0.009947776794433594 length of segment : 179 time for calcul the mask position with numpy : 0.0015032291412353516 nb_pixel_total : 105402 time to create 1 rle with old method : 0.1159052848815918 length of segment : 521 time for calcul the mask position with numpy : 0.00013184547424316406 nb_pixel_total : 4205 time to create 1 rle with old method : 0.005434513092041016 length of segment : 139 time for calcul the mask position with numpy : 0.28996729850769043 nb_pixel_total : 1288401 time to create 1 rle with new method : 0.08155989646911621 length of segment : 1479 time for calcul the mask position with numpy : 0.00017404556274414062 nb_pixel_total : 7959 time to create 1 rle with old method : 0.009473085403442383 length of segment : 108 time for calcul the mask position with numpy : 0.0018694400787353516 nb_pixel_total : 57517 time to create 1 rle with old method : 0.06727051734924316 length of segment : 550 time for calcul the mask position with numpy : 0.0002448558807373047 nb_pixel_total : 8047 time to create 1 rle with old method : 0.009538888931274414 length of segment : 139 time for calcul the mask position with numpy : 0.0014569759368896484 nb_pixel_total : 89803 time to create 1 rle with old method : 0.10351729393005371 length of segment : 481 time for calcul the mask position with numpy : 0.0023484230041503906 nb_pixel_total : 111207 time to create 1 rle with old method : 0.12330770492553711 length of segment : 571 time for calcul the mask position with numpy : 0.016898632049560547 nb_pixel_total : 777195 time to create 1 rle with new method : 0.377504825592041 length of segment : 1026 time for calcul the mask position with numpy : 0.00022459030151367188 nb_pixel_total : 4167 time to create 1 rle with old method : 0.00720977783203125 length of segment : 61 time for calcul the mask position with numpy : 0.000644683837890625 nb_pixel_total : 15004 time to create 1 rle with old method : 0.02169632911682129 length of segment : 154 time for calcul the mask position with numpy : 0.0005345344543457031 nb_pixel_total : 15967 time to create 1 rle with old method : 0.019348859786987305 length of segment : 156 time for calcul the mask position with numpy : 0.0030455589294433594 nb_pixel_total : 113458 time to create 1 rle with old method : 0.13592147827148438 length of segment : 554 time for calcul the mask position with numpy : 0.0011410713195800781 nb_pixel_total : 39260 time to create 1 rle with old method : 0.04460883140563965 length of segment : 309 time for calcul the mask position with numpy : 0.00011134147644042969 nb_pixel_total : 3091 time to create 1 rle with old method : 0.003648042678833008 length of segment : 56 time for calcul the mask position with numpy : 0.00034117698669433594 nb_pixel_total : 8948 time to create 1 rle with old method : 0.016568660736083984 length of segment : 119 time for calcul the mask position with numpy : 0.0003666877746582031 nb_pixel_total : 7282 time to create 1 rle with old method : 0.014445066452026367 length of segment : 105 time for calcul the mask position with numpy : 0.0001976490020751953 nb_pixel_total : 3246 time to create 1 rle with old method : 0.006264925003051758 length of segment : 54 time for calcul the mask position with numpy : 0.003005504608154297 nb_pixel_total : 120530 time to create 1 rle with old method : 0.15221238136291504 length of segment : 541 time for calcul the mask position with numpy : 0.002125263214111328 nb_pixel_total : 93807 time to create 1 rle with old method : 0.10840010643005371 length of segment : 466 time for calcul the mask position with numpy : 0.0030667781829833984 nb_pixel_total : 134447 time to create 1 rle with old method : 0.15879106521606445 length of segment : 397 time for calcul the mask position with numpy : 0.00044465065002441406 nb_pixel_total : 24750 time to create 1 rle with old method : 0.03589010238647461 length of segment : 185 time for calcul the mask position with numpy : 0.002223491668701172 nb_pixel_total : 93722 time to create 1 rle with old method : 0.11070728302001953 length of segment : 510 time for calcul the mask position with numpy : 0.0002307891845703125 nb_pixel_total : 6484 time to create 1 rle with old method : 0.007867574691772461 length of segment : 98 time for calcul the mask position with numpy : 0.00011992454528808594 nb_pixel_total : 4288 time to create 1 rle with old method : 0.005416393280029297 length of segment : 64 time for calcul the mask position with numpy : 0.013927459716796875 nb_pixel_total : 1034757 time to create 1 rle with new method : 0.05283212661743164 length of segment : 1199 time for calcul the mask position with numpy : 0.0025925636291503906 nb_pixel_total : 94053 time to create 1 rle with old method : 0.10861587524414062 length of segment : 516 time for calcul the mask position with numpy : 0.00034117698669433594 nb_pixel_total : 11126 time to create 1 rle with old method : 0.01377558708190918 length of segment : 99 time for calcul the mask position with numpy : 0.0003681182861328125 nb_pixel_total : 8022 time to create 1 rle with old method : 0.009897232055664062 length of segment : 142 time spent for convertir_results : 4.918390512466431 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 35 chid ids of type : 3594 Number RLEs to save : 11770 save missing photos in datou_result : time spend for datou_step_exec : 31.66742777824402 time spend to save output : 1.4494259357452393 total time spend for step 1 : 33.11685371398926 step2:crop_condition Tue Sep 30 17:11:25 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 : 18 ! batch 1 Loaded 35 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 6 About to insert : list_path_to_insert length 6 new photo from crops ! About to upload 6 photos upload in portfolio : 3736932 init cache_photo without model_param we have 6 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245087_377493 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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113809_0.png', 0, 111, 180, 0, 1759245088,'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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113811_0.png', 0, 42, 137, 0, 1759245088,'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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113813_0.png', 0, 119, 107, 0, 1759245088,'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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113824_0.png', 0, 82, 55, 0, 1759245088,'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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113823_0.png', 0, 278, 219, 0, 1759245088,'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(1759245088), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113827_0.png', 0, 98, 53, 0, 1759245088,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 6 photos in the portfolio 3736932 time of upload the photos Elapsed time : 2.0442705154418945 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! 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/1759245089_377493 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(1759245089), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173901_dc1f47a66de9c35cc322195e63e2258d_rle_crop_3981113815_0.png', 0, 130, 150, 0, 1759245089,'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 : 0.7346229553222656 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 3 new photo from crops ! About to upload 3 photos upload in portfolio : 3736932 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245091_377493 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(1759245091), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113807_0.png', 0, 80, 45, 0, 1759245091,'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(1759245091), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113819_0.png', 0, 93, 58, 0, 1759245091,'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(1759245091), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113837_0.png', 0, 162, 94, 0, 1759245091,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 3 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.290734052658081 we have finished the crop for the class : metal begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 21 About to insert : list_path_to_insert length 21 new photo from crops ! About to upload 21 photos upload in portfolio : 3736932 init cache_photo without model_param we have 21 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245109_377493 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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113804_0.png', 0, 91, 108, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113805_0.png', 0, 346, 516, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113810_0.png', 0, 319, 516, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113812_0.png', 0, 1587, 998, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113814_0.png', 0, 596, 415, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173882_d8f22af9f1364671110947c903370608_rle_crop_3981113816_0.png', 0, 340, 481, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113818_0.png', 0, 1162, 991, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113817_0.png', 0, 349, 564, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113820_0.png', 0, 162, 146, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113821_0.png', 0, 139, 156, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113822_0.png', 0, 350, 553, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113828_0.png', 0, 361, 535, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113830_0.png', 0, 715, 351, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113831_0.png', 0, 173, 185, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113829_0.png', 0, 328, 462, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173765_73bfe2deea128aea7ebc7321450cad23_rle_crop_3981113832_0.png', 0, 331, 502, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113834_0.png', 0, 84, 64, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113833_0.png', 0, 102, 89, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173681_b8e0c61b5d98bee06b3da0c8dd9b33f2_rle_crop_3981113835_0.png', 0, 1350, 999, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173385_c04549ba4e926232f109571b8c1702a1_rle_crop_3981113836_0.png', 0, 353, 497, 0, 1759245113,'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(1759245113), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113838_0.png', 0, 73, 142, 0, 1759245113,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 21 photos in the portfolio 3736932 time of upload the photos Elapsed time : 7.101176738739014 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245117_377493 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(1759245117), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113806_0.png', 0, 55, 67, 0, 1759245117,'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(1759245117), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113808_0.png', 0, 57, 48, 0, 1759245117,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.9916205406188965 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 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1759245118_377493 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(1759245119), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113825_0.png', 0, 99, 118, 0, 1759245119,'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(1759245119), 0.0, 0.0, 14, '', 0, 0, '1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113826_0.png', 0, 117, 103, 0, 1759245119,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.098238468170166 we have finished the crop for the class : pet_fonce 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 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 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 [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] Looping around the photos to save general results len do output : 35 /1386984891Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984892Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984893Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984894Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984896Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984897Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984899Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984914Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984917Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984919Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984963Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984964Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984965Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984967Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984968Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984969Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984971Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984972Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984973Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984974Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984976Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984977Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984978Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984979Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984980Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984982Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984983Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984984Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984985Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984986Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1386984987Didn'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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 123 time used for this insertion : 0.042289018630981445 save_final save missing photos in datou_result : time spend for datou_step_exec : 33.643566608428955 time spend to save output : 0.04389643669128418 total time spend for step 2 : 33.68746304512024 step3:rle_unique_nms_with_priority Tue Sep 30 17:11:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 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 35 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.49958324432373047 time for calcul the mask position with numpy : 0.0787038803100586 nb_pixel_total : 1954155 time to create 1 rle with new method : 0.21123647689819336 time for calcul the mask position with numpy : 0.006410837173461914 nb_pixel_total : 2663 time to create 1 rle with old method : 0.0031447410583496094 time for calcul the mask position with numpy : 0.006957530975341797 nb_pixel_total : 109577 time to create 1 rle with old method : 0.1283574104309082 time for calcul the mask position with numpy : 0.0068094730377197266 nb_pixel_total : 7205 time to create 1 rle with old method : 0.008414983749389648 create new chi : 0.4608154296875 time to delete rle : 0.06850075721740723 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 2478 TO DO : save crop sub photo not yet done ! save time : 0.4169046878814697 nb_obj : 4 nb_hashtags : 4 time to prepare the origin masks : 0.3432328701019287 time for calcul the mask position with numpy : 0.21898627281188965 nb_pixel_total : 1954467 time to create 1 rle with new method : 0.09849834442138672 time for calcul the mask position with numpy : 0.006932735443115234 nb_pixel_total : 105402 time to create 1 rle with old method : 0.12111449241638184 time for calcul the mask position with numpy : 0.006482124328613281 nb_pixel_total : 8955 time to create 1 rle with old method : 0.010952472686767578 time for calcul the mask position with numpy : 0.0065059661865234375 nb_pixel_total : 2222 time to create 1 rle with old method : 0.002637624740600586 time for calcul the mask position with numpy : 0.006241798400878906 nb_pixel_total : 2554 time to create 1 rle with old method : 0.003031015396118164 create new chi : 0.4912881851196289 time to delete rle : 0.0004410743713378906 batch 1 Loaded 9 chid ids of type : 3594 +++++Number RLEs to save : 2666 TO DO : save crop sub photo not yet done ! save time : 0.45185327529907227 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.055272817611694336 time for calcul the mask position with numpy : 0.015725374221801758 nb_pixel_total : 784270 time to create 1 rle with new method : 0.13767528533935547 time for calcul the mask position with numpy : 0.01703166961669922 nb_pixel_total : 1285125 time to create 1 rle with new method : 0.03440380096435547 time for calcul the mask position with numpy : 0.006087541580200195 nb_pixel_total : 4205 time to create 1 rle with old method : 0.004774808883666992 create new chi : 0.21629047393798828 time to delete rle : 0.0006175041198730469 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 4316 TO DO : save crop sub photo not yet done ! save time : 0.6122078895568848 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.21062850952148438 time for calcul the mask position with numpy : 0.06991076469421387 nb_pixel_total : 2008124 time to create 1 rle with new method : 0.1737828254699707 time for calcul the mask position with numpy : 0.006824493408203125 nb_pixel_total : 57517 time to create 1 rle with old method : 0.06917023658752441 time for calcul the mask position with numpy : 0.006310939788818359 nb_pixel_total : 7959 time to create 1 rle with old method : 0.010947704315185547 create new chi : 0.34855031967163086 time to delete rle : 0.0004088878631591797 batch 1 Loaded 5 chid ids of type : 3594 +++Number RLEs to save : 2396 TO DO : save crop sub photo not yet done ! save time : 0.41069555282592773 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.07482647895812988 time for calcul the mask position with numpy : 0.16988563537597656 nb_pixel_total : 2065553 time to create 1 rle with new method : 0.0782308578491211 time for calcul the mask position with numpy : 0.0065228939056396484 nb_pixel_total : 8047 time to create 1 rle with old method : 0.009592056274414062 create new chi : 0.2777261734008789 time to delete rle : 0.00022840499877929688 batch 1 Loaded 3 chid ids of type : 3594 ++Number RLEs to save : 1358 TO DO : save crop sub photo not yet done ! save time : 0.28160810470581055 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.034824371337890625 time for calcul the mask position with numpy : 0.17189359664916992 nb_pixel_total : 1983797 time to create 1 rle with new method : 0.17708635330200195 time for calcul the mask position with numpy : 0.006646394729614258 nb_pixel_total : 89803 time to create 1 rle with old method : 0.11596560478210449 create new chi : 0.48230648040771484 time to delete rle : 0.0004525184631347656 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2042 TO DO : save crop sub photo not yet done ! save time : 0.41442227363586426 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.08436703681945801 time for calcul the mask position with numpy : 0.047524213790893555 nb_pixel_total : 1185198 time to create 1 rle with new method : 0.2805647850036621 time for calcul the mask position with numpy : 0.012338638305664062 nb_pixel_total : 777195 time to create 1 rle with new method : 0.16419410705566406 time for calcul the mask position with numpy : 0.007323741912841797 nb_pixel_total : 111207 time to create 1 rle with old method : 0.13176918029785156 create new chi : 0.6595292091369629 time to delete rle : 0.0006477832794189453 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 4274 TO DO : save crop sub photo not yet done ! save time : 0.6178872585296631 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.08322954177856445 time for calcul the mask position with numpy : 0.2674727439880371 nb_pixel_total : 2054429 time to create 1 rle with new method : 0.24983501434326172 time for calcul the mask position with numpy : 0.00706934928894043 nb_pixel_total : 15004 time to create 1 rle with old method : 0.018700599670410156 time for calcul the mask position with numpy : 0.006163120269775391 nb_pixel_total : 4167 time to create 1 rle with old method : 0.0049211978912353516 create new chi : 0.565082311630249 time to delete rle : 0.0003113746643066406 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1510 TO DO : save crop sub photo not yet done ! save time : 0.33814454078674316 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 0.10777878761291504 time for calcul the mask position with numpy : 0.1989591121673584 nb_pixel_total : 1901824 time to create 1 rle with new method : 0.2079455852508545 time for calcul the mask position with numpy : 0.006334543228149414 nb_pixel_total : 3091 time to create 1 rle with old method : 0.0038022994995117188 time for calcul the mask position with numpy : 0.006682395935058594 nb_pixel_total : 39260 time to create 1 rle with old method : 0.05013537406921387 time for calcul the mask position with numpy : 0.007439613342285156 nb_pixel_total : 113458 time to create 1 rle with old method : 0.15312623977661133 time for calcul the mask position with numpy : 0.006378173828125 nb_pixel_total : 15967 time to create 1 rle with old method : 0.018530845642089844 create new chi : 0.6693503856658936 time to delete rle : 0.0007486343383789062 batch 1 Loaded 9 chid ids of type : 3594 +++++++Number RLEs to save : 3230 TO DO : save crop sub photo not yet done ! save time : 0.5260665416717529 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.04236769676208496 time for calcul the mask position with numpy : 0.019731760025024414 nb_pixel_total : 2057370 time to create 1 rle with new method : 0.08482813835144043 time for calcul the mask position with numpy : 0.005964040756225586 nb_pixel_total : 7282 time to create 1 rle with old method : 0.008375406265258789 time for calcul the mask position with numpy : 0.0060613155364990234 nb_pixel_total : 8948 time to create 1 rle with old method : 0.010639667510986328 create new chi : 0.14287114143371582 time to delete rle : 0.0002753734588623047 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1528 TO DO : save crop sub photo not yet done ! save time : 0.32570695877075195 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.33800268173217773 time for calcul the mask position with numpy : 0.08441615104675293 nb_pixel_total : 1949824 time to create 1 rle with new method : 0.2468869686126709 time for calcul the mask position with numpy : 0.007127285003662109 nb_pixel_total : 120530 time to create 1 rle with old method : 0.13837671279907227 time for calcul the mask position with numpy : 0.006554841995239258 nb_pixel_total : 3246 time to create 1 rle with old method : 0.003872394561767578 create new chi : 0.49810314178466797 time to delete rle : 0.00041484832763671875 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2270 TO DO : save crop sub photo not yet done ! save time : 0.4047236442565918 nb_obj : 3 nb_hashtags : 1 time to prepare the origin masks : 0.07575392723083496 time for calcul the mask position with numpy : 0.17336678504943848 nb_pixel_total : 1820596 time to create 1 rle with new method : 0.09207391738891602 time for calcul the mask position with numpy : 0.006120204925537109 nb_pixel_total : 24750 time to create 1 rle with old method : 0.0286409854888916 time for calcul the mask position with numpy : 0.007390737533569336 nb_pixel_total : 134447 time to create 1 rle with old method : 0.16610431671142578 time for calcul the mask position with numpy : 0.0076961517333984375 nb_pixel_total : 93807 time to create 1 rle with old method : 0.13460898399353027 create new chi : 0.6265442371368408 time to delete rle : 0.0005857944488525391 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3176 TO DO : save crop sub photo not yet done ! save time : 0.506892204284668 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.09118795394897461 time for calcul the mask position with numpy : 0.02913832664489746 nb_pixel_total : 1979878 time to create 1 rle with new method : 0.10446691513061523 time for calcul the mask position with numpy : 0.007174491882324219 nb_pixel_total : 93722 time to create 1 rle with old method : 0.10993051528930664 create new chi : 0.2592482566833496 time to delete rle : 0.0004858970642089844 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2100 TO DO : save crop sub photo not yet done ! save time : 0.3712289333343506 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.2678203582763672 time for calcul the mask position with numpy : 0.13657045364379883 nb_pixel_total : 2062828 time to create 1 rle with new method : 0.21042370796203613 time for calcul the mask position with numpy : 0.01096200942993164 nb_pixel_total : 4288 time to create 1 rle with old method : 0.005429744720458984 time for calcul the mask position with numpy : 0.006402254104614258 nb_pixel_total : 6484 time to create 1 rle with old method : 0.0075871944427490234 create new chi : 0.39130330085754395 time to delete rle : 0.00028252601623535156 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1404 TO DO : save crop sub photo not yet done ! save time : 0.34475231170654297 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.09131884574890137 time for calcul the mask position with numpy : 0.04622602462768555 nb_pixel_total : 1038843 time to create 1 rle with new method : 0.36206579208374023 time for calcul the mask position with numpy : 0.013173818588256836 nb_pixel_total : 1034757 time to create 1 rle with new method : 0.07808375358581543 create new chi : 0.5138468742370605 time to delete rle : 0.00039196014404296875 batch 1 Loaded 3 chid ids of type : 3594 ++Number RLEs to save : 3478 TO DO : save crop sub photo not yet done ! save time : 0.5229198932647705 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.037059783935546875 time for calcul the mask position with numpy : 0.16417646408081055 nb_pixel_total : 1979547 time to create 1 rle with new method : 0.09205341339111328 time for calcul the mask position with numpy : 0.007172107696533203 nb_pixel_total : 94053 time to create 1 rle with old method : 0.10890007019042969 create new chi : 0.3826596736907959 time to delete rle : 0.0006680488586425781 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2112 TO DO : save crop sub photo not yet done ! save time : 0.4002354145050049 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.17719745635986328 time for calcul the mask position with numpy : 0.1447770595550537 nb_pixel_total : 2054452 time to create 1 rle with new method : 0.08167004585266113 time for calcul the mask position with numpy : 0.006014585494995117 nb_pixel_total : 8022 time to create 1 rle with old method : 0.009243965148925781 time for calcul the mask position with numpy : 0.006118059158325195 nb_pixel_total : 11126 time to create 1 rle with old method : 0.013158798217773438 create new chi : 0.27086877822875977 time to delete rle : 0.00048542022705078125 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1562 TO DO : save crop sub photo not yet done ! save time : 0.3393547534942627 No data in photo_id : 1386173364 map_output_result : {1386174399: (0.0, 'Should be the crop_list due to order', 0), 1386174355: (0.0, 'Should be the crop_list due to order', 0), 1386174239: (0.0, 'Should be the crop_list due to order', 0), 1386173934: (0.0, 'Should be the crop_list due to order', 0), 1386173901: (0.0, 'Should be the crop_list due to order', 0), 1386173882: (0.0, 'Should be the crop_list due to order', 0), 1386173859: (0.0, 'Should be the crop_list due to order', 0), 1386173855: (0.0, 'Should be the crop_list due to order', 0), 1386173852: (0.0, 'Should be the crop_list due to order', 0), 1386173837: (0.0, 'Should be the crop_list due to order', 0), 1386173815: (0.0, 'Should be the crop_list due to order', 0), 1386173791: (0.0, 'Should be the crop_list due to order', 0), 1386173765: (0.0, 'Should be the crop_list due to order', 0), 1386173738: (0.0, 'Should be the crop_list due to order', 0), 1386173681: (0.0, 'Should be the crop_list due to order', 0), 1386173385: (0.0, 'Should be the crop_list due to order', 0), 1386173368: (0.0, 'Should be the crop_list due to order', 0), 1386173364: (0.0, 'Should be the crop_list due to order', 0.0)} 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 [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] Looping around the photos to save general results len do output : 18 /1386174399.Didn't retrieve data . /1386174355.Didn't retrieve data . /1386174239.Didn't retrieve data . /1386173934.Didn't retrieve data . /1386173901.Didn't retrieve data . /1386173882.Didn't retrieve data . /1386173859.Didn't retrieve data . /1386173855.Didn't retrieve data . /1386173852.Didn't retrieve data . /1386173837.Didn't retrieve data . /1386173815.Didn't retrieve data . /1386173791.Didn't retrieve data . /1386173765.Didn't retrieve data . /1386173738.Didn't retrieve data . /1386173681.Didn't retrieve data . /1386173385.Didn't retrieve data . /1386173368.Didn't retrieve data . /1386173364.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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 54 time used for this insertion : 0.03762340545654297 save_final save missing photos in datou_result : time spend for datou_step_exec : 17.930481910705566 time spend to save output : 0.03836202621459961 total time spend for step 3 : 17.968843936920166 step4:ventilate_hashtags_in_portfolio Tue Sep 30 17:12:17 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 : 27241410 get user id for portfolio 27241410 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`=27241410 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','flou','carton','environnement','papier','pet_fonce','background','pet_clair','autre','mal_croppe')) 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`=27241410 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','flou','carton','environnement','papier','pet_fonce','background','pet_clair','autre','mal_croppe')) 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`=27241410 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pehd','metal','flou','carton','environnement','papier','pet_fonce','background','pet_clair','autre','mal_croppe')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/27357440,27357441,27357442,27357443,27357444,27357445,27357446,27357447,27357448,27357449,27357450?tags=pehd,metal,flou,carton,environnement,papier,pet_fonce,background,pet_clair,autre,mal_croppe Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] Looping around the photos to save general results len do output : 1 /27241410. 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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 19 time used for this insertion : 0.03857922554016113 save_final save missing photos in datou_result : time spend for datou_step_exec : 5.589575529098511 time spend to save output : 0.038895368576049805 total time spend for step 4 : 5.6284708976745605 step5:final Tue Sep 30 17:12:23 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 : {1386174399: ('0.11831396283436213',), 1386174355: ('0.11831396283436213',), 1386174239: ('0.11831396283436213',), 1386173934: ('0.11831396283436213',), 1386173901: ('0.11831396283436213',), 1386173882: ('0.11831396283436213',), 1386173859: ('0.11831396283436213',), 1386173855: ('0.11831396283436213',), 1386173852: ('0.11831396283436213',), 1386173837: ('0.11831396283436213',), 1386173815: ('0.11831396283436213',), 1386173791: ('0.11831396283436213',), 1386173765: ('0.11831396283436213',), 1386173738: ('0.11831396283436213',), 1386173681: ('0.11831396283436213',), 1386173385: ('0.11831396283436213',), 1386173368: ('0.11831396283436213',), 1386173364: ('0.11831396283436213',)} new output for save of step final : {1386174399: ('0.11831396283436213',), 1386174355: ('0.11831396283436213',), 1386174239: ('0.11831396283436213',), 1386173934: ('0.11831396283436213',), 1386173901: ('0.11831396283436213',), 1386173882: ('0.11831396283436213',), 1386173859: ('0.11831396283436213',), 1386173855: ('0.11831396283436213',), 1386173852: ('0.11831396283436213',), 1386173837: ('0.11831396283436213',), 1386173815: ('0.11831396283436213',), 1386173791: ('0.11831396283436213',), 1386173765: ('0.11831396283436213',), 1386173738: ('0.11831396283436213',), 1386173681: ('0.11831396283436213',), 1386173385: ('0.11831396283436213',), 1386173368: ('0.11831396283436213',), 1386173364: ('0.11831396283436213',)} [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] Looping around the photos to save general results len do output : 18 /1386174399.Didn't retrieve data . /1386174355.Didn't retrieve data . /1386174239.Didn't retrieve data . /1386173934.Didn't retrieve data . /1386173901.Didn't retrieve data . /1386173882.Didn't retrieve data . /1386173859.Didn't retrieve data . /1386173855.Didn't retrieve data . /1386173852.Didn't retrieve data . /1386173837.Didn't retrieve data . /1386173815.Didn't retrieve data . /1386173791.Didn't retrieve data . /1386173765.Didn't retrieve data . /1386173738.Didn't retrieve data . /1386173681.Didn't retrieve data . /1386173385.Didn't retrieve data . /1386173368.Didn't retrieve data . /1386173364.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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 54 time used for this insertion : 0.04404711723327637 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.37828779220581055 time spend to save output : 0.045145511627197266 total time spend for step 5 : 0.4234333038330078 step6:blur_detection Tue Sep 30 17:12:23 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/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf.jpg resize: (1080, 1920) 1386174399 -0.9274821674905618 treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d.jpg resize: (1080, 1920) 1386174355 3.5005540141838845 treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359.jpg resize: (1080, 1920) 1386174239 2.3421001344847645 treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550.jpg resize: (1080, 1920) 1386173934 -2.6928098669356233 treat image : temp/1759245049_377493_1386173901_dc1f47a66de9c35cc322195e63e2258d.jpg resize: (1080, 1920) 1386173901 -1.4341977737380458 treat image : temp/1759245049_377493_1386173882_d8f22af9f1364671110947c903370608.jpg resize: (1080, 1920) 1386173882 2.368413596752122 treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38.jpg resize: (1080, 1920) 1386173859 -0.37074243112028105 treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7.jpg resize: (1080, 1920) 1386173855 -0.2551332365260013 treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801.jpg resize: (1080, 1920) 1386173852 -0.7834967710770802 treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec.jpg resize: (1080, 1920) 1386173837 -1.5711416543155277 treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906.jpg resize: (1080, 1920) 1386173815 -0.6745359487643267 treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c.jpg resize: (1080, 1920) 1386173791 -1.4885287061003598 treat image : temp/1759245049_377493_1386173765_73bfe2deea128aea7ebc7321450cad23.jpg resize: (1080, 1920) 1386173765 -1.301465142650585 treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3.jpg resize: (1080, 1920) 1386173738 -1.7867220970308462 treat image : temp/1759245049_377493_1386173681_b8e0c61b5d98bee06b3da0c8dd9b33f2.jpg resize: (1080, 1920) 1386173681 1.2102319796606382 treat image : temp/1759245049_377493_1386173385_c04549ba4e926232f109571b8c1702a1.jpg resize: (1080, 1920) 1386173385 -1.1707003146668122 treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97.jpg resize: (1080, 1920) 1386173368 0.05058037661641416 treat image : temp/1759245049_377493_1386173364_91f6d00f2861574ef8d11b21b6004bbe.jpg resize: (1080, 1920) 1386173364 -0.5676088555462941 treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113809_0.png resize: (180, 111) 1386984891 -1.909421426495981 treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113811_0.png resize: (137, 42) 1386984892 -0.8093880892896145 treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113813_0.png resize: (107, 119) 1386984893 1.323245050120337 treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113824_0.png resize: (55, 82) 1386984894 -1.8823385881899821 treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113823_0.png resize: (219, 278) 1386984896 -1.854038756052923 treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113827_0.png resize: (53, 98) 1386984897 -1.9291887009190483 treat image : temp/1759245049_377493_1386173901_dc1f47a66de9c35cc322195e63e2258d_rle_crop_3981113815_0.png resize: (150, 130) 1386984899 -2.225196111287003 treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113807_0.png resize: (45, 80) 1386984914 -3.5437878594861703 treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113819_0.png resize: (58, 93) 1386984917 -3.061236303259178 treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113837_0.png resize: (94, 162) 1386984919 -2.872235688330908 treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113804_0.png resize: (108, 91) 1386984963 -2.9699687636433163 treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113805_0.png resize: (516, 346) 1386984964 0.11685702807393389 treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113810_0.png resize: (516, 319) 1386984965 0.1589639950766247 treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113812_0.png resize: (998, 1587) 1386984966 -0.41322718308094175 treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113814_0.png resize: (415, 596) 1386984967 -1.1926741434238979 treat image : temp/1759245049_377493_1386173882_d8f22af9f1364671110947c903370608_rle_crop_3981113816_0.png resize: (481, 340) 1386984968 -0.2061745441829126 treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113818_0.png resize: (991, 1162) 1386984969 1.0921705426196873 treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113817_0.png resize: (564, 349) 1386984970 0.030283310629448997 treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113820_0.png resize: (146, 162) 1386984971 -1.2740459865227038 treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113821_0.png resize: (156, 139) 1386984972 -0.5252542648930306 treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113822_0.png resize: (553, 350) 1386984973 0.38235705960155897 treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113828_0.png resize: (535, 361) 1386984974 0.38569325361559853 treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113830_0.png resize: (351, 715) 1386984975 -1.1269279547554312 treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113831_0.png resize: (185, 173) 1386984976 -3.2263794606573724 treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113829_0.png resize: (462, 328) 1386984977 0.01723706952110582 treat image : temp/1759245049_377493_1386173765_73bfe2deea128aea7ebc7321450cad23_rle_crop_3981113832_0.png resize: (502, 331) 1386984978 -0.25917503693768695 treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113834_0.png resize: (64, 84) 1386984979 -1.3241583401132484 treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113833_0.png resize: (89, 102) 1386984980 -2.86874933883834 treat image : temp/1759245049_377493_1386173681_b8e0c61b5d98bee06b3da0c8dd9b33f2_rle_crop_3981113835_0.png resize: (999, 1350) 1386984981 -0.4258296260434845 treat image : temp/1759245049_377493_1386173385_c04549ba4e926232f109571b8c1702a1_rle_crop_3981113836_0.png resize: (497, 353) 1386984982 -0.264315140081794 treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113838_0.png resize: (142, 73) 1386984983 -1.5232974130046226 treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113806_0.png resize: (67, 55) 1386984984 -2.668115770485728 treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113808_0.png resize: (48, 57) 1386984985 0.5819340465782181 treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113825_0.png resize: (118, 99) 1386984986 -5.032965727189055 treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113826_0.png resize: (103, 117) 1386984987 -4.489557766274161 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 : 53 time used for this insertion : 0.038121700286865234 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 53 time used for this insertion : 0.03946685791015625 save missing photos in datou_result : time spend for datou_step_exec : 17.058918952941895 time spend to save output : 0.09538650512695312 total time spend for step 6 : 17.154305458068848 step7:brightness Tue Sep 30 17:12:40 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/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf.jpg treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d.jpg treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359.jpg treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550.jpg treat image : temp/1759245049_377493_1386173901_dc1f47a66de9c35cc322195e63e2258d.jpg treat image : temp/1759245049_377493_1386173882_d8f22af9f1364671110947c903370608.jpg treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38.jpg treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7.jpg treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801.jpg treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec.jpg treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906.jpg treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c.jpg treat image : temp/1759245049_377493_1386173765_73bfe2deea128aea7ebc7321450cad23.jpg treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3.jpg treat image : temp/1759245049_377493_1386173681_b8e0c61b5d98bee06b3da0c8dd9b33f2.jpg treat image : temp/1759245049_377493_1386173385_c04549ba4e926232f109571b8c1702a1.jpg treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97.jpg treat image : temp/1759245049_377493_1386173364_91f6d00f2861574ef8d11b21b6004bbe.jpg treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113809_0.png treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113811_0.png treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113813_0.png treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113824_0.png treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113823_0.png treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113827_0.png treat image : temp/1759245049_377493_1386173901_dc1f47a66de9c35cc322195e63e2258d_rle_crop_3981113815_0.png treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113807_0.png treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113819_0.png treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113837_0.png treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113804_0.png treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113805_0.png treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113810_0.png treat image : temp/1759245049_377493_1386174239_c3ab2681b417085b9cf5b6aa6b4ba359_rle_crop_3981113812_0.png treat image : temp/1759245049_377493_1386173934_245104899633cefd8aa160eb45146550_rle_crop_3981113814_0.png treat image : temp/1759245049_377493_1386173882_d8f22af9f1364671110947c903370608_rle_crop_3981113816_0.png treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113818_0.png treat image : temp/1759245049_377493_1386173859_b9013c03674eb11257ce7088330c9f38_rle_crop_3981113817_0.png treat image : temp/1759245049_377493_1386173855_50a9251f68ea32909f91d34482ee6ce7_rle_crop_3981113820_0.png treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113821_0.png treat image : temp/1759245049_377493_1386173852_85bbd2c5f6a3ca975cffe55515474801_rle_crop_3981113822_0.png treat image : temp/1759245049_377493_1386173815_3b4367c7b0de6ca99279bbdc709f2906_rle_crop_3981113828_0.png treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113830_0.png treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113831_0.png treat image : temp/1759245049_377493_1386173791_da256c56ae1870f82955070ee8c15a8c_rle_crop_3981113829_0.png treat image : temp/1759245049_377493_1386173765_73bfe2deea128aea7ebc7321450cad23_rle_crop_3981113832_0.png treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113834_0.png treat image : temp/1759245049_377493_1386173738_28230e75857bf20ad3a06b14d89b25c3_rle_crop_3981113833_0.png treat image : temp/1759245049_377493_1386173681_b8e0c61b5d98bee06b3da0c8dd9b33f2_rle_crop_3981113835_0.png treat image : temp/1759245049_377493_1386173385_c04549ba4e926232f109571b8c1702a1_rle_crop_3981113836_0.png treat image : temp/1759245049_377493_1386173368_68afd3ee5b19c0a12551de7108d28f97_rle_crop_3981113838_0.png treat image : temp/1759245049_377493_1386174399_5a64447a399a2fefca37c019e14faddf_rle_crop_3981113806_0.png treat image : temp/1759245049_377493_1386174355_8a0827dfade43a9de9ac141f12797e7d_rle_crop_3981113808_0.png treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113825_0.png treat image : temp/1759245049_377493_1386173837_eebc43352c9354426db2d5e7640e0bec_rle_crop_3981113826_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 : 53 time used for this insertion : 0.04079174995422363 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 53 time used for this insertion : 0.03925323486328125 save missing photos in datou_result : time spend for datou_step_exec : 4.712105989456177 time spend to save output : 0.09712624549865723 total time spend for step 7 : 4.809232234954834 step8:velours_tree Tue Sep 30 17:12:45 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 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 : 0.10031604766845703 time spend to save output : 4.029273986816406e-05 total time spend for step 8 : 0.1003563404083252 step9:send_mail_cod Tue Sep 30 17:12:45 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 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_P27241410_30-09-2025_17_12_45.pdf 27357440 imagette273574401759245165 27357441 change filename to text .change filename to text .change filename to text .imagette273574411759245165 27357442 imagette273574421759245165 27357443 change filename to text .imagette273574431759245165 27357445 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273574451759245166 27357446 change filename to text .change filename to text .imagette273574461759245166 27357447 imagette273574471759245166 27357448 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette273574481759245166 27357449 change filename to text .change filename to text .imagette273574491759245168 27357450 imagette273574501759245168 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=27241410 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/27357440,27357441,27357442,27357443,27357444,27357445,27357446,27357447,27357448,27357449,27357450?tags=pehd,metal,flou,carton,environnement,papier,pet_fonce,background,pet_clair,autre,mal_croppe args[1386174399] : ((1386174399, -0.9274821674905618, 492688767), (1386174399, 0.49052494284705156, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386174355] : ((1386174355, 3.5005540141838845, 492688767), (1386174355, 0.2967747432827014, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386174239] : ((1386174239, 2.3421001344847645, 492688767), (1386174239, 0.45444293668067565, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173934] : ((1386173934, -2.6928098669356233, 492609224), (1386173934, 1.8710775289945094, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173901] : ((1386173901, -1.4341977737380458, 492688767), (1386173901, 0.5408337876056375, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173882] : ((1386173882, 2.368413596752122, 492688767), (1386173882, 0.5873442588396228, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173859] : ((1386173859, -0.37074243112028105, 492688767), (1386173859, 0.5760206849240334, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173855] : ((1386173855, -0.2551332365260013, 492688767), (1386173855, 0.28794225293253156, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173852] : ((1386173852, -0.7834967710770802, 492688767), (1386173852, 0.5404719361051928, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173837] : ((1386173837, -1.5711416543155277, 492688767), (1386173837, 0.6865236775389668, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173815] : ((1386173815, -0.6745359487643267, 492688767), (1386173815, 0.5728396772302894, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173791] : ((1386173791, -1.4885287061003598, 492688767), (1386173791, 0.6179491071788412, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173765] : ((1386173765, -1.301465142650585, 492688767), (1386173765, 0.7447223151556285, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173738] : ((1386173738, -1.7867220970308462, 492688767), (1386173738, 0.7956026359710581, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173681] : ((1386173681, 1.2102319796606382, 492688767), (1386173681, 0.608991401685121, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173385] : ((1386173385, -1.1707003146668122, 492688767), (1386173385, 0.538269275617617, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173368] : ((1386173368, 0.05058037661641416, 492688767), (1386173368, 0.5231585663822389, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com args[1386173364] : ((1386173364, -0.5676088555462941, 492688767), (1386173364, 0.6017247998528922, 2107752395), '0.11831396283436213') We are sending mail with results at report@fotonower.com refus_total : 0.11831396283436213 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=27241410 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_P27241410_30-09-2025_17_12_45.pdf results_Auto_P27241410_30-09-2025_17_12_45.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27241410_30-09-2025_17_12_45.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','27241410','results_Auto_P27241410_30-09-2025_17_12_45.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27241410_30-09-2025_17_12_45.pdf','pdf','','0.56','0.11831396283436213') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/27241410

https://www.fotonower.com/image?json=false&list_photos_id=1386174399
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386174355
La photo est trop floue, merci de reprendre une photo.(avec le score = 3.5005540141838845)
https://www.fotonower.com/image?json=false&list_photos_id=1386174239
La photo est trop floue, merci de reprendre une photo.(avec le score = 2.3421001344847645)
https://www.fotonower.com/image?json=false&list_photos_id=1386173934
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173901
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173882
La photo est trop floue, merci de reprendre une photo.(avec le score = 2.368413596752122)
https://www.fotonower.com/image?json=false&list_photos_id=1386173859
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173855
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173852
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173837
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173815
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173791
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173765
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173738
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173681
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.2102319796606382)
https://www.fotonower.com/image?json=false&list_photos_id=1386173385
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173368
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1386173364
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 11.83%
Veuillez trouver les photos des contaminants.

exemples de contaminants: metal: https://www.fotonower.com/view/27357441?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/27357443?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/27357445?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/27357446?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/27357448?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/27357449?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27241410_30-09-2025_17_12_45.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/27357440,27357441,27357442,27357443,27357444,27357445,27357446,27357447,27357448,27357449,27357450?tags=pehd,metal,flou,carton,environnement,papier,pet_fonce,background,pet_clair,autre,mal_croppe.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 30 Sep 2025 15:12:52 GMT Content-Length: 0 Connection: close X-Message-Id: 07i6l_IhQDaKv1BTmVbTxQ 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 [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] 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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 18 time used for this insertion : 0.03653836250305176 save_final save missing photos in datou_result : time spend for datou_step_exec : 6.567775249481201 time spend to save output : 0.03682827949523926 total time spend for step 9 : 6.60460352897644 step10:split_time_score Tue Sep 30 17:12:52 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'}] (('18', 18),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 25092025 27241410 Nombre de photos uploadées : 18 / 23040 (0%) 25092025 27241410 Nombre de photos taguées (types de déchets): 0 / 18 (0%) 25092025 27241410 Nombre de photos taguées (volume) : 0 / 18 (0%) elapsed_time : load_data_split_time_score 3.337860107421875e-06 elapsed_time : order_list_meta_photo_and_scores 7.152557373046875e-06 ?????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0008673667907714844 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.6366839408874512 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.09845333397633747 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27221477_30-09-2025_16_57_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27221477 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27221477 AND mptpi.`type`=3594 To do Qualite : 0.13090677358906527 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223364_30-09-2025_17_01_48.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223364 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223364 AND mptpi.`type`=3594 To do Qualite : 0.017385886863425924 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27223367_30-09-2025_17_10_08.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223367 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27223367 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27223369 order by id desc limit 1 Qualite : 0.054117082281144785 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27224634_30-09-2025_17_02_16.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27224634 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=27224634 AND mptpi.`type`=3594 To do Qualite : 0.1281446116255144 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27224635_30-09-2025_17_10_54.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27224635 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`=27224635 AND mptpi.`type`=3594 To do Qualite : 0.027499035493827158 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27225428_30-09-2025_17_11_00.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27225428 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`=27225428 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27228443 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27253365 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236083 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236085 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236088 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236093 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236096 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27236099 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241406 order by id desc limit 1 Qualite : 0.11831396283436213 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P27241410_30-09-2025_17_12_45.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241410 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`=27241410 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27241422 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27247505 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 27247506 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'25092025': {'nb_upload': 18, '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 [1386174399, 1386174355, 1386174239, 1386173934, 1386173901, 1386173882, 1386173859, 1386173855, 1386173852, 1386173837, 1386173815, 1386173791, 1386173765, 1386173738, 1386173681, 1386173385, 1386173368, 1386173364] Looping around the photos to save general results len do output : 1 /27241410Didn'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, '3779775') ('3318', '27241410', '1386174399', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174355', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386174239', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173934', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173901', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173882', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173859', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173855', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173852', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173837', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173815', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173791', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173765', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173738', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173681', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173385', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173368', None, None, None, None, None, '3779775') ('3318', None, None, None, None, None, None, None, '3779775') ('3318', '27241410', '1386173364', None, None, None, None, None, '3779775') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 19 time used for this insertion : 0.03834128379821777 save_final save missing photos in datou_result : time spend for datou_step_exec : 10.836766481399536 time spend to save output : 0.03876757621765137 total time spend for step 10 : 10.875534057617188 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 18 set_done_treatment 67.74user 26.42system 2:17.10elapsed 68%CPU (0avgtext+0avgdata 2908840maxresident)k 21464inputs+38872outputs (1236major+2082588minor)pagefaults 0swaps