python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 3318 ' -s datou_3318 -M 0 -S 0 -U 95,95,120 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/caffe_cuda8_python3/python', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 3710548 load datou : 3318 # 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 ! Unexpected type for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? [(photo_id, hashtag_id, hashtag_type, x0, x1, y0, y1, score, seg_temp, polygons), ...] was removed should we ? chemin de la photo was removed should we ? [ (photo_id_loc, hashtag_id, hashtag_type, x0, x1, y0, y1, score, None), ...] was removed should we ? chemin de la photo was removed should we ? id de la photo (peut être local ou global) was removed should we ? chemin de la photo was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? donnée sous forme de texte was removed should we ? [ (photo_id, photo_id_loc, hashtag_type, x0, x1, y0, y1, score), ...] was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? id de la photo (peut être local ou global) was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? None was removed should we ? donnée sous forme de nombre was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? donnée sous forme de texte was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] was removed should we ? 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)) load thcls load THCL from format json or kwargs add thcl : 2847 in CacheModelConfig load pdts add pdt : 5275 in CacheModelConfig 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 : ['4102347'] with mtr_portfolio_ids : ['28828426'] and first list_photo_ids : [] new path : /proc/3710548/ 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 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 7 ; length of list_pids : 7 ; length of list_args : 7 time to download the photos : 1.1474003791809082 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 Mon Nov 24 14:20:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10998 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-11-24 14:20:34.225660: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-11-24 14:20:34.262543: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493010000 Hz 2025-11-24 14:20:34.265107: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f316c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-11-24 14:20:34.265171: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-11-24 14:20:34.271631: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-11-24 14:20:34.694380: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x313c0b20 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-11-24 14:20:34.694448: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-11-24 14:20:34.696619: 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 2025-11-24 14:20:34.698650: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-24 14:20:34.731781: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-24 14:20:34.751456: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-24 14:20:34.755983: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-24 14:20:34.790004: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-24 14:20:34.794939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-24 14:20:34.854851: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-24 14:20:34.856934: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-24 14:20:34.857380: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-24 14:20:34.859140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-24 14:20:34.859165: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-24 14:20:34.859192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-24 14:20:34.861408: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 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. 2025-11-24 14:20:35.320557: 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 2025-11-24 14:20:35.320656: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-24 14:20:35.320678: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-24 14:20:35.320697: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-24 14:20:35.320715: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-24 14:20:35.320732: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-24 14:20:35.320750: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-24 14:20:35.320767: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-24 14:20:35.322427: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-24 14:20:35.323767: 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 2025-11-24 14:20:35.323803: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-11-24 14:20:35.323821: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-24 14:20:35.323837: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-11-24 14:20:35.323853: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-11-24 14:20:35.323868: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-11-24 14:20:35.323884: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-11-24 14:20:35.323900: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-11-24 14:20:35.325120: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-11-24 14:20:35.325147: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-11-24 14:20:35.325156: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-11-24 14:20:35.325163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-11-24 14:20:35.326438: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10193 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 : [] 2025-11-24 14:20:40.403059: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 51380224 exceeds 10% of free system memory. 2025-11-24 14:20:43.970940: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-11-24 14:20:44.304985: 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 : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 36.00000 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: 37.00000 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 : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 31.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 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 : 14 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 : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 42.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 Detection mask done ! Trying to reset tf kernel 3711888 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5706 tf kernel not reseted sub process len(results) : 7 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 7 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 : 10998 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'] DEBUG bbox = [309, 1071, 483, 1191] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.00037097930908203125 nb_pixel_total : 13526 time to create 1 rle with old method : 0.014656782150268555 length of segment : 164 DEBUG bbox = [531, 1527, 1068, 1890] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.00186920166015625 nb_pixel_total : 108178 time to create 1 rle with old method : 0.11591601371765137 length of segment : 536 DEBUG bbox = [3, 1311, 54, 1410] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 9.1552734375e-05 nb_pixel_total : 3350 time to create 1 rle with old method : 0.0038962364196777344 length of segment : 46 DEBUG bbox = [411, 1308, 513, 1428] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.00015497207641601562 nb_pixel_total : 6922 time to create 1 rle with old method : 0.007830142974853516 length of segment : 94 DEBUG bbox = [303, 1092, 411, 1185] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.00014638900756835938 nb_pixel_total : 7284 time to create 1 rle with old method : 0.008201360702514648 length of segment : 94 DEBUG bbox = [0, 156, 1032, 1653] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.04806709289550781 nb_pixel_total : 1163942 time to create 1 rle with new method : 0.07508444786071777 length of segment : 1536 DEBUG bbox = [0, 0, 1053, 1566] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.018515348434448242 nb_pixel_total : 1162354 time to create 1 rle with new method : 1.0155730247497559 length of segment : 1538 DEBUG bbox = [891, 1170, 1053, 1326] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.0003151893615722656 nb_pixel_total : 15900 time to create 1 rle with old method : 0.018567800521850586 length of segment : 161 DEBUG bbox = [9, 960, 144, 1032] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.0002040863037109375 nb_pixel_total : 5962 time to create 1 rle with old method : 0.010675668716430664 length of segment : 158 DEBUG bbox = [300, 1068, 432, 1188] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.0002887248992919922 nb_pixel_total : 8830 time to create 1 rle with old method : 0.010197162628173828 length of segment : 105 DEBUG bbox = [513, 1506, 1080, 1905] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.0023756027221679688 nb_pixel_total : 110851 time to create 1 rle with old method : 0.1217646598815918 length of segment : 543 DEBUG bbox = [492, 1515, 1071, 1899] DEBUG masks shape = (1080, 1920) time for calcul the mask position with numpy : 0.002245664596557617 nb_pixel_total : 108669 time to create 1 rle with old method : 0.12354922294616699 length of segment : 571 time spent for convertir_results : 3.0157220363616943 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 12 chid ids of type : 3594 Number RLEs to save : 5546 save missing photos in datou_result : time spend for datou_step_exec : 26.993449926376343 time spend to save output : 0.4270355701446533 total time spend for step 1 : 27.420485496520996 step2:crop_condition Mon Nov 24 14:20:57 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 : 7 ! batch 1 Loaded 12 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 ! 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/1763990458_3710548 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(1763990459), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709745_0.png', 0, 92, 94, 0, 1763990459,'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(1763990459), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709744_0.png', 0, 111, 94, 0, 1763990459,'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(1763990459), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709749_0.png', 0, 72, 134, 0, 1763990459,'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 : 1.1452674865722656 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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/1763990459_3710548 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(1763990460), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872033_f5288b4b8996c106ad98d6456f263ba2_rle_crop_4043709741_0.png', 0, 109, 159, 0, 1763990460,'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(1763990460), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709750_0.png', 0, 107, 104, 0, 1763990460,'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 : 1.2032678127288818 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! 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 : 7 About to insert : list_path_to_insert length 7 new photo from crops ! About to upload 7 photos upload in portfolio : 3736932 init cache_photo without model_param we have 7 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1763990472_3710548 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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709743_0.png', 0, 86, 45, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709742_0.png', 0, 355, 531, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709746_0.png', 0, 1496, 996, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709747_0.png', 0, 1510, 1007, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709748_0.png', 0, 137, 162, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709751_0.png', 0, 363, 540, 0, 1763990473,'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(1763990473), 0.0, 0.0, 14, '', 0, 0, '1763990429_3710548_1395872013_eae0fcd0c805b169ec75de90f0a30579_rle_crop_4043709752_0.png', 0, 344, 564, 0, 1763990473,'0',0) batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 7 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.794095754623413 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] Looping around the photos to save general results len do output : 12 /1395904495Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904496Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904498Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904501Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904502Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904538Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904539Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904540Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904541Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904542Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904543Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1395904544Didn'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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 43 time used for this insertion : 0.016675949096679688 save_final save missing photos in datou_result : time spend for datou_step_exec : 16.282020807266235 time spend to save output : 0.017383813858032227 total time spend for step 2 : 16.299404621124268 step3:rle_unique_nms_with_priority Mon Nov 24 14:21:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 12 chid ids of type : 3594 ++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.43247342109680176 time for calcul the mask position with numpy : 0.15641522407531738 nb_pixel_total : 2060074 time to create 1 rle with new method : 0.1578843593597412 time for calcul the mask position with numpy : 0.006027936935424805 nb_pixel_total : 13526 time to create 1 rle with old method : 0.014993667602539062 create new chi : 0.3458540439605713 time to delete rle : 0.03534507751464844 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1408 TO DO : save crop sub photo not yet done ! save time : 0.14517712593078613 No data in photo_id : 1395872031 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.1895594596862793 time for calcul the mask position with numpy : 0.09432315826416016 nb_pixel_total : 1962072 time to create 1 rle with new method : 0.10265588760375977 time for calcul the mask position with numpy : 0.0061702728271484375 nb_pixel_total : 3350 time to create 1 rle with old method : 0.0038864612579345703 time for calcul the mask position with numpy : 0.0064966678619384766 nb_pixel_total : 108178 time to create 1 rle with old method : 0.12140107154846191 create new chi : 0.3452010154724121 time to delete rle : 0.00036644935607910156 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2244 TO DO : save crop sub photo not yet done ! save time : 0.19950103759765625 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.13537883758544922 time for calcul the mask position with numpy : 0.05120205879211426 nb_pixel_total : 909658 time to create 1 rle with new method : 0.12342596054077148 time for calcul the mask position with numpy : 0.03706979751586914 nb_pixel_total : 1149736 time to create 1 rle with new method : 0.08631277084350586 time for calcul the mask position with numpy : 0.00643467903137207 nb_pixel_total : 7284 time to create 1 rle with old method : 0.008224725723266602 time for calcul the mask position with numpy : 0.0065975189208984375 nb_pixel_total : 6922 time to create 1 rle with old method : 0.007807016372680664 create new chi : 0.34330177307128906 time to delete rle : 0.0007157325744628906 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 4528 TO DO : save crop sub photo not yet done ! save time : 0.35425448417663574 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.05370521545410156 time for calcul the mask position with numpy : 0.031545162200927734 nb_pixel_total : 907633 time to create 1 rle with new method : 0.12071704864501953 time for calcul the mask position with numpy : 0.0061914920806884766 nb_pixel_total : 1220 time to create 1 rle with old method : 0.0014255046844482422 time for calcul the mask position with numpy : 0.006120443344116211 nb_pixel_total : 2393 time to create 1 rle with old method : 0.002807140350341797 time for calcul the mask position with numpy : 0.014806985855102539 nb_pixel_total : 1162354 time to create 1 rle with new method : 0.08328485488891602 create new chi : 0.283449649810791 time to delete rle : 0.0005047321319580078 batch 1 Loaded 7 chid ids of type : 3594 +++++Number RLEs to save : 4262 TO DO : save crop sub photo not yet done ! save time : 0.31383752822875977 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.0407559871673584 time for calcul the mask position with numpy : 0.06658196449279785 nb_pixel_total : 1953919 time to create 1 rle with new method : 0.11335587501525879 time for calcul the mask position with numpy : 0.006750822067260742 nb_pixel_total : 110851 time to create 1 rle with old method : 0.12320065498352051 time for calcul the mask position with numpy : 0.006054878234863281 nb_pixel_total : 8830 time to create 1 rle with old method : 0.009737253189086914 create new chi : 0.3337433338165283 time to delete rle : 0.00038313865661621094 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2376 TO DO : save crop sub photo not yet done ! save time : 0.19939780235290527 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.0336153507232666 time for calcul the mask position with numpy : 0.018616914749145508 nb_pixel_total : 1964931 time to create 1 rle with new method : 0.13057780265808105 time for calcul the mask position with numpy : 0.0071163177490234375 nb_pixel_total : 108669 time to create 1 rle with old method : 0.12333488464355469 create new chi : 0.29027533531188965 time to delete rle : 0.00032782554626464844 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2222 TO DO : save crop sub photo not yet done ! save time : 0.1980440616607666 map_output_result : {1395872033: (0.0, 'Should be the crop_list due to order', 0), 1395872031: (0.0, 'Should be the crop_list due to order', 0.0), 1395872029: (0.0, 'Should be the crop_list due to order', 0), 1395872025: (0.0, 'Should be the crop_list due to order', 0), 1395872017: (0.0, 'Should be the crop_list due to order', 0), 1395872015: (0.0, 'Should be the crop_list due to order', 0), 1395872013: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : rle_unique_nms_with_priority we use saveGeneral [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] Looping around the photos to save general results len do output : 7 /1395872033.Didn't retrieve data . /1395872031.Didn't retrieve data . /1395872029.Didn't retrieve data . /1395872025.Didn't retrieve data . /1395872017.Didn't retrieve data . /1395872015.Didn't retrieve data . /1395872013.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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.015324592590332031 save_final save missing photos in datou_result : time spend for datou_step_exec : 4.5296242237091064 time spend to save output : 0.01563239097595215 total time spend for step 3 : 4.545256614685059 step4:ventilate_hashtags_in_portfolio Mon Nov 24 14:21:18 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 : 28828426 get user id for portfolio 28828426 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`=28828426 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','pehd','carton','papier','background','autre','metal','pet_clair','pet_fonce','mal_croppe','environnement')) AND mptpi.`min_score`=0.5 To do 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`=28828426 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','pehd','carton','papier','background','autre','metal','pet_clair','pet_fonce','mal_croppe','environnement')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/28831321,28831322,28831323,28831324,28831325,28831326,28831327,28831328,28831329,28831330,28831331?tags=metal,mal_croppe,carton,environnement,flou,pet_clair,pet_fonce,background,papier,autre,pehd Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] Looping around the photos to save general results len do output : 1 /28828426. 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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.018866777420043945 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.48845434188842773 time spend to save output : 0.019184589385986328 total time spend for step 4 : 0.5076389312744141 step5:final Mon Nov 24 14:21:19 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 : {1395872033: ('0.11416421105612322',), 1395872031: ('0.11416421105612322',), 1395872029: ('0.11416421105612322',), 1395872025: ('0.11416421105612322',), 1395872017: ('0.11416421105612322',), 1395872015: ('0.11416421105612322',), 1395872013: ('0.11416421105612322',)} new output for save of step final : {1395872033: ('0.11416421105612322',), 1395872031: ('0.11416421105612322',), 1395872029: ('0.11416421105612322',), 1395872025: ('0.11416421105612322',), 1395872017: ('0.11416421105612322',), 1395872015: ('0.11416421105612322',), 1395872013: ('0.11416421105612322',)} [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] Looping around the photos to save general results len do output : 7 /1395872033.Didn't retrieve data . /1395872031.Didn't retrieve data . /1395872029.Didn't retrieve data . /1395872025.Didn't retrieve data . /1395872017.Didn't retrieve data . /1395872015.Didn't retrieve data . /1395872013.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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 21 time used for this insertion : 0.017104387283325195 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.152177095413208 time spend to save output : 0.017517805099487305 total time spend for step 5 : 0.1696949005126953 step6:blur_detection Mon Nov 24 14:21:19 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/1763990429_3710548_1395872033_f5288b4b8996c106ad98d6456f263ba2.jpg resize: (1080, 1920) 1395872033 -2.0019621052024963 treat image : temp/1763990429_3710548_1395872031_17ea4fae0a4efb797c0f9cd5ca8f5381.jpg resize: (1080, 1920) 1395872031 -1.2946226119187252 treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f.jpg resize: (1080, 1920) 1395872029 -2.61535979184964 treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8.jpg resize: (1080, 1920) 1395872025 -0.9310434894335363 treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363.jpg resize: (1080, 1920) 1395872017 -1.3619753059977866 treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb.jpg resize: (1080, 1920) 1395872015 -2.6894100333332043 treat image : temp/1763990429_3710548_1395872013_eae0fcd0c805b169ec75de90f0a30579.jpg resize: (1080, 1920) 1395872013 -2.3152260303449994 treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709745_0.png resize: (94, 92) 1395904495 2.4657488188446557 treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709744_0.png resize: (94, 111) 1395904496 -1.6753945411691322 treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709749_0.png resize: (134, 72) 1395904498 -1.909759529715976 treat image : temp/1763990429_3710548_1395872033_f5288b4b8996c106ad98d6456f263ba2_rle_crop_4043709741_0.png resize: (159, 109) 1395904501 -0.7397186677915052 treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709750_0.png resize: (104, 107) 1395904502 -0.05051033633701537 treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709743_0.png resize: (45, 86) 1395904538 2.836163242164688 treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709742_0.png resize: (531, 355) 1395904539 0.4110768780118306 treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709746_0.png resize: (996, 1496) 1395904540 -0.9624345813192281 treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709747_0.png resize: (1007, 1510) 1395904541 -2.084587481625769 treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709748_0.png resize: (162, 137) 1395904542 -3.6873910755182653 treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709751_0.png resize: (540, 363) 1395904543 0.29199113810050376 treat image : temp/1763990429_3710548_1395872013_eae0fcd0c805b169ec75de90f0a30579_rle_crop_4043709752_0.png resize: (564, 344) 1395904544 -0.3239323411022473 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 : 19 time used for this insertion : 0.032646894454956055 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 19 time used for this insertion : 0.016553878784179688 save missing photos in datou_result : time spend for datou_step_exec : 7.154926300048828 time spend to save output : 0.05520772933959961 total time spend for step 6 : 7.210134029388428 step7:brightness Mon Nov 24 14:21:26 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/1763990429_3710548_1395872033_f5288b4b8996c106ad98d6456f263ba2.jpg treat image : temp/1763990429_3710548_1395872031_17ea4fae0a4efb797c0f9cd5ca8f5381.jpg treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f.jpg treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8.jpg treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363.jpg treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb.jpg treat image : temp/1763990429_3710548_1395872013_eae0fcd0c805b169ec75de90f0a30579.jpg treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709745_0.png treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709744_0.png treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709749_0.png treat image : temp/1763990429_3710548_1395872033_f5288b4b8996c106ad98d6456f263ba2_rle_crop_4043709741_0.png treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709750_0.png treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709743_0.png treat image : temp/1763990429_3710548_1395872029_9aecaa7fc50f10850ddd9cec99b8643f_rle_crop_4043709742_0.png treat image : temp/1763990429_3710548_1395872025_ac89ec21e6ca6d174929eca2ff04a9f8_rle_crop_4043709746_0.png treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709747_0.png treat image : temp/1763990429_3710548_1395872017_d18c6431c7a183915e10052caedaa363_rle_crop_4043709748_0.png treat image : temp/1763990429_3710548_1395872015_fc0078c98f79ed7d2b083a543f8625bb_rle_crop_4043709751_0.png treat image : temp/1763990429_3710548_1395872013_eae0fcd0c805b169ec75de90f0a30579_rle_crop_4043709752_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 : 19 time used for this insertion : 0.015495061874389648 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 19 time used for this insertion : 0.01445627212524414 save missing photos in datou_result : time spend for datou_step_exec : 2.392759323120117 time spend to save output : 0.035780906677246094 total time spend for step 7 : 2.4285402297973633 step8:velours_tree Mon Nov 24 14:21:28 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 : 0.13785934448242188 time spend to save output : 3.4332275390625e-05 total time spend for step 8 : 0.1378936767578125 step9:send_mail_cod Mon Nov 24 14:21:29 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/workarea/git/Velours/python in order to get the selector url, please entre the license of selector results_Auto_P28828426_24-11-2025_14_21_29.pdf 28831321 change filename to text .change filename to text .change filename to text .change filename to text .imagette288313211763990489 28831322 imagette288313221763990489 28831323 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 .imagette288313231763990489 28831325 imagette288313251763990490 28831326 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 .imagette288313261763990490 28831327 imagette288313271763990492 28831328 imagette288313281763990492 28831329 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 .imagette288313291763990492 28831330 change filename to text .change filename to text .change filename to text .imagette288313301763990494 28831331 imagette288313311763990494 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=28828426 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/28831321,28831322,28831323,28831324,28831325,28831326,28831327,28831328,28831329,28831330,28831331?tags=metal,mal_croppe,carton,environnement,flou,pet_clair,pet_fonce,background,papier,autre,pehd args[1395872033] : ((1395872033, -2.0019621052024963, 492609224), (1395872033, 0.7676576079387981, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872031] : ((1395872031, -1.2946226119187252, 492688767), (1395872031, 0.6538286755229039, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872029] : ((1395872029, -2.61535979184964, 492609224), (1395872029, 0.7248017951789147, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872025] : ((1395872025, -0.9310434894335363, 492688767), (1395872025, 0.46950207126584464, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872017] : ((1395872017, -1.3619753059977866, 492688767), (1395872017, 0.8482414511292179, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872015] : ((1395872015, -2.6894100333332043, 492609224), (1395872015, 0.46046839687906943, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com args[1395872013] : ((1395872013, -2.3152260303449994, 492609224), (1395872013, 0.6252513093597803, 2107752395), '0.11416421105612322') We are sending mail with results at report@fotonower.com refus_total : 0.11416421105612322 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=28828426 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_P28828426_24-11-2025_14_21_29.pdf results_Auto_P28828426_24-11-2025_14_21_29.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828426_24-11-2025_14_21_29.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','28828426','results_Auto_P28828426_24-11-2025_14_21_29.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828426_24-11-2025_14_21_29.pdf','pdf','','0.59','0.11416421105612322') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/28828426

https://www.fotonower.com/image?json=false&list_photos_id=1395872033
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872031
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872029
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872025
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872017
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872015
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1395872013
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 11.42%
Veuillez trouver les photos des contaminants.

exemples de contaminants: metal: https://www.fotonower.com/view/28831321?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/28831323?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/28831326?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/28831329?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/28831330?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828426_24-11-2025_14_21_29.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/28831321,28831322,28831323,28831324,28831325,28831326,28831327,28831328,28831329,28831330,28831331?tags=metal,mal_croppe,carton,environnement,flou,pet_clair,pet_fonce,background,papier,autre,pehd.


L'équipe Fotonower 202 b'' Date: Mon, 24 Nov 2025 13:21:36 GMT Content-Length: 0 Connection: close Server: nginx X-Message-Id: M5pQ8DYdTJ6z7Bt0ZyRcRQ 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 [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] 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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 7 time used for this insertion : 0.01520848274230957 save_final save missing photos in datou_result : time spend for datou_step_exec : 7.254106044769287 time spend to save output : 0.015383481979370117 total time spend for step 9 : 7.269489526748657 step10:split_time_score Mon Nov 24 14:21:36 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure begin split time score Catched exception ! Connect or reconnect ! TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('09', 87),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 24112025 28828426 Nombre de photos uploadées : 87 / 23040 (0%) 24112025 28828426 Nombre de photos taguées (types de déchets): 0 / 87 (0%) 24112025 28828426 Nombre de photos taguées (volume) : 0 / 87 (0%) elapsed_time : load_data_split_time_score 1.6689300537109375e-06 elapsed_time : order_list_meta_photo_and_scores 5.245208740234375e-06 ??????????????????????????????????????????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0038003921508789062 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.23335480690002441 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 : 0.1292190272955247 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828426_24-11-2025_14_21_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828426 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`=28828426 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828428 order by id desc limit 1 Qualite : 0.07008904145622898 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828431_24-11-2025_13_52_11.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828431 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`=28828431 AND mptpi.`type`=3594 To do Qualite : 0.25237177426268853 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828433_24-11-2025_12_21_46.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828433 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`=28828433 AND mptpi.`type`=3594 To do Qualite : 0.021958550347222217 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828435_24-11-2025_12_41_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828435 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`=28828435 AND mptpi.`type`=3594 To do Qualite : 0.05147855581275721 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28828444_24-11-2025_12_11_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28828444 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`=28828444 AND mptpi.`type`=3594 To do Qualite : 0.030636240206552704 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28829905_24-11-2025_13_41_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28829905 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`=28829905 AND mptpi.`type`=3594 To do Qualite : 0.03575169994212963 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P28829907_24-11-2025_13_23_01.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 28829907 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`=28829907 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'24112025': {'nb_upload': 87, '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 [1395872033, 1395872031, 1395872029, 1395872025, 1395872017, 1395872015, 1395872013] Looping around the photos to save general results len do output : 1 /28828426Didn'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, '4102347') ('3318', None, '1395872033', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872031', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872029', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872025', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872017', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872015', None, None, None, None, None, '4102347') ('3318', None, None, None, None, None, None, None, '4102347') ('3318', None, '1395872013', None, None, None, None, None, '4102347') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.017092466354370117 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.1207778453826904 time spend to save output : 0.01726531982421875 total time spend for step 10 : 2.138043165206909 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 7 set_done_treatment 36.91user 17.29system 1:12.81elapsed 74%CPU (0avgtext+0avgdata 2736912maxresident)k 2324312inputs+32552outputs (8976major+1290954minor)pagefaults 0swaps