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 : 2716454 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 : ['3410773'] with mtr_portfolio_ids : ['25543266'] and first list_photo_ids : [] new path : /proc/2716454/ 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 , BFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 9 ; length of list_pids : 9 ; length of list_args : 9 time to download the photos : 1.2834997177124023 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 Thu Jul 31 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 : 8759 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-07-31 14:20:33.148081: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-31 14:20:33.175306: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-31 14:20:33.177457: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fa720000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-31 14:20:33.177520: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-31 14:20:33.181272: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-31 14:20:33.310849: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3526dbf0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-31 14:20:33.310898: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-31 14:20:33.312213: 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 2025-07-31 14:20:33.312642: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:20:33.315819: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:20:33.318749: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:20:33.319297: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:20:33.321788: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:20:33.322797: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:20:33.327213: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:20:33.328532: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:20:33.328605: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:20:33.329300: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-31 14:20:33.329315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-31 14:20:33.329324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-31 14:20:33.330515: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8091 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. 2025-07-31 14:20:33.589852: 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 2025-07-31 14:20:33.589983: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:20:33.590012: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:20:33.590037: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:20:33.590061: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:20:33.590085: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:20:33.590109: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:20:33.590133: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:20:33.592047: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:20:33.593251: 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 2025-07-31 14:20:33.593279: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:20:33.593293: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:20:33.593306: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:20:33.593318: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:20:33.593331: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:20:33.593343: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:20:33.593356: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:20:33.594399: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:20:33.594432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-31 14:20:33.594440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-31 14:20:33.594447: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-31 14:20:33.595550: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8091 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 : [] 2025-07-31 14:20:41.090600: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:20:41.275091: 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 : 9 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 24.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 31.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 57.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 2 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 17.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 22.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 35.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 18.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 17.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 Detection mask done ! Trying to reset tf kernel 2717082 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2671 tf kernel not reseted sub process len(results) : 9 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 9 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 : 7960 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl2847 Catched exception ! Connect or reconnect ! thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] time for calcul the mask position with numpy : 0.0004298686981201172 nb_pixel_total : 14949 time to create 1 rle with old method : 0.017355680465698242 length of segment : 173 time for calcul the mask position with numpy : 0.00019216537475585938 nb_pixel_total : 10011 time to create 1 rle with old method : 0.011554718017578125 length of segment : 167 time for calcul the mask position with numpy : 0.001753091812133789 nb_pixel_total : 99687 time to create 1 rle with old method : 0.10721325874328613 length of segment : 507 time for calcul the mask position with numpy : 0.0002117156982421875 nb_pixel_total : 8910 time to create 1 rle with old method : 0.009647369384765625 length of segment : 101 time for calcul the mask position with numpy : 0.0001652240753173828 nb_pixel_total : 6744 time to create 1 rle with old method : 0.00765538215637207 length of segment : 95 time for calcul the mask position with numpy : 6.937980651855469e-05 nb_pixel_total : 2531 time to create 1 rle with old method : 0.002838611602783203 length of segment : 62 time for calcul the mask position with numpy : 0.0016527175903320312 nb_pixel_total : 109031 time to create 1 rle with old method : 0.11629986763000488 length of segment : 560 time for calcul the mask position with numpy : 0.0001938343048095703 nb_pixel_total : 8854 time to create 1 rle with old method : 0.00967860221862793 length of segment : 172 time for calcul the mask position with numpy : 0.00011968612670898438 nb_pixel_total : 5827 time to create 1 rle with old method : 0.006529569625854492 length of segment : 100 time for calcul the mask position with numpy : 0.00017952919006347656 nb_pixel_total : 11489 time to create 1 rle with old method : 0.012909889221191406 length of segment : 81 time for calcul the mask position with numpy : 0.0017573833465576172 nb_pixel_total : 117305 time to create 1 rle with old method : 0.12595462799072266 length of segment : 556 time for calcul the mask position with numpy : 0.0001850128173828125 nb_pixel_total : 10073 time to create 1 rle with old method : 0.011144876480102539 length of segment : 114 time for calcul the mask position with numpy : 0.0015316009521484375 nb_pixel_total : 115613 time to create 1 rle with old method : 0.12360525131225586 length of segment : 523 time for calcul the mask position with numpy : 0.01315617561340332 nb_pixel_total : 688063 time to create 1 rle with new method : 0.033814430236816406 length of segment : 998 time for calcul the mask position with numpy : 0.00014472007751464844 nb_pixel_total : 6397 time to create 1 rle with old method : 0.007354259490966797 length of segment : 79 time for calcul the mask position with numpy : 0.00017905235290527344 nb_pixel_total : 10272 time to create 1 rle with old method : 0.011911869049072266 length of segment : 103 time for calcul the mask position with numpy : 0.0036377906799316406 nb_pixel_total : 120251 time to create 1 rle with old method : 0.12767982482910156 length of segment : 550 time for calcul the mask position with numpy : 0.0002875328063964844 nb_pixel_total : 8889 time to create 1 rle with old method : 0.01010274887084961 length of segment : 119 time for calcul the mask position with numpy : 0.00042724609375 nb_pixel_total : 19505 time to create 1 rle with old method : 0.02150750160217285 length of segment : 130 time for calcul the mask position with numpy : 0.6901628971099854 nb_pixel_total : 1542785 time to create 1 rle with new method : 0.08048129081726074 length of segment : 1256 time for calcul the mask position with numpy : 0.00030875205993652344 nb_pixel_total : 8863 time to create 1 rle with old method : 0.010391712188720703 length of segment : 181 time spent for convertir_results : 2.715510129928589 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 21 chid ids of type : 3594 Number RLEs to save : 6627 save missing photos in datou_result : time spend for datou_step_exec : 27.15493416786194 time spend to save output : 0.4530653953552246 total time spend for step 1 : 27.607999563217163 step2:crop_condition Thu Jul 31 14:20:58 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure Loading chi in step crop with photo_hashtag_type : 3594 Loading chi in step crop for list_pids : 9 ! batch 1 Loaded 21 chid ids of type : 3594 ++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 5 About to insert : list_path_to_insert length 5 new photo from crops ! About to upload 5 photos upload in portfolio : 3736932 init cache_photo without model_param we have 5 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1753964458_2716454 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 5 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.4500024318695068 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/1753964461_2716454 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 0.7789027690887451 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 ! 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 : 14 About to insert : list_path_to_insert length 14 new photo from crops ! About to upload 14 photos upload in portfolio : 3736932 init cache_photo without model_param we have 14 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1753964473_2716454 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 14 photos in the portfolio 3736932 time of upload the photos Elapsed time : 4.163086414337158 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] Looping around the photos to save general results len do output : 21 /1374599622Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599623Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599624Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599625Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599626Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599627Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599628Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599672Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599673Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599674Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599675Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599676Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599677Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599678Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599680Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599681Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599682Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599684Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599685Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374599688Didn'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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 72 time used for this insertion : 0.015694379806518555 save_final save missing photos in datou_result : time spend for datou_step_exec : 19.689815521240234 time spend to save output : 0.016306161880493164 total time spend for step 2 : 19.706121683120728 step3:rle_unique_nms_with_priority Thu Jul 31 14:21:17 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 21 chid ids of type : 3594 ++++++++++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.10921835899353027 time for calcul the mask position with numpy : 0.08292603492736816 nb_pixel_total : 2058651 time to create 1 rle with new method : 0.3045637607574463 time for calcul the mask position with numpy : 0.010673284530639648 nb_pixel_total : 14949 time to create 1 rle with old method : 0.02080392837524414 create new chi : 0.4291346073150635 time to delete rle : 0.028766155242919922 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1426 TO DO : save crop sub photo not yet done ! save time : 0.11852622032165527 No data in photo_id : 1374575847 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.17607712745666504 time for calcul the mask position with numpy : 0.08422279357910156 nb_pixel_total : 2063589 time to create 1 rle with new method : 0.4334237575531006 time for calcul the mask position with numpy : 0.006739377975463867 nb_pixel_total : 10011 time to create 1 rle with old method : 0.011365413665771484 create new chi : 0.5461618900299072 time to delete rle : 0.00025725364685058594 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 1414 TO DO : save crop sub photo not yet done ! save time : 0.11341428756713867 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.04150724411010742 time for calcul the mask position with numpy : 0.7067141532897949 nb_pixel_total : 1973913 time to create 1 rle with new method : 0.40135717391967773 time for calcul the mask position with numpy : 0.007062673568725586 nb_pixel_total : 99687 time to create 1 rle with old method : 0.11438131332397461 create new chi : 1.2395646572113037 time to delete rle : 0.0003440380096435547 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 2094 TO DO : save crop sub photo not yet done ! save time : 0.1818535327911377 nb_obj : 5 nb_hashtags : 3 time to prepare the origin masks : 0.502626895904541 time for calcul the mask position with numpy : 0.27875828742980957 nb_pixel_total : 1937530 time to create 1 rle with new method : 0.2597239017486572 time for calcul the mask position with numpy : 0.005915403366088867 nb_pixel_total : 8854 time to create 1 rle with old method : 0.009827613830566406 time for calcul the mask position with numpy : 0.006735086441040039 nb_pixel_total : 109031 time to create 1 rle with old method : 0.11887693405151367 time for calcul the mask position with numpy : 0.006070137023925781 nb_pixel_total : 2531 time to create 1 rle with old method : 0.002802610397338867 time for calcul the mask position with numpy : 0.0063092708587646484 nb_pixel_total : 6744 time to create 1 rle with old method : 0.007321357727050781 time for calcul the mask position with numpy : 0.0062100887298583984 nb_pixel_total : 8910 time to create 1 rle with old method : 0.009962797164916992 create new chi : 0.7280850410461426 time to delete rle : 0.0004172325134277344 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 3060 TO DO : save crop sub photo not yet done ! save time : 0.23037290573120117 nb_obj : 3 nb_hashtags : 1 time to prepare the origin masks : 0.06499457359313965 time for calcul the mask position with numpy : 0.01854705810546875 nb_pixel_total : 1938979 time to create 1 rle with new method : 0.06728243827819824 time for calcul the mask position with numpy : 0.006787300109863281 nb_pixel_total : 117305 time to create 1 rle with old method : 0.131056547164917 time for calcul the mask position with numpy : 0.006623029708862305 nb_pixel_total : 11489 time to create 1 rle with old method : 0.013025045394897461 time for calcul the mask position with numpy : 0.006194353103637695 nb_pixel_total : 5827 time to create 1 rle with old method : 0.00677037239074707 create new chi : 0.2568173408508301 time to delete rle : 0.00044226646423339844 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 2554 TO DO : save crop sub photo not yet done ! save time : 0.20088505744934082 nb_obj : 4 nb_hashtags : 1 time to prepare the origin masks : 0.07413196563720703 time for calcul the mask position with numpy : 0.8202383518218994 nb_pixel_total : 1253454 time to create 1 rle with new method : 0.0993657112121582 time for calcul the mask position with numpy : 0.006262540817260742 nb_pixel_total : 6397 time to create 1 rle with old method : 0.007726907730102539 time for calcul the mask position with numpy : 0.011481046676635742 nb_pixel_total : 688063 time to create 1 rle with new method : 0.12170600891113281 time for calcul the mask position with numpy : 0.006964921951293945 nb_pixel_total : 115613 time to create 1 rle with old method : 0.16046667098999023 time for calcul the mask position with numpy : 0.007863759994506836 nb_pixel_total : 10073 time to create 1 rle with old method : 0.011742115020751953 create new chi : 1.2637970447540283 time to delete rle : 0.0007379055023193359 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 4508 TO DO : save crop sub photo not yet done ! save time : 0.2826817035675049 nb_obj : 4 nb_hashtags : 3 time to prepare the origin masks : 0.07852697372436523 time for calcul the mask position with numpy : 0.09298157691955566 nb_pixel_total : 1914683 time to create 1 rle with new method : 0.6000065803527832 time for calcul the mask position with numpy : 0.007697343826293945 nb_pixel_total : 19505 time to create 1 rle with old method : 0.022347450256347656 time for calcul the mask position with numpy : 0.007741689682006836 nb_pixel_total : 8889 time to create 1 rle with old method : 0.010368824005126953 time for calcul the mask position with numpy : 0.008199691772460938 nb_pixel_total : 120251 time to create 1 rle with old method : 0.13593387603759766 time for calcul the mask position with numpy : 0.0072727203369140625 nb_pixel_total : 10272 time to create 1 rle with old method : 0.011600971221923828 create new chi : 0.9158010482788086 time to delete rle : 0.00046563148498535156 batch 1 Loaded 9 chid ids of type : 3594 ++++Number RLEs to save : 2884 TO DO : save crop sub photo not yet done ! save time : 0.21418428421020508 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.047042131423950195 time for calcul the mask position with numpy : 0.009569168090820312 nb_pixel_total : 523507 time to create 1 rle with new method : 0.07095623016357422 time for calcul the mask position with numpy : 0.006169795989990234 nb_pixel_total : 7308 time to create 1 rle with old method : 0.0083160400390625 time for calcul the mask position with numpy : 0.0169980525970459 nb_pixel_total : 1542785 time to create 1 rle with new method : 0.12688446044921875 create new chi : 0.23946571350097656 time to delete rle : 0.0003502368927001953 batch 1 Loaded 5 chid ids of type : 3594 +++Number RLEs to save : 3881 TO DO : save crop sub photo not yet done ! save time : 0.26589298248291016 map_output_result : {1374576031: (0.0, 'Should be the crop_list due to order', 0), 1374575847: (0.0, 'Should be the crop_list due to order', 0.0), 1374575829: (0.0, 'Should be the crop_list due to order', 0), 1374575821: (0.0, 'Should be the crop_list due to order', 0), 1374575819: (0.0, 'Should be the crop_list due to order', 0), 1374575817: (0.0, 'Should be the crop_list due to order', 0), 1374575815: (0.0, 'Should be the crop_list due to order', 0), 1374575783: (0.0, 'Should be the crop_list due to order', 0), 1374575780: (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 [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] Looping around the photos to save general results len do output : 9 /1374576031.Didn't retrieve data . /1374575847.Didn't retrieve data . /1374575829.Didn't retrieve data . /1374575821.Didn't retrieve data . /1374575819.Didn't retrieve data . /1374575817.Didn't retrieve data . /1374575815.Didn't retrieve data . /1374575783.Didn't retrieve data . /1374575780.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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 27 time used for this insertion : 0.013005971908569336 save_final save missing photos in datou_result : time spend for datou_step_exec : 8.679836511611938 time spend to save output : 0.013341426849365234 total time spend for step 3 : 8.693177938461304 step4:ventilate_hashtags_in_portfolio Thu Jul 31 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 beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 25543266 get user id for portfolio 25543266 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`=25543266 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','papier','environnement','pet_clair','pet_fonce','carton','metal','autre','pehd','flou')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25543266 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','papier','environnement','pet_clair','pet_fonce','carton','metal','autre','pehd','flou')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25543266 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('background','mal_croppe','papier','environnement','pet_clair','pet_fonce','carton','metal','autre','pehd','flou')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/25544043,25544044,25544045,25544046,25544047,25544048,25544049,25544050,25544051,25544052,25544053?tags=background,mal_croppe,papier,environnement,pet_clair,pet_fonce,carton,metal,autre,pehd,flou Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] Looping around the photos to save general results len do output : 1 /25543266. 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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.011862993240356445 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.7067205905914307 time spend to save output : 0.012082338333129883 total time spend for step 4 : 1.7188029289245605 step5:final Thu Jul 31 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 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 : {1374576031: ('0.15670513974622782',), 1374575847: ('0.15670513974622782',), 1374575829: ('0.15670513974622782',), 1374575821: ('0.15670513974622782',), 1374575819: ('0.15670513974622782',), 1374575817: ('0.15670513974622782',), 1374575815: ('0.15670513974622782',), 1374575783: ('0.15670513974622782',), 1374575780: ('0.15670513974622782',)} new output for save of step final : {1374576031: ('0.15670513974622782',), 1374575847: ('0.15670513974622782',), 1374575829: ('0.15670513974622782',), 1374575821: ('0.15670513974622782',), 1374575819: ('0.15670513974622782',), 1374575817: ('0.15670513974622782',), 1374575815: ('0.15670513974622782',), 1374575783: ('0.15670513974622782',), 1374575780: ('0.15670513974622782',)} [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] Looping around the photos to save general results len do output : 9 /1374576031.Didn't retrieve data . /1374575847.Didn't retrieve data . /1374575829.Didn't retrieve data . /1374575821.Didn't retrieve data . /1374575819.Didn't retrieve data . /1374575817.Didn't retrieve data . /1374575815.Didn't retrieve data . /1374575783.Didn't retrieve data . /1374575780.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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 27 time used for this insertion : 0.014595508575439453 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.11922645568847656 time spend to save output : 0.014966011047363281 total time spend for step 5 : 0.13419246673583984 step6:blur_detection Thu Jul 31 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 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/1753964429_2716454_1374576031_89177f85b024ad637d419cb38128129a.jpg resize: (1080, 1920) 1374576031 0.6683890926405982 treat image : temp/1753964429_2716454_1374575847_e984dcb4c02e6806309c8086ff617a26.jpg resize: (1080, 1920) 1374575847 -1.1361532353356012 treat image : temp/1753964429_2716454_1374575829_59538cd84d686b28fd5d9bb14ce6176c.jpg resize: (1080, 1920) 1374575829 -2.052795897703317 treat image : temp/1753964429_2716454_1374575821_027a0e39f6dd2cbc5bfbc51eac5a3565.jpg resize: (1080, 1920) 1374575821 -4.209749648628418 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835.jpg resize: (1080, 1920) 1374575819 -1.1373563907342847 treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb.jpg resize: (1080, 1920) 1374575817 -3.575745864859214 treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6.jpg resize: (1080, 1920) 1374575815 1.416083603655322 treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db.jpg resize: (1080, 1920) 1374575783 -0.5477146117695788 treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9.jpg resize: (1080, 1920) 1374575780 1.4165661023446243 treat image : temp/1753964429_2716454_1374576031_89177f85b024ad637d419cb38128129a_rle_crop_3899287615_0.png resize: (173, 165) 1374599622 -1.5954498722361719 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287619_0.png resize: (95, 140) 1374599623 -1.6030703306773655 treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287632_0.png resize: (118, 115) 1374599624 -1.7396240781183432 treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287630_0.png resize: (103, 170) 1374599625 -0.7726452250038188 treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9_rle_crop_3899287635_0.png resize: (180, 101) 1374599626 -2.1069261203477723 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287618_0.png resize: (101, 135) 1374599627 -1.5411504552652349 treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287631_0.png resize: (545, 381) 1374599628 -0.32587759923467796 treat image : temp/1753964429_2716454_1374575829_59538cd84d686b28fd5d9bb14ce6176c_rle_crop_3899287616_0.png resize: (166, 89) 1374599672 -0.3722870688307334 treat image : temp/1753964429_2716454_1374575821_027a0e39f6dd2cbc5bfbc51eac5a3565_rle_crop_3899287617_0.png resize: (505, 321) 1374599673 -0.3124083249688495 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287622_0.png resize: (171, 86) 1374599674 -1.2008925298858473 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287620_0.png resize: (60, 54) 1374599675 0.4485515942095917 treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287621_0.png resize: (555, 334) 1374599676 -0.017484957587848154 treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287624_0.png resize: (80, 207) 1374599677 -2.339711760316663 treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287623_0.png resize: (100, 83) 1374599678 -1.36288642769766 treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287625_0.png resize: (547, 355) 1374599680 -0.2444217654249716 treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287628_0.png resize: (984, 931) 1374599681 0.8408100450086452 treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287626_0.png resize: (111, 137) 1374599682 -1.1118725715086997 treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287627_0.png resize: (521, 369) 1374599684 0.20841117881232452 treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287629_0.png resize: (79, 94) 1374599685 -0.9622644819988428 treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287633_0.png resize: (124, 224) 1374599686 -0.5332152294064383 treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9_rle_crop_3899287634_0.png resize: (982, 1707) 1374599688 -0.5018002797678944 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 : 30 time used for this insertion : 0.014724493026733398 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 30 time used for this insertion : 0.016573667526245117 save missing photos in datou_result : time spend for datou_step_exec : 8.404860258102417 time spend to save output : 0.03656411170959473 total time spend for step 6 : 8.441424369812012 step7:brightness Thu Jul 31 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 ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness treat image : temp/1753964429_2716454_1374576031_89177f85b024ad637d419cb38128129a.jpg treat image : temp/1753964429_2716454_1374575847_e984dcb4c02e6806309c8086ff617a26.jpg treat image : temp/1753964429_2716454_1374575829_59538cd84d686b28fd5d9bb14ce6176c.jpg treat image : temp/1753964429_2716454_1374575821_027a0e39f6dd2cbc5bfbc51eac5a3565.jpg treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835.jpg treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb.jpg treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6.jpg treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db.jpg treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9.jpg treat image : temp/1753964429_2716454_1374576031_89177f85b024ad637d419cb38128129a_rle_crop_3899287615_0.png treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287619_0.png treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287632_0.png treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287630_0.png treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9_rle_crop_3899287635_0.png treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287618_0.png treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287631_0.png treat image : temp/1753964429_2716454_1374575829_59538cd84d686b28fd5d9bb14ce6176c_rle_crop_3899287616_0.png treat image : temp/1753964429_2716454_1374575821_027a0e39f6dd2cbc5bfbc51eac5a3565_rle_crop_3899287617_0.png treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287622_0.png treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287620_0.png treat image : temp/1753964429_2716454_1374575819_44c1bb028c0a00afc41a763cb0d00835_rle_crop_3899287621_0.png treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287624_0.png treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287623_0.png treat image : temp/1753964429_2716454_1374575817_453950a82cd6878106936c0157344ebb_rle_crop_3899287625_0.png treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287628_0.png treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287626_0.png treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287627_0.png treat image : temp/1753964429_2716454_1374575815_94ee90623857a3e3d0317ef224e837e6_rle_crop_3899287629_0.png treat image : temp/1753964429_2716454_1374575783_dc9f4c1dac27544d955a1698b03eb8db_rle_crop_3899287633_0.png treat image : temp/1753964429_2716454_1374575780_4333fe8b15bc7ae2e29fca063acd50e9_rle_crop_3899287634_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 : 30 time used for this insertion : 0.016129016876220703 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 30 time used for this insertion : 0.018355607986450195 save missing photos in datou_result : time spend for datou_step_exec : 2.3758087158203125 time spend to save output : 0.03916311264038086 total time spend for step 7 : 2.4149718284606934 step8:velours_tree Thu Jul 31 14:21:39 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 0.12608122825622559 time spend to save output : 3.314018249511719e-05 total time spend for step 8 : 0.1261143684387207 step9:send_mail_cod Thu Jul 31 14:21:39 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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_P25543266_31-07-2025_14_21_39.pdf 25544043 imagette255440431753964499 25544044 imagette255440441753964499 25544045 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette255440451753964499 25544047 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 .imagette255440471753964499 25544048 imagette255440481753964500 25544049 change filename to text .change filename to text .imagette255440491753964500 25544050 imagette255440501753964500 25544051 imagette255440511753964500 25544052 imagette255440521753964500 25544053 imagette255440531753964500 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=25543266 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/25544043,25544044,25544045,25544046,25544047,25544048,25544049,25544050,25544051,25544052,25544053?tags=background,mal_croppe,papier,environnement,pet_clair,pet_fonce,carton,metal,autre,pehd,flou args[1374576031] : ((1374576031, 0.6683890926405982, 492688767), (1374576031, 0.4875433834155355, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575847] : ((1374575847, -1.1361532353356012, 492688767), (1374575847, 0.48550348067528337, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575829] : ((1374575829, -2.052795897703317, 492609224), (1374575829, 1.0271638064583022, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575821] : ((1374575821, -4.209749648628418, 492609224), (1374575821, 0.34320688511103714, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575819] : ((1374575819, -1.1373563907342847, 492688767), (1374575819, 0.36852032033357357, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575817] : ((1374575817, -3.575745864859214, 492609224), (1374575817, 0.4817003831618305, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575815] : ((1374575815, 1.416083603655322, 492688767), (1374575815, 0.4719721066656649, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575783] : ((1374575783, -0.5477146117695788, 492688767), (1374575783, 0.2599478001364741, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com args[1374575780] : ((1374575780, 1.4165661023446243, 492688767), (1374575780, 0.16809118363665865, 2107752395), '0.15670513974622782') We are sending mail with results at report@fotonower.com refus_total : 0.15670513974622782 2022-04-13 10:29:59 0 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=25543266 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_P25543266_31-07-2025_14_21_39.pdf results_Auto_P25543266_31-07-2025_14_21_39.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543266_31-07-2025_14_21_39.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','25543266','results_Auto_P25543266_31-07-2025_14_21_39.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543266_31-07-2025_14_21_39.pdf','pdf','','0.36','0.15670513974622782') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/25543266

https://www.fotonower.com/image?json=false&list_photos_id=1374576031
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575847
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575829
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575821
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575819
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575817
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575815
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.416083603655322)
https://www.fotonower.com/image?json=false&list_photos_id=1374575783
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374575780
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.4165661023446243)

Dans ces conditions,le taux de refus est: 15.67%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/25544045?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/25544047?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/25544049?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543266_31-07-2025_14_21_39.pdf.

Lien vers velours :https://www.fotonower.com/velours/25544043,25544044,25544045,25544046,25544047,25544048,25544049,25544050,25544051,25544052,25544053?tags=background,mal_croppe,papier,environnement,pet_clair,pet_fonce,carton,metal,autre,pehd,flou.


L'équipe Fotonower 202 b'' Server: nginx Date: Thu, 31 Jul 2025 12:21:42 GMT Content-Length: 0 Connection: close X-Message-Id: ilZHOoDDR3OHN-dkZo075w 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 [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] 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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 9 time used for this insertion : 0.013265609741210938 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.1341309547424316 time spend to save output : 0.013462543487548828 total time spend for step 9 : 3.1475934982299805 step10:split_time_score Thu Jul 31 14:21:42 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'}] (('11', 9),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 31072025 25543266 Nombre de photos uploadées : 9 / 23040 (0%) 31072025 25543266 Nombre de photos taguées (types de déchets): 0 / 9 (0%) 31072025 25543266 Nombre de photos taguées (volume) : 0 / 9 (0%) elapsed_time : load_data_split_time_score 1.1920928955078125e-06 elapsed_time : order_list_meta_photo_and_scores 4.76837158203125e-06 ????????? elapsed_time : fill_and_build_computed_from_old_data 0.0005054473876953125 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.21033787727355957 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 : 0.1288892103909465 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25530216_31-07-2025_08_21_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25530216 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`=25530216 AND mptpi.`type`=3594 To do Qualite : 0.0400941679526749 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532093_31-07-2025_09_51_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532093 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`=25532093 AND mptpi.`type`=3594 To do Qualite : 0.017316454475308645 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532109_31-07-2025_09_41_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532109 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`=25532109 AND mptpi.`type`=3594 To do Qualite : 0.045261622299382735 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532112_31-07-2025_09_31_06.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532112 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`=25532112 AND mptpi.`type`=3594 To do Qualite : 0.10603395061728398 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25537191_31-07-2025_11_41_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25537191 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`=25537191 AND mptpi.`type`=3594 To do find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543232 order by id desc limit 1 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543235 order by id desc limit 1 Qualite : 0.15670513974622782 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543266_31-07-2025_14_21_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543266 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`=25543266 AND mptpi.`type`=3594 To do Qualite : 0.11439766589506177 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543287_31-07-2025_14_12_54.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543287 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`=25543287 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'31072025': {'nb_upload': 9, '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 [1374576031, 1374575847, 1374575829, 1374575821, 1374575819, 1374575817, 1374575815, 1374575783, 1374575780] Looping around the photos to save general results len do output : 1 /25543266Didn'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, '3410773') ('3318', '25543266', '1374576031', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575847', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575829', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575821', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575819', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575817', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575815', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575783', None, None, None, None, None, '3410773') ('3318', None, None, None, None, None, None, None, '3410773') ('3318', '25543266', '1374575780', None, None, None, None, None, '3410773') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.016200542449951172 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.687309980392456 time spend to save output : 0.016390323638916016 total time spend for step 10 : 2.703700304031372 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 9 set_done_treatment 40.53user 24.57system 1:20.29elapsed 81%CPU (0avgtext+0avgdata 2661332maxresident)k 20200inputs+22784outputs (17major+1351138minor)pagefaults 0swaps