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 : 1607593 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 : ['2741868'] with mtr_portfolio_ids : ['22249175'] and first list_photo_ids : [] new path : /proc/1607593/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! BFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.32831692695617676 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 Fri Apr 11 04:00:30 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 : 2944 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-04-11 04:00:33.420226: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-04-11 04:00:33.451083: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-11 04:00:33.452809: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4518000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-11 04:00:33.452843: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-11 04:00:33.456678: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-11 04:00:33.686539: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3a222d40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-11 04:00:33.686601: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-11 04:00:33.687471: 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 2025-04-11 04:00:33.687864: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-11 04:00:33.691029: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-11 04:00:33.693833: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-11 04:00:33.694227: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-11 04:00:33.697045: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-11 04:00:33.698419: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-11 04:00:33.703385: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-11 04:00:33.704471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-11 04:00:33.704561: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-11 04:00:33.705124: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-11 04:00:33.705140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-11 04:00:33.705150: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-11 04:00:33.706064: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2492 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. 2025-04-11 04:00:33.987378: 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 2025-04-11 04:00:33.987481: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-11 04:00:33.987504: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-11 04:00:33.987524: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-11 04:00:33.987543: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-11 04:00:33.987562: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-11 04:00:33.987581: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-11 04:00:33.987600: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-11 04:00:33.988449: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-11 04:00:33.989284: 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 2025-04-11 04:00:33.989313: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-11 04:00:33.989328: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-11 04:00:33.989342: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-11 04:00:33.989356: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-11 04:00:33.989370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-11 04:00:33.989384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-11 04:00:33.989398: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-11 04:00:33.990202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-11 04:00:33.990230: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-11 04:00:33.990239: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-11 04:00:33.990247: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-11 04:00:33.991109: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 2492 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 : [] 2025-04-11 04:00:43.308203: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-11 04:00:43.471061: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-11 04:00:44.669314: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.669363: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.675870: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.675906: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.725418: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.725460: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.768012: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.768051: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.09GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.819639: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.819677: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.15GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-11 04:00:44.821906: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.43G (1541275648 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:44.822431: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.29G (1387148032 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.145611: W tensorflow/core/common_runtime/bfc_allocator.cc:311] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature. 2025-04-11 04:00:45.201397: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.202105: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.203042: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.203668: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.214928: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.215581: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.216238: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.216906: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.217537: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.218250: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.235302: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.236431: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.284507: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.285194: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.293225: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.293860: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.310505: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.311307: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.312111: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.312908: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.317216: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.318104: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.318763: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.319388: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.320399: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.320416: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once. 2025-04-11 04:00:45.330731: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.331401: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.340401: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.341165: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.341929: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.342687: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.343492: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-11 04:00:45.344249: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 1.93G (2078146560 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 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 : 2 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 34 NEW PHOTO Processing 1 images image shape: (2160, 3264, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 3264.00000 nb d'objets trouves : 56 Detection mask done ! Trying to reset tf kernel 1611701 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1751 tf kernel not reseted sub process len(results) : 2 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 2 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 : 2944 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 : 0.0009748935699462891 nb_pixel_total : 24528 time to create 1 rle with old method : 0.030655860900878906 length of segment : 112 time for calcul the mask position with numpy : 0.0015635490417480469 nb_pixel_total : 53854 time to create 1 rle with old method : 0.060942649841308594 length of segment : 269 time for calcul the mask position with numpy : 0.0018732547760009766 nb_pixel_total : 89725 time to create 1 rle with old method : 0.09708905220031738 length of segment : 358 time for calcul the mask position with numpy : 0.0005764961242675781 nb_pixel_total : 30537 time to create 1 rle with old method : 0.03231620788574219 length of segment : 393 time for calcul the mask position with numpy : 0.0013043880462646484 nb_pixel_total : 70852 time to create 1 rle with old method : 0.07392120361328125 length of segment : 249 time for calcul the mask position with numpy : 0.001447439193725586 nb_pixel_total : 73821 time to create 1 rle with old method : 0.0808107852935791 length of segment : 395 time for calcul the mask position with numpy : 0.004903316497802734 nb_pixel_total : 220124 time to create 1 rle with new method : 0.01068568229675293 length of segment : 408 time for calcul the mask position with numpy : 0.0004417896270751953 nb_pixel_total : 18192 time to create 1 rle with old method : 0.02092719078063965 length of segment : 198 time for calcul the mask position with numpy : 0.021142959594726562 nb_pixel_total : 468230 time to create 1 rle with new method : 0.03660225868225098 length of segment : 1144 time for calcul the mask position with numpy : 0.0009260177612304688 nb_pixel_total : 52871 time to create 1 rle with old method : 0.05852913856506348 length of segment : 247 time for calcul the mask position with numpy : 0.0004379749298095703 nb_pixel_total : 21064 time to create 1 rle with old method : 0.024388790130615234 length of segment : 173 time for calcul the mask position with numpy : 0.0014123916625976562 nb_pixel_total : 100189 time to create 1 rle with old method : 0.1135861873626709 length of segment : 457 time for calcul the mask position with numpy : 0.00032448768615722656 nb_pixel_total : 12979 time to create 1 rle with old method : 0.014575481414794922 length of segment : 172 time for calcul the mask position with numpy : 0.013688802719116211 nb_pixel_total : 113814 time to create 1 rle with old method : 0.13309907913208008 length of segment : 697 time for calcul the mask position with numpy : 0.0013265609741210938 nb_pixel_total : 46785 time to create 1 rle with old method : 0.051665544509887695 length of segment : 406 time for calcul the mask position with numpy : 0.0010459423065185547 nb_pixel_total : 58280 time to create 1 rle with old method : 0.06427001953125 length of segment : 177 time for calcul the mask position with numpy : 0.0006580352783203125 nb_pixel_total : 35283 time to create 1 rle with old method : 0.039379119873046875 length of segment : 217 time for calcul the mask position with numpy : 0.00424504280090332 nb_pixel_total : 164610 time to create 1 rle with new method : 0.03227877616882324 length of segment : 425 time for calcul the mask position with numpy : 0.0014350414276123047 nb_pixel_total : 75401 time to create 1 rle with old method : 0.10359406471252441 length of segment : 389 time for calcul the mask position with numpy : 0.0009489059448242188 nb_pixel_total : 17608 time to create 1 rle with old method : 0.027273178100585938 length of segment : 121 time for calcul the mask position with numpy : 0.0005357265472412109 nb_pixel_total : 29409 time to create 1 rle with old method : 0.03783011436462402 length of segment : 185 time for calcul the mask position with numpy : 0.0025517940521240234 nb_pixel_total : 63822 time to create 1 rle with old method : 0.07215237617492676 length of segment : 305 time for calcul the mask position with numpy : 0.0012924671173095703 nb_pixel_total : 25952 time to create 1 rle with old method : 0.02942061424255371 length of segment : 219 time for calcul the mask position with numpy : 0.0013837814331054688 nb_pixel_total : 90108 time to create 1 rle with old method : 0.12497258186340332 length of segment : 397 time for calcul the mask position with numpy : 0.0018489360809326172 nb_pixel_total : 59888 time to create 1 rle with old method : 0.06673097610473633 length of segment : 350 time for calcul the mask position with numpy : 0.003870248794555664 nb_pixel_total : 80390 time to create 1 rle with old method : 0.08754730224609375 length of segment : 388 time for calcul the mask position with numpy : 0.001310110092163086 nb_pixel_total : 28575 time to create 1 rle with old method : 0.03301835060119629 length of segment : 184 time for calcul the mask position with numpy : 0.0008637905120849609 nb_pixel_total : 23608 time to create 1 rle with old method : 0.027072668075561523 length of segment : 166 time for calcul the mask position with numpy : 0.0011124610900878906 nb_pixel_total : 25981 time to create 1 rle with old method : 0.03116130828857422 length of segment : 123 time for calcul the mask position with numpy : 0.0011849403381347656 nb_pixel_total : 17384 time to create 1 rle with old method : 0.020090579986572266 length of segment : 167 time for calcul the mask position with numpy : 0.002538919448852539 nb_pixel_total : 150327 time to create 1 rle with new method : 0.007557392120361328 length of segment : 297 time for calcul the mask position with numpy : 0.0009224414825439453 nb_pixel_total : 15859 time to create 1 rle with old method : 0.01747441291809082 length of segment : 207 time for calcul the mask position with numpy : 0.002342700958251953 nb_pixel_total : 103885 time to create 1 rle with old method : 0.11723470687866211 length of segment : 387 time for calcul the mask position with numpy : 0.0008392333984375 nb_pixel_total : 15583 time to create 1 rle with old method : 0.017305612564086914 length of segment : 159 time for calcul the mask position with numpy : 0.0010833740234375 nb_pixel_total : 23255 time to create 1 rle with old method : 0.026549577713012695 length of segment : 208 time for calcul the mask position with numpy : 0.0011761188507080078 nb_pixel_total : 20509 time to create 1 rle with old method : 0.024672508239746094 length of segment : 167 time for calcul the mask position with numpy : 0.0018787384033203125 nb_pixel_total : 30368 time to create 1 rle with old method : 0.03472423553466797 length of segment : 210 time for calcul the mask position with numpy : 0.0022497177124023438 nb_pixel_total : 36044 time to create 1 rle with old method : 0.04070448875427246 length of segment : 342 time for calcul the mask position with numpy : 0.005677700042724609 nb_pixel_total : 126693 time to create 1 rle with old method : 0.14196538925170898 length of segment : 758 time for calcul the mask position with numpy : 0.0005326271057128906 nb_pixel_total : 12385 time to create 1 rle with old method : 0.013639688491821289 length of segment : 153 time for calcul the mask position with numpy : 0.0016512870788574219 nb_pixel_total : 33391 time to create 1 rle with old method : 0.03717541694641113 length of segment : 196 time for calcul the mask position with numpy : 0.0010526180267333984 nb_pixel_total : 17376 time to create 1 rle with old method : 0.022858142852783203 length of segment : 119 time for calcul the mask position with numpy : 0.0004191398620605469 nb_pixel_total : 9210 time to create 1 rle with old method : 0.01057744026184082 length of segment : 65 time for calcul the mask position with numpy : 0.001749277114868164 nb_pixel_total : 42662 time to create 1 rle with old method : 0.04833173751831055 length of segment : 803 time for calcul the mask position with numpy : 0.007761716842651367 nb_pixel_total : 140355 time to create 1 rle with old method : 0.15602564811706543 length of segment : 594 time for calcul the mask position with numpy : 0.0004010200500488281 nb_pixel_total : 12328 time to create 1 rle with old method : 0.01435089111328125 length of segment : 137 time for calcul the mask position with numpy : 0.0005817413330078125 nb_pixel_total : 16338 time to create 1 rle with old method : 0.01890087127685547 length of segment : 349 time spent for convertir_results : 5.079730272293091 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 100 chid ids of type : 3594 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 773 save missing photos in datou_result : time spend for datou_step_exec : 32.97830367088318 time spend to save output : 3.504495143890381 total time spend for step 1 : 36.48279881477356 step2:crop_condition Fri Apr 11 04:01:07 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 : 2 ! batch 1 Loaded 100 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 ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! 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 ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 82 About to insert : list_path_to_insert length 82 new photo from crops ! About to upload 82 photos upload in portfolio : 3736932 init cache_photo without model_param we have 82 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744336892_1607593 we have uploaded 82 photos in the portfolio 3736932 time of upload the photos Elapsed time : 34.39193391799927 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 ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 4 About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 3736932 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744336928_1607593 we have uploaded 4 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.548452615737915 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 ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! we have both polygon and rles Next one ! Next one ! map_result returned by crop_photo_return_map_crop : length : 12 About to insert : list_path_to_insert length 12 new photo from crops ! About to upload 12 photos upload in portfolio : 3736932 init cache_photo without model_param we have 12 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1744336933_1607593 we have uploaded 12 photos in the portfolio 3736932 time of upload the photos Elapsed time : 5.424508571624756 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 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1351122093, 1351122087] Looping around the photos to save general results len do output : 98 /1351437724Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437725Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437726Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437727Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437728Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437729Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437730Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437731Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437732Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437733Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437734Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437735Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437736Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437738Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437739Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437740Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437741Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437742Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437743Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437744Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437745Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437746Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437747Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437748Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437749Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437750Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437751Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437752Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437753Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437754Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437755Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437756Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437757Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437758Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437759Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437760Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437761Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437762Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437763Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437764Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437765Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437766Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437767Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437768Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437769Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437770Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437771Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437772Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437773Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437774Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437775Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437776Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437777Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437778Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437779Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437780Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437781Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437782Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437783Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437784Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437786Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437787Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437788Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437789Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437791Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437792Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437793Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437794Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437795Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437796Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437798Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437799Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437800Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437801Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437802Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437803Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437804Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437805Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437806Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437807Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437808Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437809Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437813Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437814Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437815Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437816Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437821Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437823Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437824Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437825Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437826Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437827Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437828Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437830Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437831Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437832Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437833Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1351437834Didn'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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 296 time used for this insertion : 0.026712417602539062 save_final save missing photos in datou_result : time spend for datou_step_exec : 71.25473237037659 time spend to save output : 0.02959918975830078 total time spend for step 2 : 71.28433156013489 step3:rle_unique_nms_with_priority Fri Apr 11 04:02:18 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 100 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 20 nb_hashtags : 3 time to prepare the origin masks : 7.683149099349976 time for calcul the mask position with numpy : 0.7845010757446289 nb_pixel_total : 5334639 time to create 1 rle with new method : 0.8169281482696533 time for calcul the mask position with numpy : 0.029958248138427734 nb_pixel_total : 220105 time to create 1 rle with new method : 0.4607706069946289 time for calcul the mask position with numpy : 0.027647733688354492 nb_pixel_total : 164531 time to create 1 rle with new method : 0.5592520236968994 time for calcul the mask position with numpy : 0.028763294219970703 nb_pixel_total : 46788 time to create 1 rle with old method : 0.05121970176696777 time for calcul the mask position with numpy : 0.02803349494934082 nb_pixel_total : 75458 time to create 1 rle with old method : 0.08397507667541504 time for calcul the mask position with numpy : 0.029303550720214844 nb_pixel_total : 100193 time to create 1 rle with old method : 0.11203122138977051 time for calcul the mask position with numpy : 0.029474735260009766 nb_pixel_total : 113384 time to create 1 rle with old method : 0.12851786613464355 time for calcul the mask position with numpy : 0.02889251708984375 nb_pixel_total : 21065 time to create 1 rle with old method : 0.02376103401184082 time for calcul the mask position with numpy : 0.028803110122680664 nb_pixel_total : 30607 time to create 1 rle with old method : 0.03452134132385254 time for calcul the mask position with numpy : 0.028900861740112305 nb_pixel_total : 53848 time to create 1 rle with old method : 0.060277462005615234 time for calcul the mask position with numpy : 0.029078245162963867 nb_pixel_total : 35283 time to create 1 rle with old method : 0.03935384750366211 time for calcul the mask position with numpy : 0.03241539001464844 nb_pixel_total : 467971 time to create 1 rle with new method : 0.3314230442047119 time for calcul the mask position with numpy : 0.028478145599365234 nb_pixel_total : 10 time to create 1 rle with old method : 3.838539123535156e-05 time for calcul the mask position with numpy : 0.029146432876586914 nb_pixel_total : 24528 time to create 1 rle with old method : 0.026408672332763672 time for calcul the mask position with numpy : 0.028412342071533203 nb_pixel_total : 73805 time to create 1 rle with old method : 0.0803835391998291 time for calcul the mask position with numpy : 0.027618885040283203 nb_pixel_total : 70851 time to create 1 rle with old method : 0.0748748779296875 time for calcul the mask position with numpy : 0.027657747268676758 nb_pixel_total : 18145 time to create 1 rle with old method : 0.018870115280151367 time for calcul the mask position with numpy : 0.027519941329956055 nb_pixel_total : 89698 time to create 1 rle with old method : 0.09877920150756836 time for calcul the mask position with numpy : 0.027776241302490234 nb_pixel_total : 52870 time to create 1 rle with old method : 0.05793571472167969 time for calcul the mask position with numpy : 0.0273897647857666 nb_pixel_total : 56461 time to create 1 rle with old method : 0.058976173400878906 create new chi : 4.593804836273193 time to delete rle : 0.03305315971374512 batch 1 Loaded 40 chid ids of type : 3594 ++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 1.6484184265136719 nb_obj : 31 nb_hashtags : 4 time to prepare the origin masks : 7.5665388107299805 time for calcul the mask position with numpy : 0.4270613193511963 nb_pixel_total : 5815962 time to create 1 rle with new method : 0.8746867179870605 time for calcul the mask position with numpy : 0.027979612350463867 nb_pixel_total : 25985 time to create 1 rle with old method : 0.0276029109954834 time for calcul the mask position with numpy : 0.028205394744873047 nb_pixel_total : 28574 time to create 1 rle with old method : 0.03073596954345703 time for calcul the mask position with numpy : 0.027987003326416016 nb_pixel_total : 17378 time to create 1 rle with old method : 0.019213438034057617 time for calcul the mask position with numpy : 0.028159379959106445 nb_pixel_total : 17608 time to create 1 rle with old method : 0.0193026065826416 time for calcul the mask position with numpy : 0.028144121170043945 nb_pixel_total : 23296 time to create 1 rle with old method : 0.02556586265563965 time for calcul the mask position with numpy : 0.02890610694885254 nb_pixel_total : 25954 time to create 1 rle with old method : 0.03186392784118652 time for calcul the mask position with numpy : 0.030373811721801758 nb_pixel_total : 15861 time to create 1 rle with old method : 0.01737523078918457 time for calcul the mask position with numpy : 0.029311180114746094 nb_pixel_total : 20514 time to create 1 rle with old method : 0.02342963218688965 time for calcul the mask position with numpy : 0.02861762046813965 nb_pixel_total : 35432 time to create 1 rle with old method : 0.04259753227233887 time for calcul the mask position with numpy : 0.03277754783630371 nb_pixel_total : 36008 time to create 1 rle with old method : 0.05017566680908203 time for calcul the mask position with numpy : 0.02884984016418457 nb_pixel_total : 33384 time to create 1 rle with old method : 0.03666257858276367 time for calcul the mask position with numpy : 0.02892923355102539 nb_pixel_total : 17384 time to create 1 rle with old method : 0.01915717124938965 time for calcul the mask position with numpy : 0.029096126556396484 nb_pixel_total : 30358 time to create 1 rle with old method : 0.03396272659301758 time for calcul the mask position with numpy : 0.029196500778198242 nb_pixel_total : 16310 time to create 1 rle with old method : 0.01834726333618164 time for calcul the mask position with numpy : 0.02989029884338379 nb_pixel_total : 12327 time to create 1 rle with old method : 0.01395869255065918 time for calcul the mask position with numpy : 0.03480029106140137 nb_pixel_total : 140389 time to create 1 rle with old method : 0.16037416458129883 time for calcul the mask position with numpy : 0.032999515533447266 nb_pixel_total : 15582 time to create 1 rle with old method : 0.025398731231689453 time for calcul the mask position with numpy : 0.031203031539916992 nb_pixel_total : 12386 time to create 1 rle with old method : 0.013880252838134766 time for calcul the mask position with numpy : 0.029140949249267578 nb_pixel_total : 63821 time to create 1 rle with old method : 0.07296037673950195 time for calcul the mask position with numpy : 0.02880120277404785 nb_pixel_total : 112996 time to create 1 rle with old method : 0.1230459213256836 time for calcul the mask position with numpy : 0.02924656867980957 nb_pixel_total : 2234 time to create 1 rle with old method : 0.0026950836181640625 time for calcul the mask position with numpy : 0.03829240798950195 nb_pixel_total : 72029 time to create 1 rle with old method : 0.08008575439453125 time for calcul the mask position with numpy : 0.02879476547241211 nb_pixel_total : 23614 time to create 1 rle with old method : 0.026573896408081055 time for calcul the mask position with numpy : 0.02929210662841797 nb_pixel_total : 103878 time to create 1 rle with old method : 0.1280534267425537 time for calcul the mask position with numpy : 0.03330874443054199 nb_pixel_total : 59885 time to create 1 rle with old method : 0.07037615776062012 time for calcul the mask position with numpy : 0.03049945831298828 nb_pixel_total : 29410 time to create 1 rle with old method : 0.032247066497802734 time for calcul the mask position with numpy : 0.028311729431152344 nb_pixel_total : 123 time to create 1 rle with old method : 0.0003898143768310547 time for calcul the mask position with numpy : 0.02970433235168457 nb_pixel_total : 89964 time to create 1 rle with old method : 0.09916353225708008 time for calcul the mask position with numpy : 0.02929067611694336 nb_pixel_total : 150313 time to create 1 rle with new method : 0.670320987701416 time for calcul the mask position with numpy : 0.028956890106201172 nb_pixel_total : 1281 time to create 1 rle with old method : 0.0015439987182617188 create new chi : 4.2042200565338135 time to delete rle : 0.002543210983276367 batch 1 Loaded 62 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 720 TO DO : save crop sub photo not yet done ! save time : 1.2708661556243896 map_output_result : {1351122093: (0.0, 'Should be the crop_list due to order', 0), 1351122087: (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 [1351122093, 1351122087] Looping around the photos to save general results len do output : 2 /1351122093.Didn't retrieve data . /1351122087.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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.01188206672668457 save_final save missing photos in datou_result : time spend for datou_step_exec : 28.15698003768921 time spend to save output : 0.012068510055541992 total time spend for step 3 : 28.16904854774475 step4:ventilate_hashtags_in_portfolio Fri Apr 11 04:02:46 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 : 22249175 get user id for portfolio 22249175 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`=22249175 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','environnement','pehd','autre','papier','flou','carton','mal_croppe','metal','background','pet_clair')) AND mptpi.`min_score`=0.5 To do To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22249175 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_fonce','environnement','pehd','autre','papier','flou','carton','mal_croppe','metal','background','pet_clair')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/22249771,22249772,22249773,22249774,22249775,22249776,22249777,22249778,22249779,22249780,22249781?tags=flou,background,pehd,papier,pet_fonce,pet_clair,metal,mal_croppe,environnement,carton,autre Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1351122093, 1351122087] Looping around the photos to save general results len do output : 1 /22249175. 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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.014404296875 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.4759609699249268 time spend to save output : 0.014637470245361328 total time spend for step 4 : 1.490598440170288 step5:final Fri Apr 11 04:02:48 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 : {1351122093: ('0.20352036647992527',), 1351122087: ('0.20352036647992527',)} new output for save of step final : {1351122093: ('0.20352036647992527',), 1351122087: ('0.20352036647992527',)} [1351122093, 1351122087] Looping around the photos to save general results len do output : 2 /1351122093.Didn't retrieve data . /1351122087.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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.019596099853515625 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.1376323699951172 time spend to save output : 0.019798994064331055 total time spend for step 5 : 0.15743136405944824 step6:blur_detection Fri Apr 11 04:02:48 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/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b.jpg resize: (2160, 3264) 1351122093 -2.35070218739862 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1.jpg resize: (2160, 3264) 1351122087 -2.975430827231215 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451354_0.png resize: (1094, 619) 1351437724 -1.5572612319425287 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459105_0.png resize: (1094, 619) 1351437725 -1.5578920062443125 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451356_0.png resize: (169, 225) 1351437726 -1.8420130810895199 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459103_0.png resize: (169, 225) 1351437727 -1.8420130810895199 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451359_0.png resize: (172, 160) 1351437728 -1.6937285565481666 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451358_0.png resize: (457, 286) 1351437729 -0.5689864442030769 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459101_0.png resize: (457, 286) 1351437730 -0.5689864442030769 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451348_0.png resize: (357, 478) 1351437731 -1.9931791958208736 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459100_0.png resize: (13, 3) 1351437732 nan treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459111_0.png resize: (357, 478) 1351437733 -1.9931791958208736 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451351_0.png resize: (354, 315) 1351437734 -2.0426505122869276 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459108_0.png resize: (354, 315) 1351437735 -2.0426505122869276 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451352_0.png resize: (402, 737) 1351437736 -2.6136095083191972 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459107_0.png resize: (402, 737) 1351437738 -2.6136095083191972 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3755859252_0.png resize: (165, 509) 1351437739 -1.1828229201424059 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459102_0.png resize: (162, 488) 1351437740 -1.1369109938621944 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451357_0.png resize: (162, 488) 1351437741 -1.1369109938621944 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451353_0.png resize: (198, 193) 1351437742 -1.617893399427721 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459106_0.png resize: (198, 191) 1351437743 -1.5788244124792774 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451349_0.png resize: (217, 248) 1351437744 -2.8980796002607114 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459110_0.png resize: (217, 248) 1351437745 -2.8980796002607114 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451360_0.png resize: (1075, 1084) 1351437746 -0.26486961941379533 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451355_0.png resize: (247, 312) 1351437747 -0.8117380279376065 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459104_0.png resize: (247, 312) 1351437748 -0.8117380279376065 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451362_0.png resize: (214, 283) 1351437749 -0.4752707040840251 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459097_0.png resize: (214, 283) 1351437750 -0.4752707040840251 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459099_0.png resize: (1075, 1084) 1351437751 -0.27235458600626944 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451361_0.png resize: (273, 357) 1351437752 -3.057503897606541 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451363_0.png resize: (330, 923) 1351437753 -0.4331580060440383 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459096_0.png resize: (330, 923) 1351437754 -0.4331580060440383 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459098_0.png resize: (273, 357) 1351437755 -3.057503897606541 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451347_0.png resize: (252, 386) 1351437756 -2.4237360638714476 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451346_0.png resize: (111, 311) 1351437757 -1.5848521343513038 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459113_0.png resize: (111, 311) 1351437758 -1.5848521343513038 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459112_0.png resize: (252, 386) 1351437759 -2.4237360638714476 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451373_0.png resize: (166, 189) 1351437760 -1.9049523450078425 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460572_0.png resize: (166, 189) 1351437761 -1.9049523450078425 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451367_0.png resize: (282, 292) 1351437762 -1.079863289938167 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460569_0.png resize: (282, 292) 1351437763 -1.079863289938167 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451365_0.png resize: (119, 211) 1351437764 -1.3948611383962275 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460554_0.png resize: (119, 211) 1351437765 -1.3948611383962275 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451384_0.png resize: (582, 622) 1351437766 -1.8908307974441945 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460570_0.png resize: (582, 612) 1351437767 -1.9085343317264885 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451375_0.png resize: (165, 197) 1351437768 -1.9607225161845314 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460562_0.png resize: (165, 197) 1351437769 -1.9607225161845314 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451371_0.png resize: (368, 358) 1351437770 -1.3065131509276742 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3755859253_0.png resize: (381, 348) 1351437771 -1.3845879228797475 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3755859254_0.png resize: (195, 155) 1351437772 -0.9540620765301733 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451380_0.png resize: (194, 156) 1351437773 -0.9956031501666031 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460555_0.png resize: (194, 156) 1351437774 -0.9956031501666031 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460571_0.png resize: (368, 358) 1351437775 -1.3065131509276742 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451370_0.png resize: (287, 495) 1351437776 -2.2875998105021425 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460574_0.png resize: (287, 495) 1351437777 -2.2875998105021425 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451386_0.png resize: (175, 268) 1351437778 -1.9977375170191491 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460561_0.png resize: (175, 268) 1351437779 -1.9977375170191491 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451387_0.png resize: (116, 228) 1351437780 -1.1833141971294565 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460553_0.png resize: (116, 228) 1351437781 -1.1833141971294565 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451377_0.png resize: (207, 97) 1351437782 -0.37844104479793284 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460557_0.png resize: (207, 97) 1351437783 -0.37844104479793284 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451385_0.png resize: (152, 88) 1351437784 8.40056584924693 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460568_0.png resize: (152, 88) 1351437786 8.40056584924693 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451379_0.png resize: (157, 131) 1351437787 0.4708697111269787 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460567_0.png resize: (157, 131) 1351437788 0.4708697111269787 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451390_0.png resize: (452, 607) 1351437789 -1.5500877248416187 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451372_0.png resize: (182, 188) 1351437791 2.1216735619702223 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460552_0.png resize: (182, 188) 1351437792 2.1216735619702223 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460566_0.png resize: (452, 607) 1351437793 -1.5500877248416187 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451392_0.png resize: (266, 118) 1351437794 -1.681765654265147 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460564_0.png resize: (266, 118) 1351437795 -1.702374816254786 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451376_0.png resize: (290, 733) 1351437796 -2.6514366437576657 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460577_0.png resize: (290, 733) 1351437798 -2.6514366437576657 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451366_0.png resize: (176, 235) 1351437799 -1.1923157102302049 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460575_0.png resize: (176, 235) 1351437800 -1.1923157102302049 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451383_0.png resize: (274, 270) 1351437801 -1.7474414798299458 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460560_0.png resize: (274, 270) 1351437802 -1.7474414798299458 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460565_0.png resize: (127, 151) 1351437803 -1.3992956266210155 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451391_0.png resize: (127, 151) 1351437804 -1.3992956266210155 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451388_0.png resize: (65, 178) 1351437805 -0.2625907983329238 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460578_0.png resize: (10, 176) 1351437806 nan treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451369_0.png resize: (396, 256) 1351437807 0.4981176620415409 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3755707325_0.png resize: (396, 256) 1351437808 0.5125618551599096 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460576_0.png resize: (396, 256) 1351437809 0.4981176620415409 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451368_0.png resize: (208, 168) 1351437813 -1.7714441658481497 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460556_0.png resize: (208, 168) 1351437814 -1.7714441658481497 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451389_0.png resize: (290, 270) 1351437815 -2.9375359316634166 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460559_0.png resize: (283, 267) 1351437816 -2.5381593717877093 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451364_0.png resize: (342, 277) 1351437821 -2.3893531338422234 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459095_0.png resize: (342, 277) 1351437823 -2.422285974152741 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754451350_0.png resize: (248, 374) 1351437824 -3.3125098953447516 treat image : temp/1744336830_1607593_1351122093_0a99529b2b085c6ab82eb790a1871c2b_rle_crop_3754459109_0.png resize: (248, 374) 1351437825 -3.3125098953447516 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451374_0.png resize: (111, 277) 1351437826 0.28413502594679185 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460551_0.png resize: (111, 277) 1351437827 0.28413502594679185 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451378_0.png resize: (384, 588) 1351437828 -1.5397828258955821 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460573_0.png resize: (384, 588) 1351437830 -1.5397828258955821 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451381_0.png resize: (142, 193) 1351437831 -2.133157890895851 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460558_0.png resize: (142, 193) 1351437832 -2.133157890895851 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754451382_0.png resize: (210, 211) 1351437833 -1.0733653328227473 treat image : temp/1744336830_1607593_1351122087_722b1817bb0fef004ba2a477107c6ee1_rle_crop_3754460563_0.png resize: (210, 211) 1351437834 -1.0733653328227473 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 : 100 Catched exception ! Connect or reconnect ! In save_photo_hashtag_id_thcl_score : (1205, 'Lock wait timeout exceeded; try restarting transaction') [('1533', '1351122093', '492609224', '-2.35070218739862'), ('1533', '1351122087', '492609224', '-2.975430827231215'), ('1533', '1351437724', '492688767', '-1.5572612319425287'), ('1533', '1351437725', '492688767', '-1.5578920062443125'), ('1533', '1351437726', '492688767', '-1.8420130810895199'), ('1533', '1351437727', '492688767', '-1.8420130810895199'), ('1533', '1351437728', '492688767', '-1.6937285565481666'), ('1533', '1351437729', '492688767', '-0.5689864442030769'), ('1533', '1351437730', '492688767', '-0.5689864442030769'), ('1533', '1351437731', '492688767', '-1.9931791958208736'), ('1533', '1351437732', '2107751945', 'nan'), ('1533', '1351437733', '492688767', '-1.9931791958208736'), ('1533', '1351437734', '492609224', '-2.0426505122869276'), ('1533', '1351437735', '492609224', '-2.0426505122869276'), ('1533', '1351437736', '492609224', '-2.6136095083191972'), ('1533', '1351437738', '492609224', '-2.6136095083191972'), ('1533', '1351437739', '492688767', '-1.1828229201424059'), ('1533', '1351437740', '492688767', '-1.1369109938621944'), ('1533', '1351437741', '492688767', '-1.1369109938621944'), ('1533', '1351437742', '492688767', '-1.617893399427721'), ('1533', '1351437743', '492688767', '-1.5788244124792774'), ('1533', '1351437744', '492609224', '-2.8980796002607114'), ('1533', '1351437745', '492609224', '-2.8980796002607114'), ('1533', '1351437746', '492688767', '-0.26486961941379533'), ('1533', '1351437747', '492688767', '-0.8117380279376065'), ('1533', '1351437748', '492688767', '-0.8117380279376065'), ('1533', '1351437749', '492688767', '-0.4752707040840251'), ('1533', '1351437750', '492688767', '-0.4752707040840251'), ('1533', '1351437751', '492688767', '-0.27235458600626944'), ('1533', '1351437752', '492609224', '-3.057503897606541'), ('1533', '1351437753', '492688767', '-0.4331580060440383'), ('1533', '1351437754', '492688767', '-0.4331580060440383'), ('1533', '1351437755', '492609224', '-3.057503897606541'), ('1533', '1351437756', '492609224', '-2.4237360638714476'), ('1533', '1351437757', '492688767', '-1.5848521343513038'), ('1533', '1351437758', '492688767', '-1.5848521343513038'), ('1533', '1351437759', '492609224', '-2.4237360638714476'), ('1533', '1351437760', '492688767', '-1.9049523450078425'), ('1533', '1351437761', '492688767', '-1.9049523450078425'), ('1533', '1351437762', '492688767', '-1.079863289938167'), ('1533', '1351437763', '492688767', '-1.079863289938167'), ('1533', '1351437764', '492688767', '-1.3948611383962275'), ('1533', '1351437765', '492688767', '-1.3948611383962275'), ('1533', '1351437766', '492688767', '-1.8908307974441945'), ('1533', '1351437767', '492688767', '-1.9085343317264885'), ('1533', '1351437768', '492688767', '-1.9607225161845314'), ('1533', '1351437769', '492688767', '-1.9607225161845314'), ('1533', '1351437770', '492688767', '-1.3065131509276742'), ('1533', '1351437771', '492688767', '-1.3845879228797475'), ('1533', '1351437772', '492688767', '-0.9540620765301733'), ('1533', '1351437773', '492688767', '-0.9956031501666031'), ('1533', '1351437774', '492688767', '-0.9956031501666031'), ('1533', '1351437775', '492688767', '-1.3065131509276742'), ('1533', '1351437776', '492609224', '-2.2875998105021425'), ('1533', '1351437777', '492609224', '-2.2875998105021425'), ('1533', '1351437778', '492688767', '-1.9977375170191491'), ('1533', '1351437779', '492688767', '-1.9977375170191491'), ('1533', '1351437780', '492688767', '-1.1833141971294565'), ('1533', '1351437781', '492688767', '-1.1833141971294565'), ('1533', '1351437782', '492688767', '-0.37844104479793284'), ('1533', '1351437783', '492688767', '-0.37844104479793284'), ('1533', '1351437784', '492688767', '8.40056584924693'), ('1533', '1351437786', '492688767', '8.40056584924693'), ('1533', '1351437787', '492688767', '0.4708697111269787'), ('1533', '1351437788', '492688767', '0.4708697111269787'), ('1533', '1351437789', '492688767', '-1.5500877248416187'), ('1533', '1351437791', '492688767', '2.1216735619702223'), ('1533', '1351437792', '492688767', '2.1216735619702223'), ('1533', '1351437793', '492688767', '-1.5500877248416187'), ('1533', '1351437794', '492688767', '-1.681765654265147'), ('1533', '1351437795', '492688767', '-1.702374816254786'), ('1533', '1351437796', '492609224', '-2.6514366437576657'), ('1533', '1351437798', '492609224', '-2.6514366437576657'), ('1533', '1351437799', '492688767', '-1.1923157102302049'), ('1533', '1351437800', '492688767', '-1.1923157102302049'), ('1533', '1351437801', '492688767', '-1.7474414798299458'), ('1533', '1351437802', '492688767', '-1.7474414798299458'), ('1533', '1351437803', '492688767', '-1.3992956266210155'), ('1533', '1351437804', '492688767', '-1.3992956266210155'), ('1533', '1351437805', '492688767', '-0.2625907983329238'), ('1533', '1351437806', '2107751945', 'nan'), ('1533', '1351437807', '492688767', '0.4981176620415409'), ('1533', '1351437808', '492688767', '0.5125618551599096'), ('1533', '1351437809', '492688767', '0.4981176620415409'), ('1533', '1351437813', '492688767', '-1.7714441658481497'), ('1533', '1351437814', '492688767', '-1.7714441658481497'), ('1533', '1351437815', '492609224', '-2.9375359316634166'), ('1533', '1351437816', '492609224', '-2.5381593717877093'), ('1533', '1351437821', '492609224', '-2.3893531338422234'), ('1533', '1351437823', '492609224', '-2.422285974152741'), ('1533', '1351437824', '492609224', '-3.3125098953447516'), ('1533', '1351437825', '492609224', '-3.3125098953447516'), ('1533', '1351437826', '492688767', '0.28413502594679185'), ('1533', '1351437827', '492688767', '0.28413502594679185'), ('1533', '1351437828', '492688767', '-1.5397828258955821'), ('1533', '1351437830', '492688767', '-1.5397828258955821'), ('1533', '1351437831', '492609224', '-2.133157890895851'), ('1533', '1351437832', '492609224', '-2.133157890895851'), ('1533', '1351437833', '492688767', '-1.0733653328227473'), ('1533', '1351437834', '492688767', '-1.0733653328227473')] time used for this insertion : 51.748939037323 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 100 time used for this insertion : 0.12458205223083496 save missing photos in datou_result : time spend for datou_step_exec : 10.68959927558899 time spend to save output : 51.878671407699585 total time spend for step 6 : 62.568270683288574 step7:brightness Fri Apr 11 04:03:50 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 toutes les photos sont déjà traitées, on saute les calculs 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 : 2 time used for this insertion : 0.007888555526733398 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 2 time used for this insertion : 0.009006261825561523 save missing photos in datou_result : time spend for datou_step_exec : 0.12454771995544434 time spend to save output : 0.020795345306396484 total time spend for step 7 : 0.14534306526184082 step8:velours_tree Fri Apr 11 04:03:51 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 : 0.14825677871704102 time spend to save output : 4.4345855712890625e-05 total time spend for step 8 : 0.1483011245727539 step9:send_mail_cod Fri Apr 11 04:03:51 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 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 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_P22249175_11-04-2025_04_03_51.pdf 22249771 imagette222497711744337031 22249772 imagette222497721744337031 22249773 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 .imagette222497731744337031 22249774 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497741744337031 22249775 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497751744337034 22249776 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497761744337035 22249777 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497771744337044 22249778 imagette222497781744337046 22249780 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497801744337046 22249781 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette222497811744337057 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=22249175 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/22249771,22249772,22249773,22249774,22249775,22249776,22249777,22249778,22249779,22249780,22249781?tags=flou,background,pehd,papier,pet_fonce,pet_clair,metal,mal_croppe,environnement,carton,autre args[1351122093] : ((1351122093, -2.35070218739862, 492609224), (1351122093, -0.07437381891627563, 496442774), '0.20352036647992527') no score found for photo 1351122093 We are sending mail with results at report@fotonower.com args[1351122087] : ((1351122087, -2.975430827231215, 492609224), (1351122087, 0.11705114912039918, 2107752395), '0.20352036647992527') no score found for photo 1351122087 We are sending mail with results at report@fotonower.com refus_total : 0.20352036647992527 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=22249175 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1351400204,1351122524,1351400583,1351400529,1351400413,1351122110,1351400396,1351400390,1351122693,1351122574,1351123534,1351122492,1351401891,1351122104,1351122138,1351400682,1351400542,1351400737,1351400151,1351400162) Found this number of photos: 20 begin to download photo : 1351400204 begin to download photo : 1351122110 begin to download photo : 1351123534 begin to download photo : 1351400682 download finish for photo 1351122110 begin to download photo : 1351400396 download finish for photo 1351400204 begin to download photo : 1351122524 download finish for photo 1351400682 begin to download photo : 1351400542 download finish for photo 1351123534 begin to download photo : 1351122492 download finish for photo 1351400542 begin to download photo : 1351400737 download finish for photo 1351122524 begin to download photo : 1351400583 download finish for photo 1351400396 begin to download photo : 1351400390 download finish for photo 1351122492 begin to download photo : 1351401891 download finish for photo 1351400583 begin to download photo : 1351400529 download finish for photo 1351400737 begin to download photo : 1351400151 download finish for photo 1351400390 begin to download photo : 1351122693 download finish for photo 1351401891 begin to download photo : 1351122104 download finish for photo 1351400529 begin to download photo : 1351400413 download finish for photo 1351400151 begin to download photo : 1351400162 download finish for photo 1351122693 begin to download photo : 1351122574 download finish for photo 1351122104 begin to download photo : 1351122138 download finish for photo 1351400413 download finish for photo 1351400162 download finish for photo 1351122138 download finish for photo 1351122574 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249175_11-04-2025_04_03_51.pdf results_Auto_P22249175_11-04-2025_04_03_51.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249175_11-04-2025_04_03_51.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','22249175','results_Auto_P22249175_11-04-2025_04_03_51.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249175_11-04-2025_04_03_51.pdf','pdf','','1.3','0.20352036647992527') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/22249175


Dans ces conditions,le taux de refus est: 20.35%
Veuillez trouver les photos des contaminants.

exemples de contaminants: pehd: https://www.fotonower.com/view/22249773?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/22249774?limit=200
exemples de contaminants: pet_fonce: https://www.fotonower.com/view/22249775?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/22249776?limit=200
exemples de contaminants: metal: https://www.fotonower.com/view/22249777?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/22249780?limit=200
exemples de contaminants: autre: https://www.fotonower.com/view/22249781?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249175_11-04-2025_04_03_51.pdf.

Lien vers velours :https://www.fotonower.com/velours/22249771,22249772,22249773,22249774,22249775,22249776,22249777,22249778,22249779,22249780,22249781?tags=flou,background,pehd,papier,pet_fonce,pet_clair,metal,mal_croppe,environnement,carton,autre.


L'équipe Fotonower 202 b'' Server: nginx Date: Fri, 11 Apr 2025 02:04:23 GMT Content-Length: 0 Connection: close X-Message-Id: E7IgaDKWT1WzGHy2FzCQWQ 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 [1351122093, 1351122087] 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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2 time used for this insertion : 0.019460201263427734 save_final save missing photos in datou_result : time spend for datou_step_exec : 32.58191967010498 time spend to save output : 0.019684553146362305 total time spend for step 9 : 32.60160422325134 step10:split_time_score Fri Apr 11 04:04:23 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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', 42),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 10042025 22249175 Nombre de photos uploadées : 42 / 23040 (0%) 10042025 22249175 Nombre de photos taguées (types de déchets): 0 / 42 (0%) 10042025 22249175 Nombre de photos taguées (volume) : 0 / 42 (0%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 5.245208740234375e-06 ?????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.002082347869873047 elapsed_time : insert_dashboard_record_day_entry 0.034534454345703125 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 : 0.08146285908317973 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22246522_11-04-2025_00_21_32.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22246522 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22246522 AND mptpi.`type`=3726 To do Qualite : 0.21114670295401056 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22248171_11-04-2025_03_37_53.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22248171 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`=22248171 AND mptpi.`type`=3594 To do Qualite : 0.16253812894054934 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249162_11-04-2025_03_42_19.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22249162 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`=22249162 AND mptpi.`type`=3594 To do Qualite : 0.17797032441448804 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249164_11-04-2025_03_29_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22249164 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`=22249164 AND mptpi.`type`=3594 To do Qualite : 0.254227649344227 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249166_11-04-2025_03_20_42.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22249166 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22249166 AND mptpi.`type`=3726 To do Qualite : 0.08601623137107692 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249170_11-04-2025_03_15_49.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22249170 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22249170 AND mptpi.`type`=3726 To do Qualite : 0.20352036647992527 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22249175_11-04-2025_04_03_51.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22249175 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`=22249175 AND mptpi.`type`=3594 To do Qualite : 0.06472482777268794 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22234331_10-04-2025_17_50_57.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22234331 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22234331 AND mptpi.`type`=3726 To do Qualite : 0.19717008215323167 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22248175_11-04-2025_02_51_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22248175 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`=22248175 AND mptpi.`type`=3594 To do Qualite : 0.15969232753695164 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22248176_11-04-2025_02_46_21.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22248176 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`=22248176 AND mptpi.`type`=3594 To do Qualite : 0.13695543617250847 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22237479_10-04-2025_19_32_24.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22237479 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22237479 AND mptpi.`type`=3726 To do Qualite : 0.17599803127269442 find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22248183 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`=22248183 AND mptpi.`type`=3594 To do Qualite : 0.1860674246550472 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22248184_11-04-2025_02_24_31.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22248184 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`=22248184 AND mptpi.`type`=3594 To do Qualite : 0.06080137778204751 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22246525_11-04-2025_00_35_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22246525 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 ! 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 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : 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 ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 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`=22246525 AND mptpi.`type`=3726 To do Qualite : 0.18220796130952377 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22246530_11-04-2025_01_04_15.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22246530 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`=22246530 AND mptpi.`type`=3594 To do Qualite : 0.2303195134000895 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22243654_10-04-2025_22_48_38.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22243654 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`=22243654 AND mptpi.`type`=3594 To do Qualite : 0.17880971427923026 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P22243656_10-04-2025_22_30_13.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 22243656 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`=22243656 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'10042025': {'nb_upload': 42, '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 [1351122093, 1351122087] Looping around the photos to save general results len do output : 1 /22249175Didn'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, '2741868') ('3318', None, '1351122093', None, None, None, None, None, '2741868') ('3318', None, None, None, None, None, None, None, '2741868') ('3318', None, '1351122087', None, None, None, None, None, '2741868') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 1.455939769744873 save_final save missing photos in datou_result : time spend for datou_step_exec : 2.06939959526062 time spend to save output : 1.4561777114868164 total time spend for step 10 : 3.5255773067474365 caffe_path_current : /home/admin/workarea/git/Velours/python/mtr/datou/detect_blur_image.py:82: RuntimeWarning: Degrees of freedom <= 0 for slice variance = laplacian[10:(x-10),10:(y-10)].var() /home/admin/.local/lib/python3.8/site-packages/numpy/core/_methods.py:222: RuntimeWarning: invalid value encountered in true_divide arrmean = um.true_divide(arrmean, div, out=arrmean, casting='unsafe', /home/admin/.local/lib/python3.8/site-packages/numpy/core/_methods.py:254: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 2 set_done_treatment 79.01user 28.19system 4:01.48elapsed 44%CPU (0avgtext+0avgdata 3779944maxresident)k 500816inputs+137040outputs (12major+4887621minor)pagefaults 0swaps