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 : 3189108 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 : ['3652102'] with mtr_portfolio_ids : ['26440559'] and first list_photo_ids : [] new path : /proc/3189108/ 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 , BFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 11 ; length of list_pids : 11 ; length of list_args : 11 time to download the photos : 1.449876070022583 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Tue Sep 2 14:40:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 10600 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-09-02 14:40:32.784233: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-09-02 14:40:32.812616: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-09-02 14:40:32.814470: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4b90000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-09-02 14:40:32.814522: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-09-02 14:40:32.817870: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-09-02 14:40:32.987096: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3b5e6f30 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-09-02 14:40:32.987151: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-09-02 14:40:32.988641: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-02 14:40:32.989304: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-02 14:40:32.992807: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-02 14:40:32.995883: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-02 14:40:32.996485: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-02 14:40:32.999662: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-02 14:40:33.000740: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-02 14:40:33.005145: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-02 14:40:33.006682: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-02 14:40:33.006769: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-02 14:40:33.007539: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-02 14:40:33.007555: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-02 14:40:33.007564: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-02 14:40:33.008932: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9819 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-09-02 14:40:33.312789: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-02 14:40:33.312906: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-02 14:40:33.312928: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-02 14:40:33.312947: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-02 14:40:33.312965: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-02 14:40:33.312982: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-02 14:40:33.313000: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-02 14:40:33.313018: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-02 14:40:33.314687: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-02 14:40:33.316120: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-09-02 14:40:33.316156: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-09-02 14:40:33.316175: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-02 14:40:33.316192: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-09-02 14:40:33.316208: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-09-02 14:40:33.316225: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-09-02 14:40:33.316241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-09-02 14:40:33.316258: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-09-02 14:40:33.317836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-09-02 14:40:33.317875: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-09-02 14:40:33.317886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-09-02 14:40:33.317896: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-09-02 14:40:33.319491: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9819 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-09-02 14:40:41.004175: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-09-02 14:40:41.252909: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23 /data/models_weight/learn_RUBBIA_REFUS_AMIENS_23/mask_model.h5 size_local : 256009536 size in s3 : 256009536 create time local : 2021-08-09 09:43:22 create time in s3 : 2021-08-06 18:54:04 mask_model.h5 already exist and didn't need to update list_images length : 11 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 27.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 37.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 7 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 39.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 9 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 28.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 25.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 4 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 30.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 1 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 29.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 25.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 16.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 Detection mask done ! Trying to reset tf kernel 3189617 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1064 tf kernel not reseted sub process len(results) : 11 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 11 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 : 6021 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 : 0.0004248619079589844 nb_pixel_total : 15460 time to create 1 rle with old method : 0.017727136611938477 length of segment : 126 time for calcul the mask position with numpy : 0.0008602142333984375 nb_pixel_total : 56753 time to create 1 rle with old method : 0.06372618675231934 length of segment : 255 time for calcul the mask position with numpy : 0.0003535747528076172 nb_pixel_total : 22054 time to create 1 rle with old method : 0.024560928344726562 length of segment : 240 time for calcul the mask position with numpy : 0.000499725341796875 nb_pixel_total : 25417 time to create 1 rle with old method : 0.028441667556762695 length of segment : 220 time for calcul the mask position with numpy : 0.0001316070556640625 nb_pixel_total : 3793 time to create 1 rle with old method : 0.004446506500244141 length of segment : 155 time for calcul the mask position with numpy : 8.58306884765625e-05 nb_pixel_total : 3442 time to create 1 rle with old method : 0.003886699676513672 length of segment : 69 time for calcul the mask position with numpy : 0.00021505355834960938 nb_pixel_total : 12043 time to create 1 rle with old method : 0.014139175415039062 length of segment : 129 time for calcul the mask position with numpy : 0.0017116069793701172 nb_pixel_total : 101843 time to create 1 rle with old method : 0.1136465072631836 length of segment : 475 time for calcul the mask position with numpy : 0.0001659393310546875 nb_pixel_total : 8132 time to create 1 rle with old method : 0.009253263473510742 length of segment : 112 time for calcul the mask position with numpy : 0.00014519691467285156 nb_pixel_total : 7061 time to create 1 rle with old method : 0.008277177810668945 length of segment : 112 time for calcul the mask position with numpy : 6.794929504394531e-05 nb_pixel_total : 2194 time to create 1 rle with old method : 0.0026133060455322266 length of segment : 41 time for calcul the mask position with numpy : 0.00013113021850585938 nb_pixel_total : 6451 time to create 1 rle with old method : 0.007544994354248047 length of segment : 91 time for calcul the mask position with numpy : 0.0002048015594482422 nb_pixel_total : 12360 time to create 1 rle with old method : 0.01434016227722168 length of segment : 122 time for calcul the mask position with numpy : 0.0002570152282714844 nb_pixel_total : 15887 time to create 1 rle with old method : 0.01805734634399414 length of segment : 186 time for calcul the mask position with numpy : 8.678436279296875e-05 nb_pixel_total : 3696 time to create 1 rle with old method : 0.004502058029174805 length of segment : 58 time for calcul the mask position with numpy : 0.04130268096923828 nb_pixel_total : 1202211 time to create 1 rle with new method : 0.06910538673400879 length of segment : 1692 time for calcul the mask position with numpy : 0.0013527870178222656 nb_pixel_total : 51996 time to create 1 rle with old method : 0.05891823768615723 length of segment : 290 time for calcul the mask position with numpy : 0.002302885055541992 nb_pixel_total : 112210 time to create 1 rle with old method : 0.1276853084564209 length of segment : 614 time for calcul the mask position with numpy : 0.0004630088806152344 nb_pixel_total : 11172 time to create 1 rle with old method : 0.0191042423248291 length of segment : 146 time for calcul the mask position with numpy : 0.00027298927307128906 nb_pixel_total : 5669 time to create 1 rle with old method : 0.006601572036743164 length of segment : 130 time for calcul the mask position with numpy : 0.00023174285888671875 nb_pixel_total : 5439 time to create 1 rle with old method : 0.0065059661865234375 length of segment : 98 time for calcul the mask position with numpy : 0.00020766258239746094 nb_pixel_total : 4776 time to create 1 rle with old method : 0.005815744400024414 length of segment : 78 time for calcul the mask position with numpy : 0.0012841224670410156 nb_pixel_total : 68001 time to create 1 rle with old method : 0.07784867286682129 length of segment : 202 time for calcul the mask position with numpy : 0.000461578369140625 nb_pixel_total : 13732 time to create 1 rle with old method : 0.015874862670898438 length of segment : 170 time for calcul the mask position with numpy : 0.0017654895782470703 nb_pixel_total : 83660 time to create 1 rle with old method : 0.09422874450683594 length of segment : 426 time for calcul the mask position with numpy : 0.0003857612609863281 nb_pixel_total : 12566 time to create 1 rle with old method : 0.014679908752441406 length of segment : 152 time for calcul the mask position with numpy : 0.0005500316619873047 nb_pixel_total : 18693 time to create 1 rle with old method : 0.021806001663208008 length of segment : 225 time spent for convertir_results : 2.5250191688537598 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 27 chid ids of type : 3594 Number RLEs to save : 6614 save missing photos in datou_result : time spend for datou_step_exec : 24.838863134384155 time spend to save output : 0.46793055534362793 total time spend for step 1 : 25.306793689727783 step2:crop_condition Tue Sep 2 14:40:55 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 : 11 ! batch 1 Loaded 27 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++ begin to crop the class : papier param for this class : {'min_score': 0.7} filtre for class : papier hashtag_id of this class : 492668766 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 11 About to insert : list_path_to_insert length 11 new photo from crops ! About to upload 11 photos upload in portfolio : 3736932 init cache_photo without model_param we have 11 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1756816856_3189108 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 11 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.2776052951812744 we have finished the crop for the class : papier begin to crop the class : carton param for this class : {'min_score': 0.7} filtre for class : carton hashtag_id of this class : 492774966 we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 2 new photo from crops ! About to upload 2 photos upload in portfolio : 3736932 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1756816860_3189108 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 2 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.7566735744476318 we have finished the crop for the class : carton begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 begin to crop the class : pet_clair param for this class : {'min_score': 0.7} filtre for class : pet_clair hashtag_id of this class : 2107755846 we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! we have both polygon and rles Next one ! map_result returned by crop_photo_return_map_crop : length : 14 About to insert : list_path_to_insert length 14 new photo from crops ! About to upload 14 photos upload in portfolio : 3736932 init cache_photo without model_param we have 14 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1756816869_3189108 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first This is a hack ! we have uploaded 14 photos in the portfolio 3736932 time of upload the photos Elapsed time : 3.8487167358398438 we have finished the crop for the class : pet_clair begin to crop the class : autre param for this class : {'min_score': 0.7} filtre for class : autre hashtag_id of this class : 494826614 begin to crop the class : pehd param for this class : {'min_score': 0.7} filtre for class : pehd hashtag_id of this class : 628944319 begin to crop the class : pet_fonce param for this class : {'min_score': 0.7} filtre for class : pet_fonce hashtag_id of this class : 2107755900 delete rles from all chi we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles we have 0 chi objets contains the rles 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 [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] Looping around the photos to save general results len do output : 27 /1380851435Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851436Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851437Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851438Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851439Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851440Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851441Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851442Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851443Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851444Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851445Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851448Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851449Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851455Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851456Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851457Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851458Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851459Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851460Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851461Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851462Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851463Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851464Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851465Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851466Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851467Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1380851468Didn'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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 92 time used for this insertion : 0.018014192581176758 save_final save missing photos in datou_result : time spend for datou_step_exec : 17.679662704467773 time spend to save output : 0.01932668685913086 total time spend for step 2 : 17.698989391326904 step3:rle_unique_nms_with_priority Tue Sep 2 14:41:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 27 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.21440386772155762 time for calcul the mask position with numpy : 0.08890652656555176 nb_pixel_total : 2058140 time to create 1 rle with new method : 0.09595918655395508 time for calcul the mask position with numpy : 0.006653785705566406 nb_pixel_total : 15460 time to create 1 rle with old method : 0.017426252365112305 create new chi : 0.22032546997070312 time to delete rle : 0.0286562442779541 batch 1 Loaded 3 chid ids of type : 3594 ++Number RLEs to save : 1332 TO DO : save crop sub photo not yet done ! save time : 0.12753891944885254 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.1618635654449463 time for calcul the mask position with numpy : 0.07872915267944336 nb_pixel_total : 2016847 time to create 1 rle with new method : 0.10999393463134766 time for calcul the mask position with numpy : 0.0071370601654052734 nb_pixel_total : 56753 time to create 1 rle with old method : 0.0635838508605957 create new chi : 0.26979517936706543 time to delete rle : 0.0003101825714111328 batch 1 Loaded 3 chid ids of type : 3594 +++Number RLEs to save : 1590 TO DO : save crop sub photo not yet done ! save time : 0.1327662467956543 nb_obj : 6 nb_hashtags : 2 time to prepare the origin masks : 0.24303078651428223 time for calcul the mask position with numpy : 0.07584643363952637 nb_pixel_total : 1905008 time to create 1 rle with new method : 0.1058206558227539 time for calcul the mask position with numpy : 0.01221323013305664 nb_pixel_total : 101843 time to create 1 rle with old method : 0.11089801788330078 time for calcul the mask position with numpy : 0.007090330123901367 nb_pixel_total : 12043 time to create 1 rle with old method : 0.013321638107299805 time for calcul the mask position with numpy : 0.006497383117675781 nb_pixel_total : 3442 time to create 1 rle with old method : 0.0039212703704833984 time for calcul the mask position with numpy : 0.006292581558227539 nb_pixel_total : 3793 time to create 1 rle with old method : 0.004267454147338867 time for calcul the mask position with numpy : 0.0075495243072509766 nb_pixel_total : 25417 time to create 1 rle with old method : 0.028619766235351562 time for calcul the mask position with numpy : 0.0067327022552490234 nb_pixel_total : 22054 time to create 1 rle with old method : 0.024853229522705078 create new chi : 0.42320942878723145 time to delete rle : 0.0005824565887451172 batch 1 Loaded 13 chid ids of type : 3594 +++++++Number RLEs to save : 3656 TO DO : save crop sub photo not yet done ! save time : 0.24584674835205078 nb_obj : 4 nb_hashtags : 2 time to prepare the origin masks : 0.11615586280822754 time for calcul the mask position with numpy : 0.029305696487426758 nb_pixel_total : 2049762 time to create 1 rle with new method : 0.14896011352539062 time for calcul the mask position with numpy : 0.0067615509033203125 nb_pixel_total : 6451 time to create 1 rle with old method : 0.007276773452758789 time for calcul the mask position with numpy : 0.006653547286987305 nb_pixel_total : 2194 time to create 1 rle with old method : 0.0025038719177246094 time for calcul the mask position with numpy : 0.00783395767211914 nb_pixel_total : 7061 time to create 1 rle with old method : 0.007993459701538086 time for calcul the mask position with numpy : 0.006547212600708008 nb_pixel_total : 8132 time to create 1 rle with old method : 0.00917673110961914 create new chi : 0.24431204795837402 time to delete rle : 0.00032830238342285156 batch 1 Loaded 9 chid ids of type : 3594 +++++Number RLEs to save : 1792 TO DO : save crop sub photo not yet done ! save time : 0.15500807762145996 nb_obj : 3 nb_hashtags : 2 time to prepare the origin masks : 0.062077999114990234 time for calcul the mask position with numpy : 0.026241540908813477 nb_pixel_total : 2041657 time to create 1 rle with new method : 0.0832056999206543 time for calcul the mask position with numpy : 0.006406068801879883 nb_pixel_total : 3696 time to create 1 rle with old method : 0.004253864288330078 time for calcul the mask position with numpy : 0.007054567337036133 nb_pixel_total : 15887 time to create 1 rle with old method : 0.0181581974029541 time for calcul the mask position with numpy : 0.006365776062011719 nb_pixel_total : 12360 time to create 1 rle with old method : 0.015761852264404297 create new chi : 0.17591571807861328 time to delete rle : 0.0003609657287597656 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 1812 TO DO : save crop sub photo not yet done ! save time : 0.1558856964111328 nb_obj : 3 nb_hashtags : 1 time to prepare the origin masks : 0.0714731216430664 time for calcul the mask position with numpy : 0.0195620059967041 nb_pixel_total : 709950 time to create 1 rle with new method : 0.18816590309143066 time for calcul the mask position with numpy : 0.007974624633789062 nb_pixel_total : 112210 time to create 1 rle with old method : 0.13548064231872559 time for calcul the mask position with numpy : 0.006794929504394531 nb_pixel_total : 49229 time to create 1 rle with old method : 0.05500149726867676 time for calcul the mask position with numpy : 0.04427456855773926 nb_pixel_total : 1202211 time to create 1 rle with new method : 0.09965753555297852 create new chi : 0.5738005638122559 time to delete rle : 0.0008292198181152344 batch 1 Loaded 7 chid ids of type : 3594 ++++++Number RLEs to save : 6132 TO DO : save crop sub photo not yet done ! save time : 0.39354777336120605 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.04873204231262207 time for calcul the mask position with numpy : 0.1072843074798584 nb_pixel_total : 2056759 time to create 1 rle with new method : 0.1124563217163086 time for calcul the mask position with numpy : 0.006476402282714844 nb_pixel_total : 5669 time to create 1 rle with old method : 0.006421804428100586 time for calcul the mask position with numpy : 0.006364107131958008 nb_pixel_total : 11172 time to create 1 rle with old method : 0.012784957885742188 create new chi : 0.2611227035522461 time to delete rle : 0.000316619873046875 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1632 TO DO : save crop sub photo not yet done ! save time : 0.13446617126464844 No data in photo_id : 1380833330 nb_obj : 3 nb_hashtags : 3 time to prepare the origin masks : 0.453643798828125 time for calcul the mask position with numpy : 0.07499122619628906 nb_pixel_total : 1995384 time to create 1 rle with new method : 0.2311234474182129 time for calcul the mask position with numpy : 0.006886482238769531 nb_pixel_total : 68001 time to create 1 rle with old method : 0.07723402976989746 time for calcul the mask position with numpy : 0.0062961578369140625 nb_pixel_total : 4776 time to create 1 rle with old method : 0.005414724349975586 time for calcul the mask position with numpy : 0.006414175033569336 nb_pixel_total : 5439 time to create 1 rle with old method : 0.006165981292724609 create new chi : 0.42405152320861816 time to delete rle : 0.00035309791564941406 batch 1 Loaded 7 chid ids of type : 3594 ++++Number RLEs to save : 1836 TO DO : save crop sub photo not yet done ! save time : 0.16336870193481445 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.04138994216918945 time for calcul the mask position with numpy : 0.039003849029541016 nb_pixel_total : 1976208 time to create 1 rle with new method : 0.10832047462463379 time for calcul the mask position with numpy : 0.006609439849853516 nb_pixel_total : 83660 time to create 1 rle with old method : 0.09241151809692383 time for calcul the mask position with numpy : 0.006105184555053711 nb_pixel_total : 13732 time to create 1 rle with old method : 0.0153350830078125 create new chi : 0.27663612365722656 time to delete rle : 0.0003459453582763672 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2272 TO DO : save crop sub photo not yet done ! save time : 0.18867993354797363 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.09119725227355957 time for calcul the mask position with numpy : 0.12523436546325684 nb_pixel_total : 2042341 time to create 1 rle with new method : 0.08632278442382812 time for calcul the mask position with numpy : 0.00630497932434082 nb_pixel_total : 18693 time to create 1 rle with old method : 0.020443439483642578 time for calcul the mask position with numpy : 0.0060808658599853516 nb_pixel_total : 12566 time to create 1 rle with old method : 0.013904809951782227 create new chi : 0.2682669162750244 time to delete rle : 0.0002968311309814453 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1834 TO DO : save crop sub photo not yet done ! save time : 0.1604936122894287 map_output_result : {1380833400: (0.0, 'Should be the crop_list due to order', 0), 1380833397: (0.0, 'Should be the crop_list due to order', 0), 1380833394: (0.0, 'Should be the crop_list due to order', 0), 1380833381: (0.0, 'Should be the crop_list due to order', 0), 1380833379: (0.0, 'Should be the crop_list due to order', 0), 1380833339: (0.0, 'Should be the crop_list due to order', 0), 1380833338: (0.0, 'Should be the crop_list due to order', 0), 1380833330: (0.0, 'Should be the crop_list due to order', 0.0), 1380833311: (0.0, 'Should be the crop_list due to order', 0), 1380833301: (0.0, 'Should be the crop_list due to order', 0), 1380833289: (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 [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] Looping around the photos to save general results len do output : 11 /1380833400.Didn't retrieve data . /1380833397.Didn't retrieve data . /1380833394.Didn't retrieve data . /1380833381.Didn't retrieve data . /1380833379.Didn't retrieve data . /1380833339.Didn't retrieve data . /1380833338.Didn't retrieve data . /1380833330.Didn't retrieve data . /1380833311.Didn't retrieve data . /1380833301.Didn't retrieve data . /1380833289.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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 33 time used for this insertion : 0.01406550407409668 save_final save missing photos in datou_result : time spend for datou_step_exec : 6.911848545074463 time spend to save output : 0.014542579650878906 total time spend for step 3 : 6.926391124725342 step4:ventilate_hashtags_in_portfolio Tue Sep 2 14:41:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 26440559 get user id for portfolio 26440559 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`=26440559 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','pet_fonce','papier','pet_clair','carton','pehd','mal_croppe','autre','environnement','metal','background')) AND mptpi.`min_score`=0.5 To do To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=26440559 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','pet_fonce','papier','pet_clair','carton','pehd','mal_croppe','autre','environnement','metal','background')) 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`=26440559 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('flou','pet_fonce','papier','pet_clair','carton','pehd','mal_croppe','autre','environnement','metal','background')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://marlene.fotonower.com/velours/26440727,26440728,26440729,26440730,26440731,26440732,26440733,26440734,26440735,26440736,26440737?tags=flou,pet_fonce,papier,pet_clair,carton,pehd,mal_croppe,autre,environnement,metal,background Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] Looping around the photos to save general results len do output : 1 /26440559. 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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 12 time used for this insertion : 0.014858245849609375 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.7215876579284668 time spend to save output : 0.015105724334716797 total time spend for step 4 : 0.7366933822631836 step5:final Tue Sep 2 14:41:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! Catched exception ! Connect or reconnect ! Inside saveOutput : final : False verbose : 0 original output for save of step final : {1380833400: ('0.08259434624017961',), 1380833397: ('0.08259434624017961',), 1380833394: ('0.08259434624017961',), 1380833381: ('0.08259434624017961',), 1380833379: ('0.08259434624017961',), 1380833339: ('0.08259434624017961',), 1380833338: ('0.08259434624017961',), 1380833330: ('0.08259434624017961',), 1380833311: ('0.08259434624017961',), 1380833301: ('0.08259434624017961',), 1380833289: ('0.08259434624017961',)} new output for save of step final : {1380833400: ('0.08259434624017961',), 1380833397: ('0.08259434624017961',), 1380833394: ('0.08259434624017961',), 1380833381: ('0.08259434624017961',), 1380833379: ('0.08259434624017961',), 1380833339: ('0.08259434624017961',), 1380833338: ('0.08259434624017961',), 1380833330: ('0.08259434624017961',), 1380833311: ('0.08259434624017961',), 1380833301: ('0.08259434624017961',), 1380833289: ('0.08259434624017961',)} [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] Looping around the photos to save general results len do output : 11 /1380833400.Didn't retrieve data . /1380833397.Didn't retrieve data . /1380833394.Didn't retrieve data . /1380833381.Didn't retrieve data . /1380833379.Didn't retrieve data . /1380833339.Didn't retrieve data . /1380833338.Didn't retrieve data . /1380833330.Didn't retrieve data . /1380833311.Didn't retrieve data . /1380833301.Didn't retrieve data . /1380833289.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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 33 time used for this insertion : 0.01642155647277832 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.12154269218444824 time spend to save output : 0.016973018646240234 total time spend for step 5 : 0.13851571083068848 step6:blur_detection Tue Sep 2 14:41:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection methode: ratio et variance treat image : temp/1756816828_3189108_1380833400_6674204695d69a4efac65deace96938b.jpg resize: (1080, 1920) 1380833400 1.072965190646014 treat image : temp/1756816828_3189108_1380833397_0dcae49e690926c8462e000394c7d79a.jpg resize: (1080, 1920) 1380833397 -0.7091052150718151 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089.jpg resize: (1080, 1920) 1380833394 0.8577691513609929 treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344.jpg resize: (1080, 1920) 1380833381 0.23247461074827816 treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759.jpg resize: (1080, 1920) 1380833379 0.9790779138876189 treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda.jpg resize: (1080, 1920) 1380833339 1.4695038670093883 treat image : temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa.jpg resize: (1080, 1920) 1380833338 -0.15383537369844436 treat image : temp/1756816828_3189108_1380833330_8fb92a3eec128fda22abc2a271769ee6.jpg resize: (1080, 1920) 1380833330 0.06559617157472086 treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b.jpg resize: (1080, 1920) 1380833311 -1.0797614213667726 treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f.jpg resize: (1080, 1920) 1380833301 -0.5675184609580474 treat image : temp/1756816828_3189108_1380833289_633b3a288c2fa732de1852e3347bbf52.jpg resize: (1080, 1920) 1380833289 -1.2143046154850812 treat image : temp/1756816828_3189108_1380833400_6674204695d69a4efac65deace96938b_rle_crop_3940540040_0.png resize: (124, 193) 1380851435 -1.865618336697533 treat image : temp/1756816828_3189108_1380833397_0dcae49e690926c8462e000394c7d79a_rle_crop_3940540041_0.png resize: (245, 363) 1380851436 -2.3944284144935506 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540044_0.png resize: (120, 76) 1380851437 -2.2317728805051584 treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344_rle_crop_3940540050_0.png resize: (40, 73) 1380851438 4.876013283423633 treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344_rle_crop_3940540049_0.png resize: (86, 132) 1380851439 -0.8730309139607204 treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344_rle_crop_3940540051_0.png resize: (89, 106) 1380851440 -1.7106517263540424 treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759_rle_crop_3940540054_0.png resize: (58, 90) 1380851441 1.7529407707505642 treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759_rle_crop_3940540052_0.png resize: (122, 163) 1380851442 1.252413599523705 treat image : temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa_rle_crop_3940540059_0.png resize: (130, 60) 1380851443 -0.5945857022972659 treat image : temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa_rle_crop_3940540058_0.png resize: (140, 140) 1380851444 -1.9501858757541752 treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540062_0.png resize: (191, 449) 1380851445 -1.887664088140083 treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540061_0.png resize: (78, 90) 1380851448 -1.5080981706496768 treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f_rle_crop_3940540063_0.png resize: (170, 101) 1380851449 -0.1710358307332068 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540046_0.png resize: (129, 136) 1380851455 -0.47276681926376823 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540045_0.png resize: (69, 63) 1380851456 0.7234905571917777 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540042_0.png resize: (240, 142) 1380851457 -1.5394442830888313 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540047_0.png resize: (467, 351) 1380851458 0.00015350390996954986 treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540043_0.png resize: (220, 224) 1380851459 -1.2663263075972029 treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344_rle_crop_3940540048_0.png resize: (112, 94) 1380851460 -2.392474391366522 treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759_rle_crop_3940540053_0.png resize: (184, 113) 1380851461 -1.4870476410167817 treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540055_0.png resize: (1007, 1542) 1380851462 -0.9501424721823487 treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540056_0.png resize: (252, 309) 1380851463 -0.8968055931794897 treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540057_0.png resize: (611, 314) 1380851464 0.34879737334445843 treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540060_0.png resize: (93, 78) 1380851465 0.6676521932853503 treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f_rle_crop_3940540064_0.png resize: (424, 290) 1380851466 -0.24157499832168564 treat image : temp/1756816828_3189108_1380833289_633b3a288c2fa732de1852e3347bbf52_rle_crop_3940540065_0.png resize: (152, 108) 1380851467 -1.3207797739644809 treat image : temp/1756816828_3189108_1380833289_633b3a288c2fa732de1852e3347bbf52_rle_crop_3940540066_0.png resize: (225, 112) 1380851468 -2.5712641414917563 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 : 38 time used for this insertion : 0.01670980453491211 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 38 time used for this insertion : 0.01736736297607422 save missing photos in datou_result : time spend for datou_step_exec : 9.988572120666504 time spend to save output : 0.038465261459350586 total time spend for step 6 : 10.027037382125854 step7:brightness Tue Sep 2 14:41:30 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 Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness treat image : temp/1756816828_3189108_1380833400_6674204695d69a4efac65deace96938b.jpg treat image : temp/1756816828_3189108_1380833397_0dcae49e690926c8462e000394c7d79a.jpg treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089.jpg treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344.jpg treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759.jpg treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda.jpg treat image : temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa.jpg treat image : temp/1756816828_3189108_1380833330_8fb92a3eec128fda22abc2a271769ee6.jpg treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b.jpg treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f.jpg treat image : 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temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa_rle_crop_3940540059_0.png treat image : temp/1756816828_3189108_1380833338_8fc1923bae49d004d3f0cd1658dc6eaa_rle_crop_3940540058_0.png treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540062_0.png treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540061_0.png treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f_rle_crop_3940540063_0.png treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540046_0.png treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540045_0.png treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540042_0.png treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540047_0.png treat image : temp/1756816828_3189108_1380833394_f2d882291ce60958a4d35ea48d67f089_rle_crop_3940540043_0.png treat image : temp/1756816828_3189108_1380833381_7d72767a1ebe11f64aab7804f39a9344_rle_crop_3940540048_0.png treat image : temp/1756816828_3189108_1380833379_6e5c5c99c2ece77f346b8aaa8d56d759_rle_crop_3940540053_0.png treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540055_0.png treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540056_0.png treat image : temp/1756816828_3189108_1380833339_0c240e0f8fa818668ae42439f4210bda_rle_crop_3940540057_0.png treat image : temp/1756816828_3189108_1380833311_65cd96a60b276e15a0149830778f3c5b_rle_crop_3940540060_0.png treat image : temp/1756816828_3189108_1380833301_b9e24b7abb08ac2cf80ff33f22c4153f_rle_crop_3940540064_0.png treat image : temp/1756816828_3189108_1380833289_633b3a288c2fa732de1852e3347bbf52_rle_crop_3940540065_0.png treat image : temp/1756816828_3189108_1380833289_633b3a288c2fa732de1852e3347bbf52_rle_crop_3940540066_0.png Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 38 time used for this insertion : 0.01286625862121582 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 38 time used for this insertion : 0.013009786605834961 save missing photos in datou_result : time spend for datou_step_exec : 2.9760801792144775 time spend to save output : 0.0306551456451416 total time spend for step 7 : 3.006735324859619 step8:velours_tree Tue Sep 2 14:41:33 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 : 0.16122150421142578 time spend to save output : 3.886222839355469e-05 total time spend for step 8 : 0.16126036643981934 step9:send_mail_cod Tue Sep 2 14:41:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 2 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /home/admin/workarea/git/Velours/python in order to get the selector url, please entre the license of selector results_Auto_P26440559_02-09-2025_14_41_33.pdf 26440727 imagette264407271756816893 26440728 imagette264407281756816893 26440729 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 .imagette264407291756816893 26440730 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 .imagette264407301756816894 26440731 change filename to text .change filename to text .imagette264407311756816895 26440732 imagette264407321756816895 26440733 imagette264407331756816895 26440734 imagette264407341756816895 26440736 imagette264407361756816895 26440737 imagette264407371756816895 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=26440559 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://marlene.fotonower.com/velours/26440727,26440728,26440729,26440730,26440731,26440732,26440733,26440734,26440735,26440736,26440737?tags=flou,pet_fonce,papier,pet_clair,carton,pehd,mal_croppe,autre,environnement,metal,background args[1380833400] : ((1380833400, 1.072965190646014, 492688767), (1380833400, 0.5129788096786452, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833397] : ((1380833397, -0.7091052150718151, 492688767), (1380833397, 0.5815763064467707, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833394] : ((1380833394, 0.8577691513609929, 492688767), (1380833394, 0.7631672613154117, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833381] : ((1380833381, 0.23247461074827816, 492688767), (1380833381, 0.6253247039920878, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833379] : ((1380833379, 0.9790779138876189, 492688767), (1380833379, 0.5844125143735738, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833339] : ((1380833339, 1.4695038670093883, 492688767), (1380833339, 0.7499253256229288, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833338] : ((1380833338, -0.15383537369844436, 492688767), (1380833338, 0.6196588422195862, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833330] : ((1380833330, 0.06559617157472086, 492688767), (1380833330, 0.7008414357655096, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833311] : ((1380833311, -1.0797614213667726, 492688767), (1380833311, 0.6867392548290233, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833301] : ((1380833301, -0.5675184609580474, 492688767), (1380833301, 0.6653675399439971, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com args[1380833289] : ((1380833289, -1.2143046154850812, 492688767), (1380833289, 0.7232226519178901, 2107752395), '0.08259434624017961') We are sending mail with results at report@fotonower.com refus_total : 0.08259434624017961 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=26440559 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26440559_02-09-2025_14_41_33.pdf results_Auto_P26440559_02-09-2025_14_41_33.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26440559_02-09-2025_14_41_33.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','26440559','results_Auto_P26440559_02-09-2025_14_41_33.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26440559_02-09-2025_14_41_33.pdf','pdf','','0.3','0.08259434624017961') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/26440559

https://www.fotonower.com/image?json=false&list_photos_id=1380833400
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.072965190646014)
https://www.fotonower.com/image?json=false&list_photos_id=1380833397
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833394
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833381
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833379
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833339
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.4695038670093883)
https://www.fotonower.com/image?json=false&list_photos_id=1380833338
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833330
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833311
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833301
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1380833289
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 8.26%
Veuillez trouver les photos des contaminants.

exemples de contaminants: papier: https://www.fotonower.com/view/26440729?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/26440730?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/26440731?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26440559_02-09-2025_14_41_33.pdf.

Lien vers velours :https://marlene.fotonower.com/velours/26440727,26440728,26440729,26440730,26440731,26440732,26440733,26440734,26440735,26440736,26440737?tags=flou,pet_fonce,papier,pet_clair,carton,pehd,mal_croppe,autre,environnement,metal,background.


L'équipe Fotonower 202 b'' Server: nginx Date: Tue, 02 Sep 2025 12:41:37 GMT Content-Length: 0 Connection: close X-Message-Id: xUtNluXNSOSgZ7Vq12EdTQ 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 [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] 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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.013761758804321289 save_final save missing photos in datou_result : time spend for datou_step_exec : 3.6192848682403564 time spend to save output : 0.014014959335327148 total time spend for step 9 : 3.6332998275756836 step10:split_time_score Tue Sep 2 14:41:37 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'}] (('12', 11),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 02092025 26440559 Nombre de photos uploadées : 11 / 23040 (0%) 02092025 26440559 Nombre de photos taguées (types de déchets): 0 / 11 (0%) 02092025 26440559 Nombre de photos taguées (volume) : 0 / 11 (0%) elapsed_time : load_data_split_time_score 1.6689300537109375e-06 elapsed_time : order_list_meta_photo_and_scores 5.9604644775390625e-06 ??????????? elapsed_time : fill_and_build_computed_from_old_data 0.0006208419799804688 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.21646523475646973 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 : 0.054770953896604954 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26429659_02-09-2025_09_32_37.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26429659 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`=26429659 AND mptpi.`type`=3594 To do Qualite : 0.0918425188362382 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26435866_02-09-2025_12_12_07.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26435866 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`=26435866 AND mptpi.`type`=3594 To do Qualite : 0.13202340242704827 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26435870_02-09-2025_12_02_03.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26435870 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`=26435870 AND mptpi.`type`=3594 To do Qualite : 0.21863142602237648 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26435873_02-09-2025_13_01_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26435873 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`=26435873 AND mptpi.`type`=3594 To do Qualite : 0.028957288451646086 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26438219_02-09-2025_13_11_36.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26438219 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`=26438219 AND mptpi.`type`=3594 To do Qualite : 0.08259434624017961 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P26440559_02-09-2025_14_41_33.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 26440559 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`=26440559 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'02092025': {'nb_upload': 11, '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 [1380833400, 1380833397, 1380833394, 1380833381, 1380833379, 1380833339, 1380833338, 1380833330, 1380833311, 1380833301, 1380833289] Looping around the photos to save general results len do output : 1 /26440559Didn'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, '3652102') ('3318', '26440559', '1380833400', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833397', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833394', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833381', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833379', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833339', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833338', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833330', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833311', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833301', None, None, None, None, None, '3652102') ('3318', None, None, None, None, None, None, None, '3652102') ('3318', '26440559', '1380833289', None, None, None, None, None, '3652102') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 12 time used for this insertion : 0.01336216926574707 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.7789063453674316 time spend to save output : 0.013609886169433594 total time spend for step 10 : 0.7925162315368652 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 11 set_done_treatment 40.80user 17.38system 1:12.66elapsed 80%CPU (0avgtext+0avgdata 2686432maxresident)k 552872inputs+20392outputs (660major+1513090minor)pagefaults 0swaps