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 : 2779280 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 : ['3410768'] with mtr_portfolio_ids : ['25543232'] and first list_photo_ids : [] new path : /proc/2779280/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 12 ; length of list_pids : 12 ; length of list_args : 12 time to download the photos : 1.5406944751739502 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 10 step1:mask_detect Thu Jul 31 14:50:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec 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 : 8538 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-07-31 14:50:31.082407: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-31 14:50:31.107322: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-31 14:50:31.108908: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f11e0000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-31 14:50:31.108957: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-31 14:50:31.111748: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-31 14:50:31.254144: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3aac41a0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-31 14:50:31.254200: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-31 14:50:31.255941: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-31 14:50:31.256517: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:50:31.260608: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:50:31.264050: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:50:31.264602: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:50:31.267578: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:50:31.269015: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:50:31.275235: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:50:31.276906: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:50:31.277001: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:50:31.277714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-31 14:50:31.277731: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-31 14:50:31.277757: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-31 14:50:31.278954: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7883 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-07-31 14:50:31.583495: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-31 14:50:31.583628: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:50:31.583658: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:50:31.583684: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:50:31.583710: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:50:31.583735: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:50:31.583759: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:50:31.583785: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:50:31.585108: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:50:31.586219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-31 14:50:31.586252: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-31 14:50:31.586269: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:50:31.586284: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-31 14:50:31.586300: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-31 14:50:31.586315: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-31 14:50:31.586330: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-31 14:50:31.586345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-31 14:50:31.587430: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-31 14:50:31.587466: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-31 14:50:31.587475: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-31 14:50:31.587483: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-31 14:50:31.588650: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7883 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : learn_RUBBIA_REFUS_AMIENS_23 model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-07-31 14:50:39.986995: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-31 14:50:40.182123: 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 : 12 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 22.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 33.00000 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: 31.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 6 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 23.00000 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: 20.00000 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: 23.00000 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: 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 : 5 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 1 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 26.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 17) min: 0.00000 max: 1920.00000 nb d'objets trouves : 3 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 : 8 NEW PHOTO Processing 1 images image shape: (1080, 1920, 3) min: 20.00000 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: 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 : 4 Detection mask done ! Trying to reset tf kernel 2779813 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2056 tf kernel not reseted sub process len(results) : 12 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 12 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 : 7566 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 : 0.0002789497375488281 nb_pixel_total : 3234 time to create 1 rle with old method : 0.004003286361694336 length of segment : 151 time for calcul the mask position with numpy : 0.16235041618347168 nb_pixel_total : 757093 time to create 1 rle with new method : 0.33284473419189453 length of segment : 988 time for calcul the mask position with numpy : 0.011719465255737305 nb_pixel_total : 732749 time to create 1 rle with new method : 0.046405792236328125 length of segment : 954 time for calcul the mask position with numpy : 0.00010347366333007812 nb_pixel_total : 3559 time to create 1 rle with old method : 0.0038280487060546875 length of segment : 84 time for calcul the mask position with numpy : 0.00035262107849121094 nb_pixel_total : 21268 time to create 1 rle with old method : 0.021697044372558594 length of segment : 196 time for calcul the mask position with numpy : 0.0015192031860351562 nb_pixel_total : 109963 time to create 1 rle with old method : 0.11024975776672363 length of segment : 552 time for calcul the mask position with numpy : 8.988380432128906e-05 nb_pixel_total : 3053 time to create 1 rle with old method : 0.0033266544342041016 length of segment : 66 time for calcul the mask position with numpy : 9.989738464355469e-05 nb_pixel_total : 2996 time to create 1 rle with old method : 0.003490924835205078 length of segment : 50 time for calcul the mask position with numpy : 0.017104625701904297 nb_pixel_total : 885714 time to create 1 rle with new method : 0.07262182235717773 length of segment : 1269 time for calcul the mask position with numpy : 8.296966552734375e-05 nb_pixel_total : 1628 time to create 1 rle with old method : 0.0018672943115234375 length of segment : 42 time for calcul the mask position with numpy : 0.00018167495727539062 nb_pixel_total : 9874 time to create 1 rle with old method : 0.012020349502563477 length of segment : 118 time for calcul the mask position with numpy : 0.0019009113311767578 nb_pixel_total : 94591 time to create 1 rle with old method : 0.1021871566772461 length of segment : 522 time for calcul the mask position with numpy : 0.0004429817199707031 nb_pixel_total : 11729 time to create 1 rle with old method : 0.012355804443359375 length of segment : 203 time for calcul the mask position with numpy : 0.0003848075866699219 nb_pixel_total : 12982 time to create 1 rle with old method : 0.013916015625 length of segment : 132 time for calcul the mask position with numpy : 0.014319658279418945 nb_pixel_total : 750421 time to create 1 rle with new method : 0.04519367218017578 length of segment : 975 time for calcul the mask position with numpy : 0.01355600357055664 nb_pixel_total : 717323 time to create 1 rle with new method : 0.04705047607421875 length of segment : 975 time for calcul the mask position with numpy : 0.00029087066650390625 nb_pixel_total : 8009 time to create 1 rle with old method : 0.008400440216064453 length of segment : 132 time for calcul the mask position with numpy : 0.013520002365112305 nb_pixel_total : 692878 time to create 1 rle with new method : 0.034171342849731445 length of segment : 954 time for calcul the mask position with numpy : 0.0002574920654296875 nb_pixel_total : 12883 time to create 1 rle with old method : 0.013505220413208008 length of segment : 123 time for calcul the mask position with numpy : 0.0001270771026611328 nb_pixel_total : 7888 time to create 1 rle with old method : 0.008681058883666992 length of segment : 73 time for calcul the mask position with numpy : 0.0015864372253417969 nb_pixel_total : 107179 time to create 1 rle with old method : 0.11842513084411621 length of segment : 515 time for calcul the mask position with numpy : 0.014249086380004883 nb_pixel_total : 751334 time to create 1 rle with new method : 0.04991507530212402 length of segment : 984 time for calcul the mask position with numpy : 0.013713598251342773 nb_pixel_total : 764305 time to create 1 rle with new method : 0.05291604995727539 length of segment : 992 time for calcul the mask position with numpy : 0.0002884864807128906 nb_pixel_total : 15770 time to create 1 rle with old method : 0.017702102661132812 length of segment : 193 time for calcul the mask position with numpy : 0.00023126602172851562 nb_pixel_total : 12829 time to create 1 rle with old method : 0.014430522918701172 length of segment : 119 time for calcul the mask position with numpy : 0.0007123947143554688 nb_pixel_total : 31185 time to create 1 rle with old method : 0.0336461067199707 length of segment : 233 time for calcul the mask position with numpy : 0.0001678466796875 nb_pixel_total : 7927 time to create 1 rle with old method : 0.009044647216796875 length of segment : 115 time spent for convertir_results : 3.1058783531188965 Inside saveOutput : final : False verbose : 0 eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 69 chid ids of type : 3594 +++++++++++++++++++++++++++Number RLEs to save : 11710 save missing photos in datou_result : time spend for datou_step_exec : 30.160544633865356 time spend to save output : 0.6894316673278809 total time spend for step 1 : 30.849976301193237 step2:crop_condition Thu Jul 31 14:50:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 12 ! batch 1 Loaded 69 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 ! 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/1753966260_2779280 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 : 3.5394041538238525 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 : 4 About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos upload in portfolio : 3736932 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1753966264_2779280 batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 4 photos in the portfolio 3736932 time of upload the photos Elapsed time : 1.2942957878112793 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 ! 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 : 34 About to insert : list_path_to_insert length 34 new photo from crops ! About to upload 34 photos upload in portfolio : 3736932 init cache_photo without model_param we have 34 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1753966290_2779280 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg 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 Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! batch_size : 0, verbose : False, strat_bulk_insert : ignore_different_from_first Unexecpected behavior in 07/2025 that can be generalized l287 : type_extension .jpg This is a hack ! we have uploaded 34 photos in the portfolio 3736932 time of upload the photos Elapsed time : 8.86030626296997 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 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 [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] Looping around the photos to save general results len do output : 52 /1374602934Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602935Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602936Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602937Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602938Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602939Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602940Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602941Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602942Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602943Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602944Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602945Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602946Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602947Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602948Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602949Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602950Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602951Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602960Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602961Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602962Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602963Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602964Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602965Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602966Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602967Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602968Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602969Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602970Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602971Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602972Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602973Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602974Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602975Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602976Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602977Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602978Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602979Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602980Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602981Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602982Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602983Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602984Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602985Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602986Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602987Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602988Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602989Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602990Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602991Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602992Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1374602993Didn'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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 168 time used for this insertion : 0.01965188980102539 save_final save missing photos in datou_result : time spend for datou_step_exec : 39.45620059967041 time spend to save output : 0.02238321304321289 total time spend for step 2 : 39.47858381271362 step3:rle_unique_nms_with_priority Thu Jul 31 14:51:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 69 chid ids of type : 3594 ++++++++++++++++++++++++++++++++++++nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.6375219821929932 time for calcul the mask position with numpy : 0.3166046142578125 nb_pixel_total : 1313273 time to create 1 rle with new method : 0.3710300922393799 time for calcul the mask position with numpy : 0.011008501052856445 nb_pixel_total : 757093 time to create 1 rle with new method : 0.09139513969421387 time for calcul the mask position with numpy : 0.006230592727661133 nb_pixel_total : 3234 time to create 1 rle with old method : 0.003545999526977539 create new chi : 0.8111786842346191 time to delete rle : 0.028033733367919922 batch 1 Loaded 6 chid ids of type : 3594 ++Number RLEs to save : 3358 TO DO : save crop sub photo not yet done ! save time : 0.23024439811706543 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.457409143447876 time for calcul the mask position with numpy : 0.3466672897338867 nb_pixel_total : 1337292 time to create 1 rle with new method : 0.09763693809509277 time for calcul the mask position with numpy : 0.006397247314453125 nb_pixel_total : 3559 time to create 1 rle with old method : 0.004034757614135742 time for calcul the mask position with numpy : 0.012507438659667969 nb_pixel_total : 732749 time to create 1 rle with new method : 0.32115793228149414 create new chi : 0.7966539859771729 time to delete rle : 0.0003025531768798828 batch 1 Loaded 6 chid ids of type : 3594 ++Number RLEs to save : 3156 TO DO : save crop sub photo not yet done ! save time : 0.21127986907958984 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.11217141151428223 time for calcul the mask position with numpy : 0.25932741165161133 nb_pixel_total : 2052067 time to create 1 rle with new method : 0.0918276309967041 time for calcul the mask position with numpy : 0.00625300407409668 nb_pixel_total : 42 time to create 1 rle with old method : 0.00011134147644042969 time for calcul the mask position with numpy : 0.006096363067626953 nb_pixel_total : 21491 time to create 1 rle with old method : 0.02343130111694336 create new chi : 0.3906240463256836 time to delete rle : 0.00029540061950683594 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1498 TO DO : save crop sub photo not yet done ! save time : 0.12068343162536621 nb_obj : 2 nb_hashtags : 2 time to prepare the origin masks : 0.20879864692687988 time for calcul the mask position with numpy : 0.5059010982513428 nb_pixel_total : 1960584 time to create 1 rle with new method : 0.317798376083374 time for calcul the mask position with numpy : 0.006162881851196289 nb_pixel_total : 3053 time to create 1 rle with old method : 0.003356456756591797 time for calcul the mask position with numpy : 0.007085084915161133 nb_pixel_total : 109963 time to create 1 rle with old method : 0.12073111534118652 create new chi : 0.9704272747039795 time to delete rle : 0.0003390312194824219 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 2316 TO DO : save crop sub photo not yet done ! save time : 0.1697230339050293 nb_obj : 7 nb_hashtags : 2 time to prepare the origin masks : 0.8740251064300537 time for calcul the mask position with numpy : 0.042218685150146484 nb_pixel_total : 1077124 time to create 1 rle with new method : 0.09512734413146973 time for calcul the mask position with numpy : 0.0064699649810791016 nb_pixel_total : 4069 time to create 1 rle with old method : 0.0047147274017333984 time for calcul the mask position with numpy : 0.006340742111206055 nb_pixel_total : 90865 time to create 1 rle with old method : 0.10078072547912598 time for calcul the mask position with numpy : 0.006644487380981445 nb_pixel_total : 9700 time to create 1 rle with old method : 0.010724067687988281 time for calcul the mask position with numpy : 0.006276845932006836 nb_pixel_total : 1504 time to create 1 rle with old method : 0.0027337074279785156 time for calcul the mask position with numpy : 0.006262540817260742 nb_pixel_total : 1628 time to create 1 rle with old method : 0.0018489360809326172 time for calcul the mask position with numpy : 0.013503313064575195 nb_pixel_total : 885714 time to create 1 rle with new method : 0.10237002372741699 time for calcul the mask position with numpy : 0.007193565368652344 nb_pixel_total : 2996 time to create 1 rle with old method : 0.0036733150482177734 create new chi : 0.42454051971435547 time to delete rle : 0.0009477138519287109 batch 1 Loaded 18 chid ids of type : 3594 ++++++++++Number RLEs to save : 6307 TO DO : save crop sub photo not yet done ! save time : 0.4126749038696289 nb_obj : 5 nb_hashtags : 3 time to prepare the origin masks : 0.17366337776184082 time for calcul the mask position with numpy : 0.015059232711791992 nb_pixel_total : 1291653 time to create 1 rle with new method : 0.06399250030517578 time for calcul the mask position with numpy : 0.011313676834106445 nb_pixel_total : 750421 time to create 1 rle with new method : 0.4638028144836426 time for calcul the mask position with numpy : 0.006260395050048828 nb_pixel_total : 12982 time to create 1 rle with old method : 0.016233205795288086 time for calcul the mask position with numpy : 0.006257772445678711 nb_pixel_total : 152 time to create 1 rle with old method : 0.00024437904357910156 time for calcul the mask position with numpy : 0.006314516067504883 nb_pixel_total : 13050 time to create 1 rle with old method : 0.014508724212646484 time for calcul the mask position with numpy : 0.0063817501068115234 nb_pixel_total : 5342 time to create 1 rle with old method : 0.005990743637084961 create new chi : 0.6244053840637207 time to delete rle : 0.0006325244903564453 batch 1 Loaded 11 chid ids of type : 3594 +++++Number RLEs to save : 4053 TO DO : save crop sub photo not yet done ! save time : 0.2672576904296875 nb_obj : 1 nb_hashtags : 1 time to prepare the origin masks : 0.0511326789855957 time for calcul the mask position with numpy : 0.015221834182739258 nb_pixel_total : 1356277 time to create 1 rle with new method : 0.06107473373413086 time for calcul the mask position with numpy : 0.011766910552978516 nb_pixel_total : 717323 time to create 1 rle with new method : 0.028817415237426758 create new chi : 0.1173701286315918 time to delete rle : 0.0002865791320800781 batch 1 Loaded 3 chid ids of type : 3594 +Number RLEs to save : 3030 TO DO : save crop sub photo not yet done ! save time : 0.19969630241394043 No data in photo_id : 1374568259 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.059870243072509766 time for calcul the mask position with numpy : 0.014950752258300781 nb_pixel_total : 1372713 time to create 1 rle with new method : 0.05506324768066406 time for calcul the mask position with numpy : 0.011413097381591797 nb_pixel_total : 692878 time to create 1 rle with new method : 0.030093669891357422 time for calcul the mask position with numpy : 0.00676727294921875 nb_pixel_total : 8009 time to create 1 rle with old method : 0.00895380973815918 create new chi : 0.12772846221923828 time to delete rle : 0.0006377696990966797 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 3252 TO DO : save crop sub photo not yet done ! save time : 0.20808148384094238 nb_obj : 5 nb_hashtags : 2 time to prepare the origin masks : 0.8887951374053955 time for calcul the mask position with numpy : 0.04543566703796387 nb_pixel_total : 1193508 time to create 1 rle with new method : 0.3060317039489746 time for calcul the mask position with numpy : 0.006139039993286133 nb_pixel_total : 808 time to create 1 rle with old method : 0.001772165298461914 time for calcul the mask position with numpy : 0.011899471282958984 nb_pixel_total : 751334 time to create 1 rle with new method : 0.28787732124328613 time for calcul the mask position with numpy : 0.0065839290618896484 nb_pixel_total : 107179 time to create 1 rle with old method : 0.11545872688293457 time for calcul the mask position with numpy : 0.006529808044433594 nb_pixel_total : 7888 time to create 1 rle with old method : 0.008534908294677734 time for calcul the mask position with numpy : 0.006443977355957031 nb_pixel_total : 12883 time to create 1 rle with old method : 0.013446569442749023 create new chi : 0.8233757019042969 time to delete rle : 0.0007140636444091797 batch 1 Loaded 12 chid ids of type : 3594 +++++Number RLEs to save : 4901 TO DO : save crop sub photo not yet done ! save time : 0.2913813591003418 nb_obj : 3 nb_hashtags : 1 time to prepare the origin masks : 0.10639619827270508 time for calcul the mask position with numpy : 0.016465425491333008 nb_pixel_total : 1280696 time to create 1 rle with new method : 0.030898332595825195 time for calcul the mask position with numpy : 0.006182670593261719 nb_pixel_total : 12829 time to create 1 rle with old method : 0.014000177383422852 time for calcul the mask position with numpy : 0.0062503814697265625 nb_pixel_total : 15770 time to create 1 rle with old method : 0.017096996307373047 time for calcul the mask position with numpy : 0.012307882308959961 nb_pixel_total : 764305 time to create 1 rle with new method : 0.0290377140045166 create new chi : 0.1327807903289795 time to delete rle : 0.0005540847778320312 batch 1 Loaded 7 chid ids of type : 3594 +++Number RLEs to save : 3688 TO DO : save crop sub photo not yet done ! save time : 0.22174859046936035 nb_obj : 2 nb_hashtags : 1 time to prepare the origin masks : 0.06850004196166992 time for calcul the mask position with numpy : 0.04551196098327637 nb_pixel_total : 2034488 time to create 1 rle with new method : 0.25479769706726074 time for calcul the mask position with numpy : 0.006319761276245117 nb_pixel_total : 7927 time to create 1 rle with old method : 0.008384227752685547 time for calcul the mask position with numpy : 0.005943775177001953 nb_pixel_total : 31185 time to create 1 rle with old method : 0.032448768615722656 create new chi : 0.3616211414337158 time to delete rle : 0.00034737586975097656 batch 1 Loaded 5 chid ids of type : 3594 ++Number RLEs to save : 1776 TO DO : save crop sub photo not yet done ! save time : 0.1248924732208252 map_output_result : {1374568308: (0.0, 'Should be the crop_list due to order', 0), 1374568307: (0.0, 'Should be the crop_list due to order', 0), 1374568306: (0.0, 'Should be the crop_list due to order', 0), 1374568304: (0.0, 'Should be the crop_list due to order', 0), 1374568299: (0.0, 'Should be the crop_list due to order', 0), 1374568262: (0.0, 'Should be the crop_list due to order', 0), 1374568261: (0.0, 'Should be the crop_list due to order', 0), 1374568259: (0.0, 'Should be the crop_list due to order', 0.0), 1374568258: (0.0, 'Should be the crop_list due to order', 0), 1374568255: (0.0, 'Should be the crop_list due to order', 0), 1374568252: (0.0, 'Should be the crop_list due to order', 0), 1374568225: (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 [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] Looping around the photos to save general results len do output : 12 /1374568308.Didn't retrieve data . /1374568307.Didn't retrieve data . /1374568306.Didn't retrieve data . /1374568304.Didn't retrieve data . /1374568299.Didn't retrieve data . /1374568262.Didn't retrieve data . /1374568261.Didn't retrieve data . /1374568259.Didn't retrieve data . /1374568258.Didn't retrieve data . /1374568255.Didn't retrieve data . /1374568252.Didn't retrieve data . /1374568225.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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 36 time used for this insertion : 0.012714862823486328 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.142238855361938 time spend to save output : 0.013151407241821289 total time spend for step 3 : 12.15539026260376 step4:ventilate_hashtags_in_portfolio Thu Jul 31 14:51:50 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 25543232 get user id for portfolio 25543232 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`=25543232 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('metal','papier','mal_croppe','background','pehd','pet_fonce','flou','environnement','carton','pet_clair','autre')) AND mptpi.`min_score`=0.5 To do Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") Catched exception ! Connect or reconnect ! (1064, "You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ')\n and cspi.crop_hashtag_id = chi.id' at line 3") To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25543232 AND mptpi.`type`=3594 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('metal','papier','mal_croppe','background','pehd','pet_fonce','flou','environnement','carton','pet_clair','autre')) AND mptpi.`min_score`=0.5 To do lien utilise dans velours : https://www.fotonower.com/velours/25544981,25544982,25544983,25544984,25544985,25544986,25544987,25544988,25544989,25544990,25544991?tags=flou,metal,environnement,autre,papier,carton,pet_fonce,mal_croppe,background,pehd,pet_clair Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] Looping around the photos to save general results len do output : 1 /25543232. 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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 time used for this insertion : 0.015273809432983398 save_final save missing photos in datou_result : time spend for datou_step_exec : 1.3991649150848389 time spend to save output : 0.015599250793457031 total time spend for step 4 : 1.414764165878296 step5:final Thu Jul 31 14:51:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! 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 : {1374568308: ('0.19138800784959636',), 1374568307: ('0.19138800784959636',), 1374568306: ('0.19138800784959636',), 1374568304: ('0.19138800784959636',), 1374568299: ('0.19138800784959636',), 1374568262: ('0.19138800784959636',), 1374568261: ('0.19138800784959636',), 1374568259: ('0.19138800784959636',), 1374568258: ('0.19138800784959636',), 1374568255: ('0.19138800784959636',), 1374568252: ('0.19138800784959636',), 1374568225: ('0.19138800784959636',)} new output for save of step final : {1374568308: ('0.19138800784959636',), 1374568307: ('0.19138800784959636',), 1374568306: ('0.19138800784959636',), 1374568304: ('0.19138800784959636',), 1374568299: ('0.19138800784959636',), 1374568262: ('0.19138800784959636',), 1374568261: ('0.19138800784959636',), 1374568259: ('0.19138800784959636',), 1374568258: ('0.19138800784959636',), 1374568255: ('0.19138800784959636',), 1374568252: ('0.19138800784959636',), 1374568225: ('0.19138800784959636',)} [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] Looping around the photos to save general results len do output : 12 /1374568308.Didn't retrieve data . /1374568307.Didn't retrieve data . /1374568306.Didn't retrieve data . /1374568304.Didn't retrieve data . /1374568299.Didn't retrieve data . /1374568262.Didn't retrieve data . /1374568261.Didn't retrieve data . /1374568259.Didn't retrieve data . /1374568258.Didn't retrieve data . /1374568255.Didn't retrieve data . /1374568252.Didn't retrieve data . /1374568225.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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 36 time used for this insertion : 0.013225555419921875 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.12579083442687988 time spend to save output : 0.013854742050170898 total time spend for step 5 : 0.13964557647705078 step6:blur_detection Thu Jul 31 14:51:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection toutes les photos sont déjà traitées, on saute les calculs Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 12 time used for this insertion : 0.00885319709777832 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 12 time used for this insertion : 0.00895380973815918 save missing photos in datou_result : time spend for datou_step_exec : 0.022293567657470703 time spend to save output : 0.022382020950317383 total time spend for step 6 : 0.044675588607788086 step7:brightness Thu Jul 31 14:51:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness toutes les photos sont déjà traitées, on saute les calculs Inside saveOutput : final : False verbose : 0 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 12 time used for this insertion : 0.00895833969116211 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 12 time used for this insertion : 0.00895547866821289 save missing photos in datou_result : time spend for datou_step_exec : 0.02878713607788086 time spend to save output : 0.02226996421813965 total time spend for step 7 : 0.05105710029602051 step8:velours_tree Thu Jul 31 14:51:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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 : 0.07880449295043945 time spend to save output : 3.266334533691406e-05 total time spend for step 8 : 0.07883715629577637 step9:send_mail_cod Thu Jul 31 14:51:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 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_P25543232_31-07-2025_14_51_52.pdf 25544981 imagette255449811753966312 25544982 imagette255449821753966312 25544984 change filename to text .change filename to text .change filename to text .imagette255449841753966312 25544985 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette255449851753966312 25544986 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 .imagette255449861753966313 25544987 imagette255449871753966314 25544988 imagette255449881753966314 25544989 imagette255449891753966314 25544990 imagette255449901753966314 25544991 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette255449911753966314 SELECT h.hashtag,pcr.value FROM MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h where pcr.portfolio_id=25543232 and hashtag_type = 3594 and pcr.hashtag_id = h.hashtag_id; velour_link : https://www.fotonower.com/velours/25544981,25544982,25544983,25544984,25544985,25544986,25544987,25544988,25544989,25544990,25544991?tags=flou,metal,environnement,autre,papier,carton,pet_fonce,mal_croppe,background,pehd,pet_clair args[1374568308] : ((1374568308, -2.681490947461662, 492609224), (1374568308, 0.40470388775802674, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568307] : ((1374568307, -1.7676585485357876, 492688767), (1374568307, 0.6989882087119221, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568306] : ((1374568306, -2.3955387076088392, 492609224), (1374568306, 0.5744812680768271, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568304] : ((1374568304, -4.535261240554171, 492609224), (1374568304, 0.4850728202128862, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568299] : ((1374568299, -2.439644782928829, 492609224), (1374568299, 0.3702577390332917, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568262] : ((1374568262, -3.1294149559611046, 492609224), (1374568262, 0.5797944278342843, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568261] : ((1374568261, -2.518733668564176, 492609224), (1374568261, 0.8058194370922291, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568259] : ((1374568259, 1.1407422770763647, 492688767), (1374568259, -1.2426367423274927, 501862349), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568258] : ((1374568258, -2.3793009330507044, 492609224), (1374568258, 0.4308058775947592, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568255] : ((1374568255, -2.0216820028799822, 492609224), (1374568255, 0.3756658405612423, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568252] : ((1374568252, -2.538941200303783, 492609224), (1374568252, 0.393707125860143, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com args[1374568225] : ((1374568225, -0.7664478522454041, 492688767), (1374568225, 0.5964850091761327, 2107752395), '0.19138800784959636') We are sending mail with results at report@fotonower.com refus_total : 0.19138800784959636 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=25543232 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_P25543232_31-07-2025_14_51_52.pdf results_Auto_P25543232_31-07-2025_14_51_52.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543232_31-07-2025_14_51_52.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','25543232','results_Auto_P25543232_31-07-2025_14_51_52.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543232_31-07-2025_14_51_52.pdf','pdf','','0.81','0.19138800784959636') message_in_mail: Bonjour,
Veuillez trouver ci dessous les résultats du service carac on demand pour le portfolio: https://www.fotonower.com/view/25543232

https://www.fotonower.com/image?json=false&list_photos_id=1374568308
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568307
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568306
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568304
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568299
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568262
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568261
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568259
La photo est trop floue, merci de reprendre une photo.(avec le score = 1.1407422770763647)
https://www.fotonower.com/image?json=false&list_photos_id=1374568258
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568255
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568252
Bravo, la photo est bien prise.
https://www.fotonower.com/image?json=false&list_photos_id=1374568225
Bravo, la photo est bien prise.

Dans ces conditions,le taux de refus est: 19.14%
Veuillez trouver les photos des contaminants.

exemples de contaminants: autre: https://www.fotonower.com/view/25544984?limit=200
exemples de contaminants: papier: https://www.fotonower.com/view/25544985?limit=200
exemples de contaminants: carton: https://www.fotonower.com/view/25544986?limit=200
exemples de contaminants: pet_clair: https://www.fotonower.com/view/25544991?limit=200
Veuillez trouver le rapport en pdf:https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543232_31-07-2025_14_51_52.pdf.

Lien vers velours :https://www.fotonower.com/velours/25544981,25544982,25544983,25544984,25544985,25544986,25544987,25544988,25544989,25544990,25544991?tags=flou,metal,environnement,autre,papier,carton,pet_fonce,mal_croppe,background,pehd,pet_clair.


L'équipe Fotonower 202 b'' Server: nginx Date: Thu, 31 Jul 2025 12:51:59 GMT Content-Length: 0 Connection: close X-Message-Id: lF-sWM3oT5Cdlp1RL-LIWw 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 [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] 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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 12 time used for this insertion : 0.013658761978149414 save_final save missing photos in datou_result : time spend for datou_step_exec : 6.550791263580322 time spend to save output : 0.013860702514648438 total time spend for step 9 : 6.564651966094971 step10:split_time_score Thu Jul 31 14:51:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed 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'}] (('10', 52),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 31072025 25543232 Nombre de photos uploadées : 52 / 23040 (0%) 31072025 25543232 Nombre de photos taguées (types de déchets): 0 / 52 (0%) 31072025 25543232 Nombre de photos taguées (volume) : 0 / 52 (0%) elapsed_time : load_data_split_time_score 1.430511474609375e-06 elapsed_time : order_list_meta_photo_and_scores 5.245208740234375e-06 ???????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0022237300872802734 Catched exception ! Connect or reconnect ! Catched exception ! Connect or reconnect ! elapsed_time : insert_dashboard_record_day_entry 0.21064400672912598 We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps Qualite : 0.1288892103909465 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25530216_31-07-2025_08_21_35.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25530216 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25530216 AND mptpi.`type`=3594 To do Qualite : 0.0400941679526749 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532093_31-07-2025_09_51_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532093 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25532093 AND mptpi.`type`=3594 To do Qualite : 0.017316454475308645 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532109_31-07-2025_09_41_23.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532109 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25532109 AND mptpi.`type`=3594 To do Qualite : 0.045261622299382735 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25532112_31-07-2025_09_31_06.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25532112 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25532112 AND mptpi.`type`=3594 To do Qualite : 0.10603395061728398 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25537191_31-07-2025_11_41_29.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25537191 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25537191 AND mptpi.`type`=3594 To do Qualite : 0.1775103777154558 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543232_31-07-2025_14_51_52.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543232 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`=25543232 AND mptpi.`type`=3594 To do Qualite : 0.2067458164544753 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543235_31-07-2025_14_31_40.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543235 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`=25543235 AND mptpi.`type`=3594 To do Qualite : 0.15670513974622782 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543266_31-07-2025_14_21_39.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543266 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25543266 AND mptpi.`type`=3594 To do Qualite : 0.11439766589506177 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_Auto_P25543287_31-07-2025_14_12_54.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 25543287 order by id desc limit 1 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=25543287 AND mptpi.`type`=3594 To do NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'31072025': {'nb_upload': 52, '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 [1374568308, 1374568307, 1374568306, 1374568304, 1374568299, 1374568262, 1374568261, 1374568259, 1374568258, 1374568255, 1374568252, 1374568225] Looping around the photos to save general results len do output : 1 /25543232Didn'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, '3410768') ('3318', None, '1374568308', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568307', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568306', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568304', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568299', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568262', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568261', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568259', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568258', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568255', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568252', None, None, None, None, None, '3410768') ('3318', None, None, None, None, None, None, None, '3410768') ('3318', None, '1374568225', None, None, None, None, None, '3410768') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 time used for this insertion : 0.014209747314453125 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.8945813179016113 time spend to save output : 0.014456748962402344 total time spend for step 10 : 0.9090380668640137 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 12 set_done_treatment 45.94user 27.66system 1:35.48elapsed 77%CPU (0avgtext+0avgdata 2744672maxresident)k 519896inputs+55696outputs (45major+1495655minor)pagefaults 0swaps