Global: debug: false use_gpu: true epoch_num: 500 log_smooth_window: 20 print_batch_step: 10 save_model_dir: ./output/ch_PP-OCR_v3_det/ save_epoch_step: 100 eval_batch_step: - 0 - 400 cal_metric_during_train: false pretrained_model: null checkpoints: null save_inference_dir: null use_visualdl: false infer_img: doc/imgs_en/img_10.jpg save_res_path: ./checkpoints/det_db/predicts_db.txt distributed: true Architecture: name: DistillationModel algorithm: Distillation model_type: det Models: Student: pretrained: model_type: det algorithm: DB Transform: null Backbone: name: MobileNetV3 scale: 0.5 model_name: large disable_se: true Neck: name: RSEFPN out_channels: 96 shortcut: True Head: name: DBHead k: 50 Student2: pretrained: model_type: det algorithm: DB Transform: null Backbone: name: MobileNetV3 scale: 0.5 model_name: large disable_se: true Neck: name: RSEFPN out_channels: 96 shortcut: True Head: name: DBHead k: 50 Teacher: pretrained: freeze_params: true return_all_feats: false model_type: det algorithm: DB Backbone: name: ResNet in_channels: 3 layers: 50 Neck: name: LKPAN out_channels: 256 Head: name: DBHead kernel_list: [7,2,2] k: 50 Loss: name: CombinedLoss loss_config_list: - DistillationDilaDBLoss: weight: 1.0 model_name_pairs: - ["Student", "Teacher"] - ["Student2", "Teacher"] key: maps balance_loss: true main_loss_type: DiceLoss alpha: 5 beta: 10 ohem_ratio: 3 - DistillationDMLLoss: model_name_pairs: - ["Student", "Student2"] maps_name: "thrink_maps" weight: 1.0 model_name_pairs: ["Student", "Student2"] key: maps - DistillationDBLoss: weight: 1.0 model_name_list: ["Student", "Student2"] balance_loss: true main_loss_type: DiceLoss alpha: 5 beta: 10 ohem_ratio: 3 Optimizer: name: Adam beta1: 0.9 beta2: 0.999 lr: name: Cosine learning_rate: 0.001 warmup_epoch: 2 regularizer: name: L2 factor: 5.0e-05 PostProcess: name: DistillationDBPostProcess model_name: ["Student"] key: head_out thresh: 0.3 box_thresh: 0.6 max_candidates: 1000 unclip_ratio: 1.5 Metric: name: DistillationMetric base_metric_name: DetMetric main_indicator: hmean key: "Student" Train: dataset: name: SimpleDataSet data_dir: ./train_data/icdar2015/text_localization/ label_file_list: - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt ratio_list: [1.0] transforms: - DecodeImage: img_mode: BGR channel_first: false - DetLabelEncode: null - CopyPaste: - IaaAugment: augmenter_args: - type: Fliplr args: p: 0.5 - type: Affine args: rotate: - -10 - 10 - type: Resize args: size: - 0.5 - 3 - EastRandomCropData: size: - 960 - 960 max_tries: 50 keep_ratio: true - MakeBorderMap: shrink_ratio: 0.4 thresh_min: 0.3 thresh_max: 0.7 - MakeShrinkMap: shrink_ratio: 0.4 min_text_size: 8 - NormalizeImage: scale: 1./255. mean: - 0.485 - 0.456 - 0.406 std: - 0.229 - 0.224 - 0.225 order: hwc - ToCHWImage: null - KeepKeys: keep_keys: - image - threshold_map - threshold_mask - shrink_map - shrink_mask loader: shuffle: true drop_last: false batch_size_per_card: 8 num_workers: 4 Eval: dataset: name: SimpleDataSet data_dir: ./train_data/icdar2015/text_localization/ label_file_list: - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt transforms: - DecodeImage: # load image img_mode: BGR channel_first: False - DetLabelEncode: # Class handling label - DetResizeForTest: - NormalizeImage: scale: 1./255. mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: 'hwc' - ToCHWImage: - KeepKeys: keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] loader: shuffle: False drop_last: False batch_size_per_card: 1 # must be 1 num_workers: 2