Global: debug: false use_gpu: true epoch_num: 500 log_smooth_window: 20 print_batch_step: 10 save_model_dir: ./output/v3_arabic_mobile save_epoch_step: 3 eval_batch_step: [0, 2000] cal_metric_during_train: true pretrained_model: checkpoints: save_inference_dir: use_visualdl: false infer_img: ./doc/imgs_words/arabic/ar_2.jpg character_dict_path: ppocr/utils/dict/arabic_dict.txt max_text_length: &max_text_length 25 infer_mode: false use_space_char: true distributed: true save_res_path: ./output/rec/predicts_ppocrv3_arabic.txt Optimizer: name: Adam beta1: 0.9 beta2: 0.999 lr: name: Cosine learning_rate: 0.001 warmup_epoch: 5 regularizer: name: L2 factor: 3.0e-05 Architecture: model_type: rec algorithm: SVTR Transform: Backbone: name: MobileNetV1Enhance scale: 0.5 last_conv_stride: [1, 2] last_pool_type: avg Head: name: MultiHead head_list: - CTCHead: Neck: name: svtr dims: 64 depth: 2 hidden_dims: 120 use_guide: True Head: fc_decay: 0.00001 - SARHead: enc_dim: 512 max_text_length: *max_text_length Loss: name: MultiLoss loss_config_list: - CTCLoss: - SARLoss: PostProcess: name: CTCLabelDecode Metric: name: RecMetric main_indicator: acc ignore_space: False Train: dataset: name: SimpleDataSet data_dir: ./train_data/ ext_op_transform_idx: 1 label_file_list: - ./train_data/train_list.txt transforms: - DecodeImage: img_mode: BGR channel_first: false - RecConAug: prob: 0.5 ext_data_num: 2 image_shape: [48, 320, 3] - RecAug: - MultiLabelEncode: - RecResizeImg: image_shape: [3, 48, 320] - KeepKeys: keep_keys: - image - label_ctc - label_sar - length - valid_ratio loader: shuffle: true batch_size_per_card: 128 drop_last: true num_workers: 4 Eval: dataset: name: SimpleDataSet data_dir: ./train_data label_file_list: - ./train_data/val_list.txt transforms: - DecodeImage: img_mode: BGR channel_first: false - MultiLabelEncode: - RecResizeImg: image_shape: [3, 48, 320] - KeepKeys: keep_keys: - image - label_ctc - label_sar - length - valid_ratio loader: shuffle: false drop_last: false batch_size_per_card: 128 num_workers: 4