Global: device: gpu epoch_num: 20 log_smooth_window: 20 print_batch_step: 10 output_dir: ./output/rec/u14m_filter/vit_parseq/ eval_epoch_step: [0, 1] eval_batch_step: [0, 500] cal_metric_during_train: True pretrained_model: checkpoints: use_tensorboard: false infer_img: # for data or label process character_dict_path: &character_dict_path ./tools/utils/EN_symbol_dict.txt max_text_length: &max_text_length 25 use_space_char: &use_space_char False use_amp: True save_res_path: ./output/rec/u14m_filter/predicts_vit_parseq.txt grad_clip_val: 20 Optimizer: name: AdamW lr: 0.001485 # 2gpus 384bs/gpu weight_decay: 0. filter_bias_and_bn: False LRScheduler: name: OneCycleLR warmup_epoch: 1.5 # pct_start 0.075*20 = 1.5ep cycle_momentum: False Architecture: model_type: rec algorithm: PARSeq Transform: Encoder: name: ViT Decoder: name: PARSeqDecoder decode_ar: True refine_iters: 1 Loss: name: PARSeqLoss PostProcess: name: ARLabelDecode character_dict_path: *character_dict_path use_space_char: *use_space_char Metric: name: RecMetric main_indicator: acc is_filter: True Train: dataset: name: LMDBDataSet data_dir: ../Union14M-L-LMDB-Filtered transforms: - DecodeImagePIL: # load image img_mode: RGB - PARSeqAug: - ARLabelEncode: # Class handling label character_dict_path: *character_dict_path use_space_char: *use_space_char max_text_length: *max_text_length - RecTVResize: image_shape: [32, 128] padding: False - KeepKeys: keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order loader: shuffle: True batch_size_per_card: 384 drop_last: True num_workers: 4 Eval: dataset: name: LMDBDataSet data_dir: ../evaluation/ transforms: - DecodeImagePIL: # load image img_mode: RGB - ARLabelEncode: # Class handling label character_dict_path: *character_dict_path use_space_char: *use_space_char max_text_length: *max_text_length - RecTVResize: image_shape: [32, 128] padding: False - KeepKeys: keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order loader: shuffle: False drop_last: False batch_size_per_card: 256 num_workers: 2