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- Global:
- device: gpu
- epoch_num: 20
- log_smooth_window: 20
- print_batch_step: 10
- output_dir: /share/ckpt/zhaoshuai/openocr/dptr_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: /share/ckpt/zhaoshuai/openocr/dptr_parseq/predicts_dptr_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: DPTR
- Decoder:
- name: DptrParseq
- decode_ar: True
- refine_iters: 1
- is_pretrain: True
- ORP_path: /share/ckpt/zhaoshuai/parseq/clip_background.pth
- 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: TextLMDBDataSet
- data_dir: /share/test/zhaoshuai/parseq-data/data/train/real/ArT
- transforms:
- - DPTRLabelEncode: # Class handling label
- character_dict_path: *character_dict_path
- use_space_char: *use_space_char
- max_text_length: *max_text_length
- - KeepKeys:
- keep_keys: ['clip_label', 'label'] # dataloader will return list in this order
- loader:
- shuffle: True
- batch_size_per_card: 256
- drop_last: True
- num_workers: 4
- Eval:
- dataset:
- name: TextLMDBDataSet
- data_dir: /share/test/zhaoshuai/parseq-data/data/val
- transforms:
- - DPTRLabelEncode: # Class handling label
- character_dict_path: *character_dict_path
- use_space_char: *use_space_char
- max_text_length: *max_text_length
- - KeepKeys:
- keep_keys: ['clip_label', 'label'] # dataloader will return list in this order
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 256
- num_workers: 2
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