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- Global:
- use_gpu: true
- epoch_num: 500
- log_smooth_window: 20
- print_batch_step: 10
- save_model_dir: ./output/sr/sr_tsrn_transformer_strock/
- save_epoch_step: 3
- # evaluation is run every 2000 iterations
- eval_batch_step: [0, 1000]
- cal_metric_during_train: False
- pretrained_model:
- checkpoints:
- save_inference_dir: sr_output
- use_visualdl: False
- infer_img: doc/imgs_words_en/word_52.png
- # for data or label process
- character_dict_path: ./train_data/srdata/english_decomposition.txt
- max_text_length: 100
- infer_mode: False
- use_space_char: False
- save_res_path: ./output/sr/predicts_gestalt.txt
- Optimizer:
- name: Adam
- beta1: 0.5
- beta2: 0.999
- clip_norm: 0.25
- lr:
- learning_rate: 0.0001
- Architecture:
- model_type: sr
- algorithm: Gestalt
- Transform:
- name: TSRN
- STN: True
- infer_mode: False
- Loss:
- name: StrokeFocusLoss
- character_dict_path: ./train_data/srdata/english_decomposition.txt
- PostProcess:
- name: None
- Metric:
- name: SRMetric
- main_indicator: all
- Train:
- dataset:
- name: LMDBDataSetSR
- data_dir: ./train_data/srdata/train
- transforms:
- - SRResize:
- imgH: 32
- imgW: 128
- down_sample_scale: 2
- - SRLabelEncode: # Class handling label
- - KeepKeys:
- keep_keys: ['img_lr', 'img_hr', 'length', 'input_tensor', 'label'] # dataloader will return list in this order
- loader:
- shuffle: False
- batch_size_per_card: 16
- drop_last: True
- num_workers: 4
- Eval:
- dataset:
- name: LMDBDataSetSR
- data_dir: ./train_data/srdata/test
- transforms:
- - SRResize:
- imgH: 32
- imgW: 128
- down_sample_scale: 2
- - SRLabelEncode: # Class handling label
- - KeepKeys:
- keep_keys: ['img_lr', 'img_hr','length', 'input_tensor', 'label'] # dataloader will return list in this order
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 16
- num_workers: 4
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