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- Global:
- device: gpu
- epoch_num: 20
- log_smooth_window: 20
- print_batch_step: 10
- output_dir: ./output/rec/u14m_filter/crnn_ctc_long/
- 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
- save_res_path: ./output/rec/u14m_filter/predicts_crnn_ctc.txt
- use_amp: True
- Optimizer:
- name: AdamW
- lr: 0.00065 # for 4gpus bs256/gpu
- weight_decay: 0.0
- 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: CRNN
- Transform:
- Encoder:
- name: ResNet_ASTER
- Decoder:
- name: CTCDecoder
- Loss:
- name: CTCLoss
- zero_infinity: True
- PostProcess:
- name: CTCLabelDecode
- 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
- - PARSeqAugPIL:
- - CTCLabelEncode: # 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: 256
- drop_last: True
- num_workers: 4
- Eval:
- dataset:
- name: RatioDataSetTVResize
- ds_width: True
- padding: False
- base_shape: [[32, 32], [64, 32], [96, 32], [128, 32]]
- data_dir_list: [
- '../evaluation/CUTE80',
- '../evaluation/IC13_857',
- '../evaluation/IC15_1811',
- '../evaluation/IIIT5k',
- '../evaluation/SVT',
- '../evaluation/SVTP',
- ]
- transforms:
- - DecodeImagePIL: # load image
- img_mode: RGB
- - CTCLabelEncode: # Class handling label
- character_dict_path: *character_dict_path
- use_space_char: *use_space_char
- max_text_length: *max_text_length
- - KeepKeys:
- keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
- sampler:
- name: RatioSampler
- scales: [[128, 32]] # w, h
- # divide_factor: to ensure the width and height dimensions can be devided by downsampling multiple
- first_bs: 256
- fix_bs: false
- divided_factor: [4, 16] # w, h
- is_training: False
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 256
- max_ratio: 20
- num_workers: 4
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