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- Global:
- use_gpu: True
- epoch_num: 6
- log_smooth_window: 20
- print_batch_step: 50
- save_model_dir: ./output/rec/rec_resnet_rfl_visual/
- save_epoch_step: 1
- # evaluation is run every 5000 iterations after the 4000th iteration
- eval_batch_step: [0, 5000]
- cal_metric_during_train: False
- pretrained_model:
- checkpoints:
- save_inference_dir:
- use_visualdl: False
- infer_img: doc/imgs_words_en/word_10.png
- # for data or label process
- character_dict_path:
- max_text_length: 25
- infer_mode: False
- use_space_char: False
- save_res_path: ./output/rec/rec_resnet_rfl_visual.txt
- Optimizer:
- name: AdamW
- beta1: 0.9
- beta2: 0.999
- weight_decay: 0.0
- clip_norm_global: 5.0
- lr:
- name: Piecewise
- decay_epochs : [3, 4, 5]
- values : [0.001, 0.0003, 0.00009, 0.000027]
- Architecture:
- model_type: rec
- algorithm: RFL
- in_channels: 1
- Transform:
- name: TPS
- num_fiducial: 20
- loc_lr: 1.0
- model_name: large
- Backbone:
- name: ResNetRFL
- use_cnt: True
- use_seq: False
- Neck:
- name: RFAdaptor
- use_v2s: False
- use_s2v: False
- Head:
- name: RFLHead
- in_channels: 512
- hidden_size: 256
- batch_max_legnth: 25
- out_channels: 38
- use_cnt: True
- use_seq: False
- Loss:
- name: RFLLoss
- PostProcess:
- name: RFLLabelDecode
- Metric:
- name: CNTMetric
- main_indicator: acc
- Train:
- dataset:
- name: LMDBDataSet
- data_dir: ./train_data/data_lmdb_release/training
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - RFLLabelEncode: # Class handling label
- - RFLRecResizeImg:
- image_shape: [1, 32, 100]
- padding: false
- interpolation: 2
- - KeepKeys:
- keep_keys: ['image', 'label', 'length', 'cnt_label'] # dataloader will return list in this order
- loader:
- shuffle: True
- batch_size_per_card: 64
- drop_last: True
- num_workers: 8
- Eval:
- dataset:
- name: LMDBDataSet
- data_dir: ./train_data/data_lmdb_release/evaluation
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - RFLLabelEncode: # Class handling label
- - RFLRecResizeImg:
- image_shape: [1, 32, 100]
- padding: false
- interpolation: 2
- - KeepKeys:
- keep_keys: ['image', 'label', 'length', 'cnt_label'] # dataloader will return list in this order
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 256
- num_workers: 8
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