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- Global:
- use_gpu: True
- epoch_num: 10
- log_smooth_window: 20
- print_batch_step: 10
- save_model_dir: ./output/rec/r45_abinet/
- save_epoch_step: 1
- # evaluation is run every 2000 iterations
- eval_batch_step: [0, 2000]
- cal_metric_during_train: True
- pretrained_model: ./pretrain_models/abinet_vl_pretrained
- checkpoints:
- save_inference_dir:
- use_visualdl: False
- infer_img: doc/imgs_words_en/word_10.png
- # for data or label process
- character_dict_path:
- character_type: en
- max_text_length: 25
- infer_mode: False
- use_space_char: False
- save_res_path: ./output/rec/predicts_abinet.txt
- Optimizer:
- name: Adam
- beta1: 0.9
- beta2: 0.99
- clip_norm: 20.0
- lr:
- name: Piecewise
- decay_epochs: [6]
- values: [0.0001, 0.00001]
- regularizer:
- name: 'L2'
- factor: 0.
- Architecture:
- model_type: rec
- algorithm: ABINet
- in_channels: 3
- Transform:
- Backbone:
- name: ResNet45
- Head:
- name: ABINetHead
- use_lang: True
- iter_size: 3
-
- Loss:
- name: CELoss
- ignore_index: &ignore_index 100 # Must be greater than the number of character classes
- PostProcess:
- name: ABINetLabelDecode
- Metric:
- name: RecMetric
- main_indicator: acc
- Train:
- dataset:
- name: LMDBDataSet
- data_dir: ./train_data/data_lmdb_release/training/
- transforms:
- - DecodeImage: # load image
- img_mode: RGB
- channel_first: False
- - ABINetRecAug:
- - ABINetLabelEncode: # Class handling label
- ignore_index: *ignore_index
- - ABINetRecResizeImg:
- image_shape: [3, 32, 128]
- - KeepKeys:
- keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
- loader:
- shuffle: True
- batch_size_per_card: 96
- drop_last: True
- num_workers: 4
- Eval:
- dataset:
- name: LMDBDataSet
- data_dir: ./train_data/data_lmdb_release/evaluation/
- transforms:
- - DecodeImage: # load image
- img_mode: RGB
- channel_first: False
- - ABINetLabelEncode: # Class handling label
- ignore_index: *ignore_index
- - ABINetRecResizeImg:
- image_shape: [3, 32, 128]
- - 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: 4
- use_shared_memory: False
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