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113 lines
2.8 KiB
YAML
113 lines
2.8 KiB
YAML
Global:
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use_gpu: True
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epoch_num: 20
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./json/rec/svtr_cppd_base/
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save_epoch_step: 1
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# evaluation is run every 2000 iterations after the 0th iteration
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eval_batch_step: [0, 2000]
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cal_metric_during_train: True
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pretrained_model:
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checkpoints:
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save_inference_dir:
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use_visualdl: False
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infer_img: doc/imgs_words_en/word_10.png
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# for data or label process
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character_dict_path:
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character_type: en
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max_text_length: 25
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infer_mode: False
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use_space_char: False
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save_res_path: ./json/rec/predicts_svtr_cppd_base.txt
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Optimizer:
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name: AdamW
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beta1: 0.9
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beta2: 0.99
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epsilon: 1.e-8
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weight_decay: 0.05
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no_weight_decay_name: norm pos_embed char_node_embed pos_node_embed char_pos_embed vis_pos_embed
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one_dim_param_no_weight_decay: True
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lr:
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name: Cosine
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learning_rate: 0.0005 # 4gpus 256bs
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warmup_epoch: 2
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Architecture:
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model_type: rec
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algorithm: CPPD
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Transform:
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Backbone:
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name: SVTRNet
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img_size: [32, 100]
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patch_merging: 'Conv'
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embed_dim: [128, 256, 384]
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depth: [6, 6, 4]
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num_heads: [4, 8, 12]
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mixer: ['Conv','Conv','Conv','Conv','Conv','Conv', 'Conv','Conv', 'Global','Global','Global','Global','Global','Global','Global','Global','Global','Global']
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local_mixer: [[5, 5], [5, 5], [5, 5]]
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last_stage: False
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prenorm: True
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Head:
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name: CPPDHead
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dim: 384
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vis_seq: 50
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num_layer: 3
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Loss:
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name: CPPDLoss
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ignore_index: &ignore_index 100 # must be greater than the number of character classes
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smoothing: True
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sideloss_weight: 1.0
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PostProcess:
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name: CPPDLabelDecode
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Metric:
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name: RecMetric
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main_indicator: acc
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Train:
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dataset:
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name: LMDBDataSet
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data_dir: ./train_data/data_lmdb_release/training/
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- CPPDLabelEncode: # Class handling label
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ignore_index: *ignore_index
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- SVTRRecResizeImg:
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image_shape: [3, 32, 100]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', 'label_node', 'length'] # dataloader will return list in this order
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loader:
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shuffle: True
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batch_size_per_card: 256
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drop_last: True
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num_workers: 8
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Eval:
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dataset:
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name: LMDBDataSet
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data_dir: ./train_data/data_lmdb_release/evaluation/
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- CPPDLabelEncode: # Class handling label
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ignore_index: *ignore_index
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- SVTRRecResizeImg:
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image_shape: [3, 32, 100]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', 'label_node','length'] # dataloader will return list in this order
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loader:
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shuffle: False
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drop_last: False
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batch_size_per_card: 256
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num_workers: 2
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