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118
test_tipc/configs/rec_svtrnet/rec_svtrnet.yml
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118
test_tipc/configs/rec_svtrnet/rec_svtrnet.yml
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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: ./output/rec/svtr/
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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: ./output/rec/predicts_svtr_tiny.txt
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d2s_train_image_shape: [3, 64, 256]
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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: 8.e-8
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weight_decay: 0.05
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no_weight_decay_name: norm 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
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warmup_epoch: 2
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Architecture:
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model_type: rec
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algorithm: SVTR
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Transform:
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name: STN_ON
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tps_inputsize: [32, 64]
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tps_outputsize: [32, 100]
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num_control_points: 20
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tps_margins: [0.05,0.05]
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stn_activation: none
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Backbone:
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name: SVTRNet
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img_size: [32, 100]
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out_char_num: 25
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out_channels: 192
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patch_merging: 'Conv'
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embed_dim: [64, 128, 256]
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depth: [3, 6, 3]
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num_heads: [2, 4, 8]
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mixer: ['Local','Local','Local','Local','Local','Local','Global','Global','Global','Global','Global','Global']
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local_mixer: [[7, 11], [7, 11], [7, 11]]
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last_stage: True
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prenorm: false
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Neck:
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name: SequenceEncoder
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encoder_type: reshape
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Head:
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name: CTCHead
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Loss:
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name: CTCLoss
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PostProcess:
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name: CTCLabelDecode
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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: SimpleDataSet
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data_dir: ./train_data/ic15_data/
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label_file_list: ["./train_data/ic15_data/rec_gt_train.txt"]
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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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- CTCLabelEncode: # Class handling label
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- SVTRRecResizeImg:
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image_shape: [3, 64, 256]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', '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: 512
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drop_last: True
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num_workers: 4
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./train_data/ic15_data
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label_file_list: ["./train_data/ic15_data/rec_gt_test.txt"]
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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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- CTCLabelEncode: # Class handling label
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- SVTRRecResizeImg:
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image_shape: [3, 64, 256]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', '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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