112 lines
2.1 KiB
YAML
112 lines
2.1 KiB
YAML
Global:
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debug: false
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use_gpu: true
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epoch_num: 800
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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_mobile_pp-OCRv2
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save_epoch_step: 3
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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/ch/word_1.jpg
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character_dict_path: ppocr/utils/ppocr_keys_v1.txt
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character_type: ch
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max_text_length: 25
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infer_mode: false
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use_space_char: true
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distributed: true
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save_res_path: ./output/rec/predicts_mobile_pp-OCRv2.txt
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Optimizer:
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name: Adam
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beta1: 0.9
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beta2: 0.999
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lr:
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name: Piecewise
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decay_epochs : [700, 800]
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values : [0.001, 0.0001]
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warmup_epoch: 5
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regularizer:
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name: L2
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factor: 2.0e-05
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Architecture:
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model_type: rec
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algorithm: CRNN
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Transform:
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Backbone:
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name: MobileNetV1Enhance
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scale: 0.5
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Neck:
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name: SequenceEncoder
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encoder_type: rnn
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hidden_size: 64
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Head:
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name: CTCHead
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mid_channels: 96
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fc_decay: 0.00002
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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/
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label_file_list:
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- ./train_data/train_list.txt
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transforms:
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- DecodeImage:
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img_mode: BGR
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channel_first: false
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- RecAug:
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- CTCLabelEncode:
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- RecResizeImg:
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image_shape: [3, 32, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label
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- length
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loader:
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shuffle: true
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batch_size_per_card: 128
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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: SimpleDataSet
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data_dir: ./train_data
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label_file_list:
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- ./train_data/val_list.txt
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transforms:
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- DecodeImage:
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img_mode: BGR
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channel_first: false
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- CTCLabelEncode:
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- RecResizeImg:
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image_shape: [3, 32, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label
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- length
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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: 128
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num_workers: 8
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