update multi rec model (#6142)
* update multi rec model * fix pdserving for det * rename multi config * update ch_rec_slim linkpull/6145/head
parent
91d2802775
commit
f3c35aa1e6
deploy/pdserving
doc/doc_ch
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@ -0,0 +1,131 @@
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Global:
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debug: false
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use_gpu: true
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epoch_num: 500
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/v3_arabic_mobile
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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/dict/arabic_dict.txt
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max_text_length: &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_ppocrv3_arabic.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: Cosine
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learning_rate: 0.001
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warmup_epoch: 5
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regularizer:
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name: L2
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factor: 3.0e-05
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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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Backbone:
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name: MobileNetV1Enhance
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scale: 0.5
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last_conv_stride: [1, 2]
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last_pool_type: avg
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Head:
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name: MultiHead
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head_list:
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- CTCHead:
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Neck:
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name: svtr
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dims: 64
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depth: 2
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hidden_dims: 120
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use_guide: True
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Head:
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fc_decay: 0.00001
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- SARHead:
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enc_dim: 512
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max_text_length: *max_text_length
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Loss:
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name: MultiLoss
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loss_config_list:
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- CTCLoss:
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- SARLoss:
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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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ignore_space: False
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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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ext_op_transform_idx: 1
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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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- RecConAug:
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prob: 0.5
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ext_data_num: 2
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image_shape: [48, 320, 3]
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- RecAug:
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- MultiLabelEncode:
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- RecResizeImg:
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image_shape: [3, 48, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_sar
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- length
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- valid_ratio
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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: 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
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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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- MultiLabelEncode:
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- RecResizeImg:
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image_shape: [3, 48, 320]
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- KeepKeys:
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keep_keys:
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- image
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- label_ctc
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- label_sar
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- length
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- valid_ratio
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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: 4
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@ -0,0 +1,131 @@
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Global:
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debug: false
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use_gpu: true
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epoch_num: 500
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/v3_chinese_cht_mobile
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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/dict/chinese_cht_dict.txt
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max_text_length: &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_ppocrv3_chinese_cht.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: Cosine
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learning_rate: 0.001
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warmup_epoch: 5
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regularizer:
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name: L2
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factor: 3.0e-05
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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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Backbone:
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name: MobileNetV1Enhance
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scale: 0.5
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last_conv_stride: [1, 2]
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last_pool_type: avg
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Head:
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name: MultiHead
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head_list:
|
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- CTCHead:
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Neck:
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name: svtr
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dims: 64
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depth: 2
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hidden_dims: 120
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use_guide: True
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Head:
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fc_decay: 0.00001
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- SARHead:
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enc_dim: 512
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max_text_length: *max_text_length
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Loss:
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name: MultiLoss
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loss_config_list:
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- CTCLoss:
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- SARLoss:
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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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ignore_space: False
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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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ext_op_transform_idx: 1
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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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- RecConAug:
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prob: 0.5
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ext_data_num: 2
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image_shape: [48, 320, 3]
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- RecAug:
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- MultiLabelEncode:
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||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
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- KeepKeys:
|
||||
keep_keys:
|
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- image
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||||
- label_ctc
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- label_sar
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- length
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- valid_ratio
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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: 4
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||||
Eval:
|
||||
dataset:
|
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name: SimpleDataSet
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data_dir: ./train_data
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||||
label_file_list:
|
||||
- ./train_data/val_list.txt
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||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
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||||
channel_first: false
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||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
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||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
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||||
- length
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||||
- valid_ratio
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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: 4
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@ -0,0 +1,131 @@
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|||
Global:
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debug: false
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use_gpu: true
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epoch_num: 500
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/v3_cyrillic_mobile
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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/dict/cyrillic_dict.txt
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max_text_length: &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_ppocrv3_cyrillic.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: Cosine
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learning_rate: 0.001
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warmup_epoch: 5
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regularizer:
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name: L2
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factor: 3.0e-05
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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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Backbone:
|
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name: MobileNetV1Enhance
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scale: 0.5
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last_conv_stride: [1, 2]
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last_pool_type: avg
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Head:
|
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name: MultiHead
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head_list:
|
||||
- CTCHead:
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Neck:
|
||||
name: svtr
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dims: 64
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||||
depth: 2
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||||
hidden_dims: 120
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use_guide: True
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Head:
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fc_decay: 0.00001
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- SARHead:
|
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enc_dim: 512
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max_text_length: *max_text_length
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|
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Loss:
|
||||
name: MultiLoss
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||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
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||||
|
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PostProcess:
|
||||
name: CTCLabelDecode
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||||
|
||||
Metric:
|
||||
name: RecMetric
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main_indicator: acc
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ignore_space: False
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||||
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||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
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||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
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||||
label_file_list:
|
||||
- ./train_data/train_list.txt
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||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
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||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
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||||
image_shape: [48, 320, 3]
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||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
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||||
- length
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||||
- valid_ratio
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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: 4
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Eval:
|
||||
dataset:
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name: SimpleDataSet
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data_dir: ./train_data
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||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
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channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
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||||
loader:
|
||||
shuffle: false
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drop_last: false
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batch_size_per_card: 128
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num_workers: 4
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@ -0,0 +1,131 @@
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|||
Global:
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||||
debug: false
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use_gpu: true
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epoch_num: 500
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/v3_devanagari_mobile
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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:
|
||||
checkpoints:
|
||||
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/dict/devanagari_dict.txt
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max_text_length: &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_ppocrv3_devanagari.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: Cosine
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learning_rate: 0.001
|
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warmup_epoch: 5
|
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regularizer:
|
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name: L2
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factor: 3.0e-05
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|
||||
|
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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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Backbone:
|
||||
name: MobileNetV1Enhance
|
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scale: 0.5
|
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last_conv_stride: [1, 2]
|
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last_pool_type: avg
|
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Head:
|
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name: MultiHead
|
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head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
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dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
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use_guide: True
|
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Head:
|
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fc_decay: 0.00001
|
||||
- SARHead:
|
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enc_dim: 512
|
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max_text_length: *max_text_length
|
||||
|
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Loss:
|
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name: MultiLoss
|
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loss_config_list:
|
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- CTCLoss:
|
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- SARLoss:
|
||||
|
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PostProcess:
|
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name: CTCLabelDecode
|
||||
|
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Metric:
|
||||
name: RecMetric
|
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main_indicator: acc
|
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ignore_space: False
|
||||
|
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Train:
|
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dataset:
|
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name: SimpleDataSet
|
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data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
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channel_first: false
|
||||
- RecConAug:
|
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prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
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@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
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print_batch_step: 10
|
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save_model_dir: ./output/v3_japan_mobile
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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
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/japan_dict.txt
|
||||
max_text_length: &max_text_length 25
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infer_mode: false
|
||||
use_space_char: true
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||||
distributed: true
|
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save_res_path: ./output/rec/predicts_ppocrv3_japan.txt
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|
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|
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Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
||||
print_batch_step: 10
|
||||
save_model_dir: ./output/v3_ka_mobile
|
||||
save_epoch_step: 3
|
||||
eval_batch_step: [0, 2000]
|
||||
cal_metric_during_train: true
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/ka_dict.txt
|
||||
max_text_length: &max_text_length 25
|
||||
infer_mode: false
|
||||
use_space_char: true
|
||||
distributed: true
|
||||
save_res_path: ./output/rec/predicts_ppocrv3_ka.txt
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
||||
print_batch_step: 10
|
||||
save_model_dir: ./output/v3_korean_mobile
|
||||
save_epoch_step: 3
|
||||
eval_batch_step: [0, 2000]
|
||||
cal_metric_during_train: true
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/korean_dict.txt
|
||||
max_text_length: &max_text_length 25
|
||||
infer_mode: false
|
||||
use_space_char: true
|
||||
distributed: true
|
||||
save_res_path: ./output/rec/predicts_ppocrv3_korean.txt
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
||||
print_batch_step: 10
|
||||
save_model_dir: ./output/v3_latin_mobile
|
||||
save_epoch_step: 3
|
||||
eval_batch_step: [0, 2000]
|
||||
cal_metric_during_train: true
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/latin_dict.txt
|
||||
max_text_length: &max_text_length 25
|
||||
infer_mode: false
|
||||
use_space_char: true
|
||||
distributed: true
|
||||
save_res_path: ./output/rec/predicts_ppocrv3_latin.txt
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
||||
print_batch_step: 10
|
||||
save_model_dir: ./output/v3_ta_mobile
|
||||
save_epoch_step: 3
|
||||
eval_batch_step: [0, 2000]
|
||||
cal_metric_during_train: true
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/ta_dict.txt
|
||||
max_text_length: &max_text_length 25
|
||||
infer_mode: false
|
||||
use_space_char: true
|
||||
distributed: true
|
||||
save_res_path: ./output/rec/predicts_ppocrv3_ta.txt
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -0,0 +1,131 @@
|
|||
Global:
|
||||
debug: false
|
||||
use_gpu: true
|
||||
epoch_num: 500
|
||||
log_smooth_window: 20
|
||||
print_batch_step: 10
|
||||
save_model_dir: ./output/v3_te_mobile
|
||||
save_epoch_step: 3
|
||||
eval_batch_step: [0, 2000]
|
||||
cal_metric_during_train: true
|
||||
pretrained_model:
|
||||
checkpoints:
|
||||
save_inference_dir:
|
||||
use_visualdl: false
|
||||
infer_img: doc/imgs_words/ch/word_1.jpg
|
||||
character_dict_path: ppocr/utils/dict/te_dict.txt
|
||||
max_text_length: &max_text_length 25
|
||||
infer_mode: false
|
||||
use_space_char: true
|
||||
distributed: true
|
||||
save_res_path: ./output/rec/predicts_ppocrv3_te.txt
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Adam
|
||||
beta1: 0.9
|
||||
beta2: 0.999
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.001
|
||||
warmup_epoch: 5
|
||||
regularizer:
|
||||
name: L2
|
||||
factor: 3.0e-05
|
||||
|
||||
|
||||
Architecture:
|
||||
model_type: rec
|
||||
algorithm: SVTR
|
||||
Transform:
|
||||
Backbone:
|
||||
name: MobileNetV1Enhance
|
||||
scale: 0.5
|
||||
last_conv_stride: [1, 2]
|
||||
last_pool_type: avg
|
||||
Head:
|
||||
name: MultiHead
|
||||
head_list:
|
||||
- CTCHead:
|
||||
Neck:
|
||||
name: svtr
|
||||
dims: 64
|
||||
depth: 2
|
||||
hidden_dims: 120
|
||||
use_guide: True
|
||||
Head:
|
||||
fc_decay: 0.00001
|
||||
- SARHead:
|
||||
enc_dim: 512
|
||||
max_text_length: *max_text_length
|
||||
|
||||
Loss:
|
||||
name: MultiLoss
|
||||
loss_config_list:
|
||||
- CTCLoss:
|
||||
- SARLoss:
|
||||
|
||||
PostProcess:
|
||||
name: CTCLabelDecode
|
||||
|
||||
Metric:
|
||||
name: RecMetric
|
||||
main_indicator: acc
|
||||
ignore_space: False
|
||||
|
||||
Train:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data/
|
||||
ext_op_transform_idx: 1
|
||||
label_file_list:
|
||||
- ./train_data/train_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- RecConAug:
|
||||
prob: 0.5
|
||||
ext_data_num: 2
|
||||
image_shape: [48, 320, 3]
|
||||
- RecAug:
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: true
|
||||
batch_size_per_card: 128
|
||||
drop_last: true
|
||||
num_workers: 4
|
||||
Eval:
|
||||
dataset:
|
||||
name: SimpleDataSet
|
||||
data_dir: ./train_data
|
||||
label_file_list:
|
||||
- ./train_data/val_list.txt
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
img_mode: BGR
|
||||
channel_first: false
|
||||
- MultiLabelEncode:
|
||||
- RecResizeImg:
|
||||
image_shape: [3, 48, 320]
|
||||
- KeepKeys:
|
||||
keep_keys:
|
||||
- image
|
||||
- label_ctc
|
||||
- label_sar
|
||||
- length
|
||||
- valid_ratio
|
||||
loader:
|
||||
shuffle: false
|
||||
drop_last: false
|
||||
batch_size_per_card: 128
|
||||
num_workers: 4
|
|
@ -37,7 +37,7 @@ op:
|
|||
model_config: ./ppocr_det_v3_serving
|
||||
|
||||
#Fetch结果列表,以client_config中fetch_var的alias_name为准
|
||||
fetch_list: ["save_infer_model/scale_0.tmp_1"]
|
||||
fetch_list: ["sigmoid_0.tmp_0"]
|
||||
|
||||
#计算硬件ID,当devices为""或不写时为CPU预测;当devices为"0", "0,1,2"时为GPU预测,表示使用的GPU卡
|
||||
devices: "0"
|
||||
|
|
|
@ -56,7 +56,7 @@ class DetOp(Op):
|
|||
return {"x": det_img[np.newaxis, :].copy()}, False, None, ""
|
||||
|
||||
def postprocess(self, input_dicts, fetch_dict, data_id, log_id):
|
||||
det_out = fetch_dict["save_infer_model/scale_0.tmp_1"]
|
||||
det_out = fetch_dict["sigmoid_0.tmp_0"]
|
||||
ratio_list = [
|
||||
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
|
||||
]
|
||||
|
|
|
@ -55,7 +55,7 @@ class DetOp(Op):
|
|||
return {"x": det_img[np.newaxis, :].copy()}, False, None, ""
|
||||
|
||||
def postprocess(self, input_dicts, fetch_dict, data_id, log_id):
|
||||
det_out = fetch_dict["save_infer_model/scale_0.tmp_1"]
|
||||
det_out = fetch_dict["sigmoid_0.tmp_0"]
|
||||
ratio_list = [
|
||||
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
|
||||
]
|
||||
|
|
|
@ -81,7 +81,7 @@ PaddleOCR提供的可下载模型包括`推理模型`、`训练模型`、`预训
|
|||
|
||||
|模型名称|模型简介|配置文件|推理模型大小|下载地址|
|
||||
| --- | --- | --- | --- | --- |
|
||||
|ch_PP-OCRv3_rec_slim |【最新】slim量化版超轻量模型,支持中英文、数字识别|[ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml)| 4.9M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/ch/ch_PP-OCRv3_rec_slim_train.tar) / [slim模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.nb) |
|
||||
|ch_PP-OCRv3_rec_slim |【最新】slim量化版超轻量模型,支持中英文、数字识别|[ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml)| 4.9M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_train.tar) / [slim模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_slim_infer.nb) |
|
||||
|ch_PP-OCRv3_rec|【最新】原始超轻量模型,支持中英文、数字识别|[ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml)| 12.4M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
|
||||
|ch_PP-OCRv2_rec_slim| slim量化版超轻量模型,支持中英文、数字识别|[ch_PP-OCRv2_rec.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec.yml)| 9M |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_slim_quant_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_slim_quant_train.tar) |
|
||||
|ch_PP-OCRv2_rec| 原始超轻量模型,支持中英文、数字识别|[ch_PP-OCRv2_rec_distillation.yml](../../configs/rec/ch_PP-OCRv2/ch_PP-OCRv2_rec_distillation.yml)|8.5M|[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_train.tar) |
|
||||
|
@ -96,7 +96,7 @@ PaddleOCR提供的可下载模型包括`推理模型`、`训练模型`、`预训
|
|||
|
||||
|模型名称|模型简介|配置文件|推理模型大小|下载地址|
|
||||
| --- | --- | --- | --- | --- |
|
||||
|en_PP-OCRv3_rec_slim |【最新】slim量化版超轻量模型,支持英文、数字识别 | [en_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml)| - |[推理模型(coming soon)](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_infer.tar) / [训练模型(coming soon)](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_train.tar) / [slim模型(coming soon)](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_infer.nb) |
|
||||
|en_PP-OCRv3_rec_slim |【最新】slim量化版超轻量模型,支持英文、数字识别 | [en_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml)| - |[推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_train.tar) / [slim模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_slim_infer.nb) |
|
||||
|ch_PP-OCRv3_rec |【最新】原始超轻量模型,支持英文、数字识别|[en_PP-OCRv3_rec.yml](../../configs/rec/en_PP-OCRv3/en_PP-OCRv3_rec.yml)| 9.6M | [推理模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
|
||||
|en_number_mobile_slim_v2.0_rec|slim裁剪量化版超轻量模型,支持英文、数字识别|[rec_en_number_lite_train.yml](../../configs/rec/multi_language/rec_en_number_lite_train.yml)| 2.7M | [推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/en_number_mobile_v2.0_rec_slim_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/en_number_mobile_v2.0_rec_slim_train.tar) |
|
||||
|en_number_mobile_v2.0_rec|原始超轻量模型,支持英文、数字识别|[rec_en_number_lite_train.yml](../../configs/rec/multi_language/rec_en_number_lite_train.yml)|2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_train.tar) |
|
||||
|
@ -107,18 +107,17 @@ PaddleOCR提供的可下载模型包括`推理模型`、`训练模型`、`预训
|
|||
|
||||
|模型名称|字典文件|模型简介|配置文件|推理模型大小|下载地址|
|
||||
| --- | --- | --- | --- |--- | --- |
|
||||
| french_mobile_v2.0_rec | ppocr/utils/dict/french_dict.txt |法文识别|[rec_french_lite_train.yml](../../configs/rec/multi_language/rec_french_lite_train.yml)|2.65M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_train.tar) |
|
||||
| german_mobile_v2.0_rec | ppocr/utils/dict/german_dict.txt |德文识别|[rec_german_lite_train.yml](../../configs/rec/multi_language/rec_german_lite_train.yml)|2.65M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_train.tar) |
|
||||
| korean_mobile_v2.0_rec | ppocr/utils/dict/korean_dict.txt |韩文识别|[rec_korean_lite_train.yml](../../configs/rec/multi_language/rec_korean_lite_train.yml)|3.9M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_train.tar) |
|
||||
| japan_mobile_v2.0_rec | ppocr/utils/dict/japan_dict.txt |日文识别|[rec_japan_lite_train.yml](../../configs/rec/multi_language/rec_japan_lite_train.yml)|4.23M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_train.tar) |
|
||||
| chinese_cht_mobile_v2.0_rec | ppocr/utils/dict/chinese_cht_dict.txt | 中文繁体识别|rec_chinese_cht_lite_train.yml|5.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_train.tar) |
|
||||
| te_mobile_v2.0_rec | ppocr/utils/dict/te_dict.txt | 泰卢固文识别|rec_te_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_train.tar) |
|
||||
| ka_mobile_v2.0_rec | ppocr/utils/dict/ka_dict.txt |卡纳达文识别|rec_ka_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_train.tar) |
|
||||
| ta_mobile_v2.0_rec | ppocr/utils/dict/ta_dict.txt |泰米尔文识别|rec_ta_lite_train.yml|2.63M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_train.tar) |
|
||||
| latin_mobile_v2.0_rec | ppocr/utils/dict/latin_dict.txt | 拉丁文识别 | [rec_latin_lite_train.yml](../../configs/rec/multi_language/rec_latin_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_train.tar) |
|
||||
| arabic_mobile_v2.0_rec | ppocr/utils/dict/arabic_dict.txt | 阿拉伯字母 | [rec_arabic_lite_train.yml](../../configs/rec/multi_language/rec_arabic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_train.tar) |
|
||||
| cyrillic_mobile_v2.0_rec | ppocr/utils/dict/cyrillic_dict.txt | 斯拉夫字母 | [rec_cyrillic_lite_train.yml](../../configs/rec/multi_language/rec_cyrillic_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_train.tar) |
|
||||
| devanagari_mobile_v2.0_rec | ppocr/utils/dict/devanagari_dict.txt |梵文字母 | [rec_devanagari_lite_train.yml](../../configs/rec/multi_language/rec_devanagari_lite_train.yml) |2.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_train.tar) |
|
||||
| korean_PP-OCRv3_rec | ppocr/utils/dict/korean_dict.txt |韩文识别|[korean_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/korean_PP-OCRv3_rec.yml)|11M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_PP-OCRv3_rec_train.tar) |
|
||||
| japan_PP-OCRv3_rec | ppocr/utils/dict/japan_dict.txt |日文识别|[japan_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/japan_PP-OCRv3_rec.yml)|11M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_PP-OCRv3_rec_train.tar) |
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| chinese_cht_PP-OCRv3_rec | ppocr/utils/dict/chinese_cht_dict.txt | 中文繁体识别|[chinese_cht_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/chinese_cht_PP-OCRv3_rec.yml)|12M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_PP-OCRv3_rec_train.tar) |
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| te_PP-OCRv3_rec | ppocr/utils/dict/te_dict.txt | 泰卢固文识别|[te_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/te_PP-OCRv3_rec.yml)|9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_PP-OCRv3_rec_train.tar) |
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| ka_PP-OCRv3_rec | ppocr/utils/dict/ka_dict.txt |卡纳达文识别|[ka_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/ka_PP-OCRv3_rec.yml)|9.9M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_PP-OCRv3_rec_train.tar) |
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| ta_PP-OCRv3_rec | ppocr/utils/dict/ta_dict.txt |泰米尔文识别|[ta_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/ta_PP-OCRv3_rec.yml)|9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_PP-OCRv3_rec_train.tar) |
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| latin_PP-OCRv3_rec | ppocr/utils/dict/latin_dict.txt | 拉丁文识别 | [latin_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/latin_PP-OCRv3_rec.yml) |9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_PP-OCRv3_rec_train.tar) |
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| arabic_PP-OCRv3_rec | ppocr/utils/dict/arabic_dict.txt | 阿拉伯字母 | [arabic_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/rec_arabic_lite_train.yml) |9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_PP-OCRv3_rec_train.tar) |
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| cyrillic_PP-OCRv3_rec | ppocr/utils/dict/cyrillic_dict.txt | 斯拉夫字母 | [cyrillic_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/cyrillic_PP-OCRv3_rec.yml) |9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_PP-OCRv3_rec_train.tar) |
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| devanagari_PP-OCRv3_rec | ppocr/utils/dict/devanagari_dict.txt |梵文字母 | [devanagari_PP-OCRv3_rec.yml](../../configs/rec/PP-OCRv3/multi_language/devanagari_PP-OCRv3_rec.yml) |9.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_PP-OCRv3_rec_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_PP-OCRv3_rec_train.tar) |
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更多支持语种请参考: [多语言模型](./multi_languages.md)
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Reference in New Issue