664 lines
13 KiB
Markdown
664 lines
13 KiB
Markdown
# 识别结果
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参数基本采用默认参数，都训练 **10轮** 。
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## PP-OCRv5_server (极好)
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识别效果：**极好** ，基本都是别出来了，并且正确。
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### PP-OCRv5_server_det.yml
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```yaml
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Global:
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model_name: PP-OCRv5_server_det # To use static model for inference.
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debug: false
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use_gpu: true
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epoch_num: &epoch_num 10
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output-v5server/PP-OCRv5_server_det
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save_epoch_step: 200
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eval_batch_step:
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- 0
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- 200
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cal_metric_during_train: false
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checkpoints:
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pretrained_model: ./pretrain_models/PP-OCRv5_server_det_pretrained.pdparams
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save_inference_dir: null
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use_visualdl: false
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infer_img: doc/imgs_en/img_10.jpg
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save_res_path: ./checkpoints/det_db/predicts_db.txt
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distributed: false
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Architecture:
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model_type: det
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algorithm: DB
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Transform: null
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Backbone:
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name: PPHGNetV2_B4
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det: True
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Neck:
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name: LKPAN
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out_channels: 256
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intracl: true
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Head:
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name: PFHeadLocal
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k: 50
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mode: "large"
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Loss:
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name: DBLoss
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balance_loss: true
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main_loss_type: DiceLoss
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alpha: 5
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beta: 10
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ohem_ratio: 3
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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 #(8*8c)
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warmup_epoch: 2
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regularizer:
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name: L2
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factor: 1e-6
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PostProcess:
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name: DBPostProcess
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thresh: 0.3
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box_thresh: 0.6
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max_candidates: 1000
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unclip_ratio: 1.5
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Metric:
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name: DetMetric
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main_indicator: hmean
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Train:
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dataset:
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name: SimpleDataSet
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data_dir: ./data/input0/images #图片文件夹路径
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label_file_list:
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- ./det_train_label.txt #标签路径
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ratio_list: [1.0]
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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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- DetLabelEncode: null
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- CopyPaste: null
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- IaaAugment:
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augmenter_args:
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- type: Fliplr
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args:
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p: 0.5
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- type: Affine
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args:
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rotate:
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- -10
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- 10
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- type: Resize
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args:
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size:
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- 0.5
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- 3
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- EastRandomCropData:
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size:
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- 640
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- 640
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max_tries: 50
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keep_ratio: true
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- MakeBorderMap:
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shrink_ratio: 0.4
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thresh_min: 0.3
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thresh_max: 0.7
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total_epoch: *epoch_num
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- MakeShrinkMap:
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shrink_ratio: 0.4
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min_text_size: 8
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total_epoch: *epoch_num
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- NormalizeImage:
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scale: 1./255.
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mean:
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- 0.485
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- 0.456
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- 0.406
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std:
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- 0.229
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- 0.224
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- 0.225
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order: hwc
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- ToCHWImage: null
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- KeepKeys:
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keep_keys:
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- image
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- threshold_map
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- threshold_mask
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- shrink_map
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- shrink_mask
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loader:
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shuffle: true
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drop_last: false
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batch_size_per_card: 10
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num_workers: 1
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./data/input0/images
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label_file_list:
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- ./det_eval_label.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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- DetLabelEncode: null
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- DetResizeForTest:
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- NormalizeImage:
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scale: 1./255.
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mean:
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- 0.485
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- 0.456
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- 0.406
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std:
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- 0.229
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- 0.224
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- 0.225
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order: hwc
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- ToCHWImage: null
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- KeepKeys:
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keep_keys:
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- image
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- shape
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- polys
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- ignore_tags
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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: 1
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num_workers: 1
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profiler_options: null
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```
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### PP-OCRv5_server_rec.yml
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```yaml
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Global:
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model_name: PP-OCRv5_server_rec # To use static model for inference.
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debug: false
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use_gpu: true
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epoch_num: 10
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output-v5server/PP-OCRv5_server_rec
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save_epoch_step: 200
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eval_batch_step: [0, 200]
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cal_metric_during_train: true
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calc_epoch_interval: 1
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pretrained_model: ./pretrain_models/PP-OCRv5_server_rec_pretrained.pdparams
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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/ppocrv5_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-v5server/rec/predicts_ppocrv5.txt
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d2s_train_image_shape: [3, 48, 320]
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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: 0.0005
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warmup_epoch: 1
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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_HGNet
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Transform:
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Backbone:
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name: PPHGNetV2_B4
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text_rec: True
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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: 120
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depth: 2
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hidden_dims: 120
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kernel_size: [1, 3]
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use_guide: True
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Head:
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fc_decay: 0.00001
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- NRTRHead:
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nrtr_dim: 384
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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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- NRTRLoss:
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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: MultiScaleDataSet
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ds_width: false
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data_dir: ./RecTrainData/
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ext_op_transform_idx: 1
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label_file_list:
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- ./rec_train_label.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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- MultiLabelEncode:
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gtc_encode: NRTRLabelEncode
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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_gtc
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- length
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- valid_ratio
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sampler:
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name: MultiScaleSampler
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scales: [[320, 32], [320, 48], [320, 64]]
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first_bs: &bs 12
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fix_bs: false
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divided_factor: [8, 16] # w, h
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is_training: True
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loader:
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shuffle: true
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batch_size_per_card: 10
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drop_last: true
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num_workers: 1
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./RecEvalData/
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label_file_list:
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- ./rec_eval_label.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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gtc_encode: NRTRLabelEncode
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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_gtc
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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: 1
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num_workers: 1
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```
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## PP-OCRv5_mobile
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### PP-OCRv5_mobile_det.yml
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```yaml
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Global:
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model_name: PP-OCRv5_mobile_det # To use static model for inference.
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debug: false
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use_gpu: true
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epoch_num: &epoch_num 100
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log_smooth_window: 20
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print_batch_step: 100
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save_model_dir: ./output-v5mobile/PP-OCRv5_mobile_det
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save_epoch_step: 200
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eval_batch_step:
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- 0
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- 200
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cal_metric_during_train: false
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checkpoints:
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pretrained_model: https://paddleocr.bj.bcebos.com/pretrained/PPLCNetV3_x0_75_ocr_det.pdparams
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save_inference_dir: null
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use_visualdl: false
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infer_img: doc/imgs_en/img_10.jpg
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save_res_path: ./checkpoints/det_db/predicts_db.txt
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d2s_train_image_shape: [3, 640, 640]
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distributed: true
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Architecture:
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model_type: det
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algorithm: DB
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Transform: null
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Backbone:
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name: PPLCNetV3
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scale: 0.75
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det: True
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Neck:
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name: RSEFPN
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out_channels: 96
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shortcut: True
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Head:
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name: DBHead
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k: 50
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fix_nan: True
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Loss:
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name: DBLoss
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balance_loss: true
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main_loss_type: DiceLoss
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alpha: 5
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beta: 10
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ohem_ratio: 3
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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 #(8*8c)
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warmup_epoch: 2
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regularizer:
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name: L2
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factor: 5.0e-05
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PostProcess:
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name: DBPostProcess
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thresh: 0.3
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box_thresh: 0.6
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max_candidates: 1000
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unclip_ratio: 1.5
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Metric:
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name: DetMetric
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main_indicator: hmean
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Train:
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dataset:
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name: SimpleDataSet
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data_dir: ./data/input0/images #图片文件夹路径
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label_file_list:
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- ./det_train_label.txt #标签路径
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ratio_list: [1.0]
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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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- DetLabelEncode: null
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- CopyPaste: null
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- IaaAugment:
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augmenter_args:
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- type: Fliplr
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args:
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p: 0.5
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- type: Affine
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args:
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rotate:
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- -10
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- 10
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- type: Resize
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args:
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size:
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- 0.5
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- 3
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- EastRandomCropData:
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size:
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- 640
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- 640
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max_tries: 50
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keep_ratio: true
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- MakeBorderMap:
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shrink_ratio: 0.4
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thresh_min: 0.3
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thresh_max: 0.7
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total_epoch: *epoch_num
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- MakeShrinkMap:
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shrink_ratio: 0.4
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min_text_size: 8
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total_epoch: *epoch_num
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- NormalizeImage:
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scale: 1./255.
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mean:
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- 0.485
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- 0.456
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- 0.406
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std:
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- 0.229
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- 0.224
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- 0.225
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order: hwc
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- ToCHWImage: null
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- KeepKeys:
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keep_keys:
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- image
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- threshold_map
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- threshold_mask
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- shrink_map
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- shrink_mask
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loader:
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shuffle: true
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drop_last: false
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batch_size_per_card: 14
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num_workers: 1
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./data/input0/images
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label_file_list:
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- ./det_eval_label.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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- DetLabelEncode: null
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- DetResizeForTest:
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- NormalizeImage:
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scale: 1./255.
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mean:
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- 0.485
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- 0.456
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- 0.406
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std:
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- 0.229
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- 0.224
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- 0.225
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order: hwc
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- ToCHWImage: null
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- KeepKeys:
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keep_keys:
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- image
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- shape
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- polys
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- ignore_tags
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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: 1
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num_workers: 1
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profiler_options: null
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```
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### PP-OCRv5_mobile_rec.yml
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```yaml
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Global:
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model_name: PP-OCRv5_mobile_rec # To use static model for inference.
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debug: false
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use_gpu: true
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epoch_num: 75
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/PP-OCRv5_mobile_rec
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save_epoch_step: 10
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eval_batch_step: [0, 2000]
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cal_metric_during_train: true
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pretrained_model: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv5_mobile_rec_pretrained.pdparams
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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/ppocrv5_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_ppocrv5.txt
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d2s_train_image_shape: [3, 48, 320]
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|
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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: 0.0005
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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_LCNet
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Transform:
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Backbone:
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name: PPLCNetV3
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scale: 0.95
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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: 120
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depth: 2
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hidden_dims: 120
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kernel_size: [1, 3]
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use_guide: True
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Head:
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fc_decay: 0.00001
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- NRTRHead:
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nrtr_dim: 384
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max_text_length: *max_text_length
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|
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Loss:
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name: MultiLoss
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|
loss_config_list:
|
|
- CTCLoss:
|
|
- NRTRLoss:
|
|
|
|
PostProcess:
|
|
name: CTCLabelDecode
|
|
|
|
Metric:
|
|
name: RecMetric
|
|
main_indicator: acc
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|
|
|
Train:
|
|
dataset:
|
|
name: MultiScaleDataSet
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|
ds_width: false
|
|
data_dir: ./RecTrainData/
|
|
ext_op_transform_idx: 1
|
|
label_file_list:
|
|
- ./rec_train_label.txt
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|
transforms:
|
|
- DecodeImage:
|
|
img_mode: BGR
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|
channel_first: false
|
|
- RecConAug:
|
|
prob: 0.5
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ext_data_num: 2
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image_shape: [48, 320, 3]
|
|
max_text_length: *max_text_length
|
|
- RecAug:
|
|
- MultiLabelEncode:
|
|
gtc_encode: NRTRLabelEncode
|
|
- KeepKeys:
|
|
keep_keys:
|
|
- image
|
|
- label_ctc
|
|
- label_gtc
|
|
- length
|
|
- valid_ratio
|
|
sampler:
|
|
name: MultiScaleSampler
|
|
scales: [[320, 32], [320, 48], [320, 64]]
|
|
first_bs: &bs 128
|
|
fix_bs: false
|
|
divided_factor: [8, 16] # w, h
|
|
is_training: True
|
|
loader:
|
|
shuffle: true
|
|
batch_size_per_card: 14
|
|
drop_last: true
|
|
num_workers: 1
|
|
Eval:
|
|
dataset:
|
|
name: SimpleDataSet
|
|
data_dir: ./RecEvalData/
|
|
label_file_list:
|
|
- ./rec_eval_label.txt
|
|
transforms:
|
|
- DecodeImage:
|
|
img_mode: BGR
|
|
channel_first: false
|
|
- MultiLabelEncode:
|
|
gtc_encode: NRTRLabelEncode
|
|
- RecResizeImg:
|
|
image_shape: [3, 48, 320]
|
|
- KeepKeys:
|
|
keep_keys:
|
|
- image
|
|
- label_ctc
|
|
- label_gtc
|
|
- length
|
|
- valid_ratio
|
|
loader:
|
|
shuffle: false
|
|
drop_last: false
|
|
batch_size_per_card: 14
|
|
num_workers: 1
|
|
```
|
|
|