🔄 PaddleOCR Model Convert

 

• This repository is mainly to convert Inference Model in PaddleOCR into ONNX format.
• Input: url or local tar path of inference model
• Output: converted ONNX model
• If it is a recognition model, you need to provide the original txt path of the corresponding dictionary (Open the txt file in github, click the path after raw in the upper right corner, similar to this), used to write the dictionary into the ONNX model
• ☆ It needs to be used with the relevant reasoning code in RapidOCR
• If you encounter a model that cannot be successfully converted, you can check which steps are wrong one by one according to the ideas in the figure below.

flowchart TD

A([PaddleOCR inference model]) --paddle2onnx--> B([ONNX])
B --> C([Change Dynamic Input]) --> D([Rec: save the character dict to onnx])
D --> E([Save])

pip install paddleocr_convert

• Usage:

  $ paddleocr_convert -h
  usage: paddleocr_convert [-h] [-p MODEL_PATH] [-o SAVE_DIR]
                          [-txt_path TXT_PATH]
  
  optional arguments:
  -h, --help show this help message and exit
  -p MODEL_PATH, --model_path MODEL_PATH
                          The inference model url or local path of paddleocr.
                          e.g. https://paddleocr.bj.bcebos.com/PP-
                          OCRv3/chinese/ch_PP-OCRv3_det_infer.tar or
                          models/ch_PP-OCRv3_det_infer.tar
  -o SAVE_DIR, --save_dir SAVE_DIR
                          The directory of saving the model.
  -txt_path TXT_PATH, --txt_path TXT_PATH
                          The raw txt url or local txt path, if the model is
                          recognition model.

• Example:

  #online
  $ paddleocr_convert -p https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar \
                      -o models
  
  $ paddleocr_convert -p https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar\
                      -o models\
                      -txt_path https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.6/ppocr/utils/ppocr_keys_v1.txt
  
  # offline
  $ paddleocr_convert -p models/ch_PP-OCRv3_det_infer.tar\
                      -o models
  
  $ paddleocr_convert -p models/ch_PP-OCRv3_rec_infer.tar\
                      -o models\
                      -txt_path models/ppocr_keys_v1.txt

• online mode

  from paddleocr_convert import PaddleOCRModelConvert
  
  converter = PaddleOCRModelConvert()
  save_dir = 'models'
  url = 'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar'
  txt_url = 'https://raw.githubusercontent.com/PaddlePaddle/PaddleOCR/release/2.6/ppocr/utils/ppocr_keys_v1.txt'
  
  converter(url, save_dir, txt_path=txt_url)

• offline mode

  from paddleocr_convert import PaddleOCRModelConvert
  
  converter = PaddleOCRModelConvert()
  save_dir = 'models'
  model_path = 'models/ch_PP-OCRv3_rec_infer.tar'
  txt_path = 'models/ppocr_keys_v1.txt'
  converter(model_path, save_dir, txt_path=txt_path)

Assuming that the model needs to be recognized in Japanese, and it has been converted, the path is local/models/japan.onnx

1. Install rapidocr_onnxruntime library

   pip install rapidocr_onnxruntime

2. Script use

   from rapidocr_onnxruntime import RapidOCR
   
   model_path = 'local/models/japan.onnx'
   engine = RapidOCR(rec_model_path=model_path)
   
   img = '1.jpg'
   result, elapse = engine(img)

3. CLI use

   rapidocr_onnxruntime -img 1.jpg --rec_model_path local/models/japan.onnx