Please refer me to the exact code and files PaddleOCR uses to prepare the image to input into the model.

[thebest132]

In my case I need to run the detection and recognition .onnx models. I also need the code and location of the usage of det_db_unclip_ratio .

[GreatV]

To understand how PaddleOCR prepares an image for input into the model, you need to look at the image preprocessing pipeline in the PaddleOCR repository. Specifically, image preprocessing is handled in the ppocr/data/imaug directory, which contains the code for resizing, normalization, and other transformations applied to images before they are passed to the detection and recognition models.

Image Preprocessing Code Locations:

• Detection Model Preprocessing:
  The relevant code for preparing images for the detection model is typically found in:

  • ppocr/data/imaug/operators.py
  • ppocr/postprocess/db_postprocess.py
  • Functions such as ResizeNormForInfer handle resizing, normalization, and preparation for inference.

• Recognition Model Preprocessing:

  • ppocr/data/imaug/rec_img_aug.py contains augmentations used for recognition.
  • ppocr/data/imaug/operators.py also includes preprocessing steps such as resizing and normalization before input into the recognition model.

Code Usage for det_db_unclip_ratio:

• Location of det_db_unclip_ratio Usage:
  • This parameter is used in ppocr/postprocess/db_postprocess.py.
  • It is critical for the post-processing step when extracting text regions from the model’s detection output.
  • The DBPostProcess class makes use of this parameter to determine how much to expand the detected text region.

Related Discussions:

• A relevant discussion about model training and detection can be found here:
  PaddleOCR Detection Model Training Discussion
  This discussion provides insights into the detection model's training and processing pipeline.

Would you like additional details on a specific part of the pipeline?

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