feat: adapt rapidocr v3 and refactor code #99
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Pull Request Overview
This PR refactors the core engine initialization and updates to support RapidOCR v3, reorganizing model downloading and preprocessing/postprocessing workflows.
- Adapt PPTableStructurer and TableLabelDecode for new token handling
- Introduce
ModelProcessorfor model path management - Refactor
RapidTableto userapidocrpackage and new dataclass configs
Reviewed Changes
Copilot reviewed 19 out of 35 changed files in this pull request and generated 6 comments.
| File | Description |
|---|---|
| rapid_table/table_structure/pp_structure/post_process.py | Adjusted label decoding and special-token handling |
| rapid_table/main.py | Refactored RapidTable init and CLI entrypoint |
| rapid_table/inference_engine/torch.py | Added stub for Torch inference session |
| rapid_table/inference_engine/onnxruntime/main.py | Updated ONNX Runtime session creation and error handling |
Comments suppressed due to low confidence (2)
rapid_table/main.py:45
- [nitpick] Warning is incomplete/unhelpful; consider clarifying, e.g., 'rapidocr package is not installed; OCR step disabled, only table postprocessing will run.'
logger.warning("rapidocr package is not installed, only table rec")
rapid_table/inference_engine/onnxruntime/main.py:70
- The method is annotated to return
np.ndarraybut callssession.run, which returns aList[np.ndarray]; update the return type or convert the output accordingly.
def __call__(self, input_content: np.ndarray) -> np.ndarray:
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