mirror of
https://github.com/RapidAI/RapidOCR.git
synced 2026-11-10 21:10:55 +08:00
JinmingMei
9fe06b676c
* feat(python): support PP-OCRv6 for onnxruntime and openvino Add PP-OCRv6 rec and det models (tiny/small/medium) for onnxruntime and openvino engines. v6 ships no cls model; reuse PP-OCRv5 cls. - typings.py: add OCRVersion.PPOCRV6 and ModelType.TINY/SMALL/MEDIUM - default_models.yaml: add PP-OCRv6 blocks under onnxruntime/openvino with PaddlePaddle official ModelScope URLs, verified SHA256, and dict_url (PaddleOCR dict files) Verified end-to-end on ch_en_num.jpg with v6 small det+rec + v5 cls (onnxruntime): 18 text lines recognized correctly. * fix(python): use uniquely-named PP-OCRv6 model URLs to avoid cache collision PP-OCRv6 official ONNX exports are all named inference.onnx, causing det and rec models to overwrite each other in RapidOCR's cache (cache_dir/Path(url).name). Switch model_dir/dict_url to a mirror with unique filenames (ch_PP-OCRv6_<task>_<size>.onnx) under modelscope.cn/models/jaminmei/PP-OCRv6-onnx@v1.0. SHA256 unchanged (byte-identical files, renamed only). Verified onnxruntime + openvino: no more redownload-on-collision; second run is pure cache hit. * test(python): add PP-OCRv6 det/rec unit tests for onnxruntime and openvino Mirror the test_ppocrv5_det/rec_mobile pattern. v6 small det on ch_en_num.jpg -> 18 boxes; v6 small rec on text_rec.jpg -> '韩国小馆'. Parametrized over the two engines v6 supports (ONNXRUNTIME, OPENVINO). Existing 100 tests unaffected (verified via collect-only). Verified: 4 new tests pass (onnxruntime + openvino x det/rec). * chore(python): switch PP-OCRv6 model URLs to official RapidAI/RapidOCR repo - det/rec x tiny/small/medium now point to modelscope.cn/RapidAI/RapidOCR (official SWHL conversion, not contributor mirror) - update SHA256 to the official files' hashes - drop rec dict_url: official ONNX embeds the character list in metadata (session.have_key() path), matching v4/v5 onnx convention - verified: 4 v6 unit tests pass; det benchmark Hmean identical to prior mirror-based run (0.8263/0.8492/0.8421 for tiny/small/medium)