Bump supported ONNX RT version to 1.14.1 #23529
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- Existing tests pass with the ONNX models mentioned in tests.
| Ort::AllocatedStringPtr name_p = pos == INPUT | ||
| ? this_session.GetInputNameAllocated(i, allocator) | ||
| : this_session.GetOutputNameAllocated(i, allocator); | ||
| tensor_info.back().name = std::string(name_p.get()); |
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@dmatveev, please, check that copy is created properly, because AllocatedStringPtr name_p will die in this scope.
Try run demos or onnx tests. I did not see onnx check (mb I am blind).
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Existing tests pass with the ONNX models mentioned in tests.
Ok. Then all works.
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@dmatveev Did the G-API ONNX classification test pass on your end (requires model downloading, see https://github.com/opencv/opencv/blob/4.x/modules/gapi/misc/python/test/test_gapi_infer_onnx.py#L21)? The model I have keeps returning garbage and inference results don't differ at all while I process my video sample. The behavior is the same on the CPU and GPU.
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@mpashchenkov thanks for review, std::string copies its char* argument (not moves) so its ok for name_p to be destroyed right after.
@asutic I will have a look on that, thanks!
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G-API ONNX doesn't support GPU. Or did I miss something?
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@dmatveev,
A crutch for the longevity of names:
Keep ptrs in class state ->
std::vector<const char*> inputNodeNames;
std::vector<Ort::AllocatedStringPtr> inputNodePtrs;
just in case *
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@dmatveev, https://github.com/opencv/opencv_extra/blob/4.x/testdata/gapi/onnx/download_onnx_models.py Script can be updated for current modes or (if works) link can be posted on the WIKI. |
Thanks @mpashchenkov I missed this! I crafted wiki with manual commands to download models instead :) https://github.com/opencv/opencv/wiki/Using-G-API-with-MS-ONNX-Runtime |
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Patch to opencv_extra has the same branch name.