G-API: Support CUDA & TensoRT Execution Providers for ONNXRT Backend #24059
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PReLU with element-wise scales #24056
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24051
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Update opencv dnn to support cann version >=6.3 #23936
1.modify the search path of "libopsproto.so" in OpenCVFindCANN.cmake
2.add the search path of "libgraph_base.so" in OpenCVFindCANN.cmake
3.automatic check Ascend socVersion,and test on Ascend310/Ascend310B/Ascend910B well
Python typing refinement for dnn_registerLayer/dnn_unregisterLayer functions #24066
This patch introduces typings generation for `dnn_registerLayer`/`dnn_unregisterLayer` manually defined in [`cv2/modules/dnn/misc/python/pyopencv_dnn.hpp`](https://github.com/opencv/opencv/blob/4.x/modules/dnn/misc/python/pyopencv_dnn.hpp)
Updates:
- Add `LayerProtocol` to `cv2/dnn/__init__.pyi`:
```python
class LayerProtocol(Protocol):
def __init__(
self, params: dict[str, DictValue],
blobs: typing.Sequence[cv2.typing.MatLike]
) -> None: ...
def getMemoryShapes(
self, inputs: typing.Sequence[typing.Sequence[int]]
) -> typing.Sequence[typing.Sequence[int]]: ...
def forward(
self, inputs: typing.Sequence[cv2.typing.MatLike]
) -> typing.Sequence[cv2.typing.MatLike]: ...
```
- Add `dnn_registerLayer` function to `cv2/__init__.pyi`:
```python
def dnn_registerLayer(layerTypeName: str,
layerClass: typing.Type[LayerProtocol]) -> None: ...
```
- Add `dnn_unregisterLayer` function to `cv2/__init__.pyi`:
```python
def dnn_unregisterLayer(layerTypeName: str) -> None: ...
```
### Pull Request Readiness Checklist
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- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Fix harmless ASAN error. #24042
For an empty radius, &v[0] would be accessed (though the called functions would not use it due to v.size() being 0). Also add checks for emptyness and fix the first element checks, in case we get INT_MAX to compare to.
### Pull Request Readiness Checklist
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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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G-API: Support DirectML Execution Provider for ONNXRT Backend #24045
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- [ ] I agree to contribute to the project under Apache 2 License.
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- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
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feat: add cuda_Stream and cuda_GpuMat to simple types mapping #24029
This patch fixes usage of `cuda::Stream` in function arguments.
Affected modules: `cudacodec`:
[`using namespace cuda`](9dfe233020/modules/cudacodec/include/opencv2/cudacodec.hpp (L62)) in public `cudacodec.hpp` header can be removed after merge of the patch.
### Pull Request Readiness Checklist
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- [x] I agree to contribute to the project under Apache 2 License.
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- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Fix FLANN python bindings #24028
As a side-effect this patch improves reporting errors by FLANN `get_param`.
resolves#21642
### Pull Request Readiness Checklist
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- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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G-API: Support OpenVINO Execution Provider for ONNXRT Backend #24024
### Pull Request Readiness Checklist
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- [ ] I agree to contribute to the project under Apache 2 License.
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- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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[TFLite] Pack layer and other fixes for SSD from Keras #24004
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23992
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1076
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Details here: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=58006
runtime error: call to function (unknown) through pointer to incorrect function type 'void (*)(const unsigned char **, const int *, unsigned char **, const int *, int, int)'
Python typing magic constants #24023
This patch adds typing stubs generation for `__all__` and `__version__` constants.
Introduced `__all__` is intentionally empty for all generated modules stubs.
Type hints won't work for star imports
resolves#23950
### Pull Request Readiness Checklist
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Fix python typing stubs generation for CUDA modules #24022resolves#23946resolves#23945resolvesopencv/opencv-python#871
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
