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Merge pull request #28968 from Prasadayus:Identity_function_fix_for_0D

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Fixes the issue for Identity functions for 0D #28968

Closes https://github.com/opencv/opencv/issues/25763

### 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
- [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
This commit is contained in:
Prasad Ayush Kumar
2026-05-12 17:13:46 +05:30
committed by GitHub
parent 2ad46b860b
commit 223b110c30
5 changed files with 47 additions and 26 deletions
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modules/python/src2/cv2_numpy.cpp
+4 -8
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@@ -15,8 +15,9 @@ UMatData* NumpyAllocator::allocate(PyObject* o, int dims, const int* sizes, int
npy_intp* _strides = PyArray_STRIDES((PyArrayObject*) o);
for( int i = 0; i < dims - 1; i++ )
step[i] = (size_t)_strides[i];
step[dims-1] = CV_ELEM_SIZE(type);
u->size = sizes[0]*step[0];
if( dims > 0 )
step[dims-1] = CV_ELEM_SIZE(type);
u->size = dims > 0 ? sizes[0]*step[0] : CV_ELEM_SIZE(type);
u->userdata = o;
return u;
}
@@ -33,12 +34,7 @@ UMatData* NumpyAllocator::allocate(int dims0, const int* sizes, int type, void*
int depth = CV_MAT_DEPTH(type);
int cn = CV_MAT_CN(type);
const int f = (int)(sizeof(size_t)/8);
int typenum = depth == CV_8U ? NPY_UBYTE : depth == CV_8S ? NPY_BYTE :
depth == CV_16U ? NPY_USHORT : depth == CV_16S ? NPY_SHORT :
depth == CV_32U ? NPY_UINT32 : depth == CV_32S ? NPY_INT32 : depth == CV_64S ? NPY_INT64 :
depth == CV_32F ? NPY_FLOAT : depth == CV_64F ? NPY_DOUBLE : depth == CV_16F ? NPY_HALF :
depth == CV_Bool ? NPY_BOOL : f*NPY_ULONGLONG + (f^1)*NPY_UINT;
int typenum = cvDepthToNumpyType(depth);
int i, dims = dims0;
cv::AutoBuffer<npy_intp> _sizes(dims + 1);
for( i = 0; i < dims; i++ )