Merge pull request #28968 from Prasadayus:Identity_function_fix_for_0D

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

modules/python/src2/cv2_convert.cpp

@@ -129,18 +129,7 @@ bool pyopencv_to(PyObject* o, Mat& m, const ArgInfo& info)
 
     bool needcopy = false, needcast = false;
     int typenum = PyArray_TYPE(oarr), new_typenum = typenum;
-    int type = typenum == NPY_UBYTE ? CV_8U :
-               typenum == NPY_BYTE ? CV_8S :
-               typenum == NPY_USHORT ? CV_16U :
-               typenum == NPY_SHORT ? CV_16S :
-               typenum == NPY_INT ? CV_32S :
-               typenum == NPY_UINT32 ? CV_32U :
-               typenum == NPY_INT32 ? CV_32S :
-               typenum == NPY_HALF ? CV_16F :
-               typenum == NPY_FLOAT ? CV_32F :
-               typenum == NPY_DOUBLE ? CV_64F :
-               typenum == NPY_BOOL ? CV_Bool :
-               -1;
+    int type = numpyTypeToCvDepth(typenum);
 
     if( type < 0 )
     {
@@ -296,12 +285,14 @@ bool pyopencv_to(PyObject* o, Mat& m, const ArgInfo& info)
         return filled;
     }
 
-    // handle degenerate case
-    // FIXIT: Don't force 1D for Scalars
-    if( ndims == 0) {
-        size[ndims] = 1;
-        step[ndims] = elemsize;
-        ndims++;
+    // 0D (scalar) tensor: allocate a proper scalar Mat and copy the value.
+    if (ndims == 0)
+    {
+        m.fit(0, nullptr, type);
+        memcpy(m.data, PyArray_DATA(oarr), CV_ELEM_SIZE(type));
+        if (needcopy)
+            Py_DECREF(o);
+        return true;
     }
 
 #if 1
@@ -326,6 +317,15 @@ PyObject* pyopencv_from(const cv::Mat& m)
 {
     if( !m.data )
         Py_RETURN_NONE;
+    // 0D (scalar) Mat: return a true 0D numpy array.
+    if( m.dims == 0 )
+    {
+        int typenum = cvDepthToNumpyType(CV_MAT_DEPTH(m.type()));
+        PyObject* o = PyArray_SimpleNew(0, nullptr, typenum);
+        if( o )
+            memcpy(PyArray_DATA((PyArrayObject*)o), m.data, CV_ELEM_SIZE(m.type()));
+        return o;
+    }
     cv::Mat temp, *p = (cv::Mat*)&m;
     if(!p->u || p->allocator != &GetNumpyAllocator())
     {

modules/python/src2/cv2_numpy.cpp

@@ -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++ )

modules/python/src2/cv2_util.cpp

@@ -6,6 +6,25 @@
 PyObject* opencv_error = NULL;
 cv::TLSData<std::vector<std::string> > conversionErrorsTLS;
 
+int cvDepthToNumpyType(int depth)
+{
+    const int f = (int)(sizeof(size_t)/8);
+    return 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 numpyTypeToCvDepth(int typenum)
+{
+    return typenum == NPY_UBYTE ? CV_8U : typenum == NPY_BYTE ? CV_8S :
+           typenum == NPY_USHORT ? CV_16U : typenum == NPY_SHORT ? CV_16S :
+           typenum == NPY_INT ? CV_32S : typenum == NPY_UINT32 ? CV_32U : typenum == NPY_INT32 ? CV_32S :
+           typenum == NPY_HALF ? CV_16F : typenum == NPY_FLOAT ? CV_32F : typenum == NPY_DOUBLE ? CV_64F :
+           typenum == NPY_BOOL ? CV_Bool : -1;
+}
+
 using namespace cv;
 
 //======================================================================================================================

modules/python/src2/cv2_util.hpp

@@ -14,6 +14,9 @@ void emit_failmsg(PyObject * exc, const char *msg);
 int failmsg(const char *fmt, ...);
 PyObject* failmsgp(const char *fmt, ...);
 
+int cvDepthToNumpyType(int depth);
+int numpyTypeToCvDepth(int typenum);
+
 //======================================================================================================================
 
 class PyAllowThreads