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python: drop the CV_16BF -> float32 mapping, share the empty / 0-D output path, run flag tests without ml_dtypes

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Signed-off-by: Abhishek Gola <abhishek.gola@bigvisionllc.com>
This commit is contained in:
Abhishek Gola
2026-10-30 15:59:00 +05:30
parent 3f7c2f7077
commit 8751eb491e
9 changed files with 109 additions and 63 deletions
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49
modules/python/src2/cv2_convert.cpp
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@@ -334,8 +334,9 @@ bool pyopencv_to(PyObject* o, Mat& m, const ArgInfo& info)
return true;
}
// Builds an empty or 0-D array of dtype `descr`; the caller guarantees it matches m.depth().
static PyObject* pyopencv_from_nonconventional(const cv::Mat& m, PyArray_Descr* descr)
// Copies an empty or 0-D Mat into a new array of dtype `descr`, which must match m.depth().
// Steals the reference to `descr`. Channels become the last axis, so a 0-D Mat has shape (cn,).
static PyObject* pyopencv_from_new_array(const cv::Mat& m, PyArray_Descr* descr)
{
const int cn = m.channels();
int dims = m.dims;
@@ -345,7 +346,6 @@ static PyObject* pyopencv_from_nonconventional(const cv::Mat& m, PyArray_Descr*
if( cn > 1 )
_sizes[dims++] = cn;
Py_INCREF(descr); // PyArray_NewFromDescr steals the reference
PyObject* o = PyArray_NewFromDescr(&PyArray_Type, descr, dims, _sizes.data(),
nullptr, nullptr, 0, nullptr);
if( o && !m.empty() )
@@ -356,12 +356,14 @@ static PyObject* pyopencv_from_nonconventional(const cv::Mat& m, PyArray_Descr*
template<>
PyObject* pyopencv_from(const cv::Mat& m)
{
PyArray_Descr* exotic = nullptr;
if( isNonConventionalDepth(m.depth()) )
{
PyArray_Descr* descr = nonConventionalDescrForCvDepth(m.depth());
if( !descr )
exotic = nonConventionalDescrForCvDepth(m.depth());
if( !exotic )
{
// The caller's own array (e.g. dst=) already has the exact dtype: return it as is.
// Like the shared path below, this assumes m spans the whole array, not a ROI of it.
if( m.u && m.allocator == &GetNumpyAllocator() )
{
PyObject* o = (PyObject*)m.u->userdata;
@@ -377,36 +379,21 @@ PyObject* pyopencv_from(const cv::Mat& m)
ERRWRAP2(m.convertTo(m32f, CV_32F));
return pyopencv_from(m32f);
}
if( m.empty() || m.dims == 0 )
return pyopencv_from_nonconventional(m, descr);
// Otherwise share the path below: NumpyAllocator allocates with `descr`.
}
if( m.empty() )
{
// empty() also catches a live buffer with a zero-length dim: return an empty array, not None.
if( m.dims >= 1 )
{
int cn = m.channels();
int typenum = cvDepthToNumpyType(m.depth());
int dims = m.dims;
cv::AutoBuffer<npy_intp> _sizes(dims + 1);
for( int i = 0; i < dims; i++ )
_sizes[i] = (npy_intp)m.size[i];
if( cn > 1 )
_sizes[dims++] = cn;
return PyArray_SimpleNew(dims, _sizes.data(), typenum);
}
if( m.empty() && m.dims == 0 )
Py_RETURN_NONE;
}
// 0D (scalar) Mat: return a true 0D numpy array.
if( m.dims == 0 )
// empty() also catches a live buffer with a zero-length dim: return an empty array, not None.
// A 0D (scalar) Mat becomes a true 0D numpy array.
if( m.empty() || 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;
PyArray_Descr* descr = exotic;
if( descr )
Py_INCREF(descr);
else
descr = PyArray_DescrFromType(cvDepthToNumpyType(m.depth()));
return pyopencv_from_new_array(m, descr);
}
// NumpyAllocator gives bfloat16 / float8 arrays their exact dtype here too.
cv::Mat temp, *p = (cv::Mat*)&m;
if(!p->u || p->allocator != &GetNumpyAllocator())
{