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opencv/modules/core/test/test_umat.cpp
Kavyansh Tyagi 7ca36d9c50
Merge pull request #27408 from KAVYANSHTYAGI:Umat-vector-contructor 
Deprecate copyData Parameter in UMat Construction from std::vector and Always Copy Data #27408

Overview

This PR simplifies and modernizes the construction of cv::UMat from std::vector by removing the legacy copyData parameter, always copying the data, and ensuring clearer, safer semantics. This brings UMat in line with current best practices and paves the way for the upcoming OpenCV 5.x series.

What Changed?

1. Header Documentation Update

    Removed confusing or obsolete documentation about copyData and clarified the behavior:

        Old: builds matrix from std::vector with or without copying the data

        New: builds matrix from std::vector. The data is always copied. The copyData parameter is deprecated and will be removed in OpenCV 5.0.

2. Implementation Update

    In UMat::UMat(const std::vector<_Tp>& vec, bool copyData), the copyData parameter:

        Is now ignored and marked as deprecated.

        Marked with CV_UNUSED(copyData) for backward compatibility and to avoid warnings.

    The constructor always copies the data from the input vector, regardless of the value of copyData.

    All branching logic around copyData has been removed. Any code for "not copying" was not implemented and is now dropped.

    This guarantees data safety and predictable behavior.

3. Test Added

    A new test construct_from_vector in test_umat_from_vector.cpp:

        Verifies that UMat copies the vector data, not referencing it.

        Modifies the source vector after construction to confirm that the UMat is unaffected (proving copy, not reference).

        Checks matrix shape, type, and content to ensure correctness.

Why This Change?

1. Safety and Predictability

    Always copying avoids dangling references and hard-to-debug lifetime issues with stack/heap-allocated vectors.

    Removes an undocumented, unimplemented branch (copyData=false).

2. Backward Compatibility

    The constructor signature remains for now, but the copyData parameter is marked as deprecated and ignored.

    Codebases that pass the parameter will still compile and run as before (but always copy).

3. API Clarity and Maintenance

    Documentation now matches the real implementation.

    No misleading expectations about zero-copy.

    Code is cleaner, future-proof, and easier to maintain.

4. Preparation for OpenCV 5.0

    The copyData parameter is deprecated and will be removed in OpenCV 5.x.

    Prepares users and downstream libraries for the planned change.



How This Helps OpenCV Users and Developers

    Guarantees data safety and makes behavior explicit.

    Removes legacy/ambiguous code.

    Provides a clear path to OpenCV 5.x.

    Minimizes future migration pain.

    Ensures all users see the same, reliable behavior (copy semantics).


Refer:#27409
2025-06-09 16:02:38 +03:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
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// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the OpenCV Foundation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
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//M*/
#include "test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
using namespace opencv_test;
using namespace testing;
using namespace cv;
namespace opencv_test {
namespace ocl {
#define UMAT_TEST_SIZES testing::Values(cv::Size(1, 1), cv::Size(1,128), cv::Size(128, 1), \
cv::Size(128, 128), cv::Size(640, 480), cv::Size(751, 373), cv::Size(1200, 1200))
/////////////////////////////// Basic Tests ////////////////////////////////
PARAM_TEST_CASE(UMatBasicTests, int, int, Size, bool)
{
Mat a;
UMat ua;
int type;
int depth;
int cn;
Size size;
bool useRoi;
Size roi_size;
Rect roi;
virtual void SetUp()
{
depth = GET_PARAM(0);
cn = GET_PARAM(1);
size = GET_PARAM(2);
useRoi = GET_PARAM(3);
type = CV_MAKE_TYPE(depth, cn);
a = randomMat(size, type, -100, 100);
a.copyTo(ua);
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
}
};
TEST_P(UMatBasicTests, createUMat)
{
if(useRoi)
{
ua = UMat(ua, roi);
}
int dims = randomInt(2,6);
int _sz[CV_MAX_DIM];
for( int i = 0; i<dims; i++)
{
_sz[i] = randomInt(1,50);
}
int *sz = _sz;
int new_depth = randomInt(CV_8S, CV_64F);
int new_cn = randomInt(1,4);
ua.create(dims, sz, CV_MAKE_TYPE(new_depth, new_cn));
for(int i = 0; i<dims; i++)
{
ASSERT_EQ(ua.size[i], sz[i]);
}
ASSERT_EQ(ua.dims, dims);
ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
Size new_size = randomSize(1, 1000);
ua.create(new_size, CV_MAKE_TYPE(new_depth, new_cn) );
ASSERT_EQ( ua.size(), new_size);
ASSERT_EQ(ua.type(), CV_MAKE_TYPE(new_depth, new_cn) );
ASSERT_EQ( ua.dims, 2);
}
TEST_P(UMatBasicTests, swap)
{
Mat b = randomMat(size, type, -100, 100);
UMat ub;
b.copyTo(ub);
if(useRoi)
{
ua = UMat(ua,roi);
ub = UMat(ub,roi);
}
UMat uc = ua, ud = ub;
swap(ua,ub);
EXPECT_MAT_NEAR(ub,uc, 0);
EXPECT_MAT_NEAR(ud, ua, 0);
}
TEST_P(UMatBasicTests, base)
{
const int align_mask = 3;
roi.x &= ~align_mask;
roi.y &= ~align_mask;
roi.width = (roi.width + align_mask) & ~align_mask;
roi &= Rect(0, 0, ua.cols, ua.rows);
if(useRoi)
{
ua = UMat(ua,roi);
}
UMat ub = ua.clone();
EXPECT_MAT_NEAR(ub,ua,0);
ASSERT_EQ(ua.channels(), cn);
ASSERT_EQ(ua.depth(), depth);
ASSERT_EQ(ua.type(), type);
ASSERT_EQ(ua.elemSize(), a.elemSize());
ASSERT_EQ(ua.elemSize1(), a.elemSize1());
ASSERT_EQ(ub.empty(), ub.cols*ub.rows == 0);
ub.release();
ASSERT_TRUE( ub.empty() );
if(useRoi && a.size() != ua.size())
{
ASSERT_EQ(ua.isSubmatrix(), true);
}
else
{
ASSERT_EQ(ua.isSubmatrix(), false);
}
int dims = randomInt(2,6);
int sz[CV_MAX_DIM];
size_t total = 1;
for(int i = 0; i<dims; i++)
{
sz[i] = randomInt(1,45);
total *= (size_t)sz[i];
}
int new_type = CV_MAKE_TYPE(randomInt(CV_8S,CV_64F),randomInt(1,4));
ub = UMat(dims, sz, new_type);
ASSERT_EQ(ub.total(), total);
}
TEST_P(UMatBasicTests, copyTo)
{
int i;
if(useRoi)
{
UMat roi_ua;
Mat roi_a;
roi_ua = UMat(ua, roi);
roi_a = Mat(a, roi);
roi_a.copyTo(roi_ua);
EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
roi_ua.copyTo(roi_a);
EXPECT_MAT_NEAR(roi_ua, roi_a, 0);
roi_ua.copyTo(ua);
EXPECT_MAT_NEAR(roi_ua, ua, 0);
ua.copyTo(a);
EXPECT_MAT_NEAR(ua, a, 0);
}
{
UMat ub;
ua.copyTo(ub);
EXPECT_MAT_NEAR(ua, ub, 0);
}
{
UMat ub;
i = randomInt(0, ua.cols-1);
a.col(i).copyTo(ub);
EXPECT_MAT_NEAR(a.col(i), ub, 0);
}
{
UMat ub;
ua.col(i).copyTo(ub);
EXPECT_MAT_NEAR(ua.col(i), ub, 0);
}
{
Mat b;
ua.col(i).copyTo(b);
EXPECT_MAT_NEAR(ua.col(i), b, 0);
}
{
UMat ub;
i = randomInt(0, a.rows-1);
ua.row(i).copyTo(ub);
EXPECT_MAT_NEAR(ua.row(i), ub, 0);
}
{
UMat ub;
a.row(i).copyTo(ub);
EXPECT_MAT_NEAR(a.row(i), ub, 0);
}
{
Mat b;
ua.row(i).copyTo(b);
EXPECT_MAT_NEAR(ua.row(i), b, 0);
}
}
TEST_P(UMatBasicTests, GetUMat)
{
if(useRoi)
{
a = Mat(a, roi);
ua = UMat(ua,roi);
}
{
UMat ub;
ub = a.getUMat(ACCESS_RW);
EXPECT_MAT_NEAR(ub, ua, 0);
}
{
UMat u = a.getUMat(ACCESS_RW);
{
Mat b = u.getMat(ACCESS_RW);
EXPECT_MAT_NEAR(b, a, 0);
}
}
{
Mat b;
b = ua.getMat(ACCESS_RW);
EXPECT_MAT_NEAR(b, a, 0);
}
{
Mat m = ua.getMat(ACCESS_RW);
{
UMat ub = m.getUMat(ACCESS_RW);
EXPECT_MAT_NEAR(ub, ua, 0);
}
}
}
INSTANTIATE_TEST_CASE_P(UMat, UMatBasicTests, Combine(testing::Values(CV_8U, CV_64F), testing::Values(1, 2),
testing::Values(cv::Size(1, 1), cv::Size(1, 128), cv::Size(128, 1), cv::Size(128, 128), cv::Size(640, 480)), Bool()));
//////////////////////////////////////////////////////////////// Reshape ////////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(UMatTestReshape, int, int, Size, bool)
{
Mat a;
UMat ua, ub;
int type;
int depth;
int cn;
Size size;
bool useRoi;
Size roi_size;
virtual void SetUp()
{
depth = GET_PARAM(0);
cn = GET_PARAM(1);
size = GET_PARAM(2);
useRoi = GET_PARAM(3);
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(UMatTestReshape, reshape)
{
a = randomMat(size,type, -100, 100);
a.copyTo(ua);
if(useRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
ua = UMat(ua, roi).clone();
a = Mat(a, roi).clone();
}
int nChannels = randomInt(1,4);
if ((ua.cols*ua.channels()*ua.rows)%nChannels != 0)
{
EXPECT_ANY_THROW(ua.reshape(nChannels));
}
else
{
ub = ua.reshape(nChannels);
ASSERT_EQ(ub.channels(),nChannels);
ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
EXPECT_MAT_NEAR(ua.reshape(nChannels), a.reshape(nChannels), 0);
int new_rows = randomInt(1, INT_MAX);
if ( ((int)ua.total()*ua.channels())%(new_rows*nChannels) != 0)
{
EXPECT_ANY_THROW (ua.reshape(nChannels, new_rows) );
}
else
{
EXPECT_NO_THROW ( ub = ua.reshape(nChannels, new_rows) );
ASSERT_EQ(ub.channels(),nChannels);
ASSERT_EQ(ub.rows, new_rows);
ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
EXPECT_MAT_NEAR(ua.reshape(nChannels,new_rows), a.reshape(nChannels,new_rows), 0);
}
new_rows = (int)ua.total()*ua.channels()/(nChannels*randomInt(1, size.width*size.height));
if (new_rows == 0) new_rows = 1;
int new_cols = (int)ua.total()*ua.channels()/(new_rows*nChannels);
int sz[] = {new_rows, new_cols};
if( ((int)ua.total()*ua.channels()) % (new_rows*new_cols) != 0 )
{
EXPECT_ANY_THROW( ua.reshape(nChannels, ua.dims, sz) );
}
else
{
EXPECT_NO_THROW ( ub = ua.reshape(nChannels, ua.dims, sz) );
ASSERT_EQ(ub.channels(),nChannels);
ASSERT_EQ(ub.rows, new_rows);
ASSERT_EQ(ub.cols, new_cols);
ASSERT_EQ(ub.channels()*ub.cols*ub.rows, ua.channels()*ua.cols*ua.rows);
EXPECT_MAT_NEAR(ua.reshape(nChannels, ua.dims, sz), a.reshape(nChannels, a.dims, sz), 0);
}
}
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestReshape, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
static void check_ndim_shape(const cv::UMat &mat, int cn, int ndims, const int *sizes)
{
EXPECT_EQ(mat.channels(), cn);
EXPECT_EQ(mat.dims, ndims);
if (mat.dims != ndims)
return;
for (int i = 0; i < ndims; i++)
EXPECT_EQ(mat.size[i], sizes[i]);
}
TEST(UMatTestReshape, reshape_ndims_2)
{
const cv::UMat A(8, 16, CV_8UC3);
cv::UMat B;
{
int new_sizes_mask[] = { 0, 3, 4, 4 };
int new_sizes_real[] = { 8, 3, 4, 4 };
ASSERT_NO_THROW(B = A.reshape(1, 4, new_sizes_mask));
check_ndim_shape(B, 1, 4, new_sizes_real);
}
{
int new_sizes[] = { 16, 8 };
ASSERT_NO_THROW(B = A.reshape(0, 2, new_sizes));
check_ndim_shape(B, 3, 2, new_sizes);
EXPECT_EQ(B.rows, new_sizes[0]);
EXPECT_EQ(B.cols, new_sizes[1]);
}
{
int new_sizes[] = { 2, 5, 1, 3 };
cv::UMat A_sliced = A(cv::Range::all(), cv::Range(0, 15));
ASSERT_ANY_THROW(A_sliced.reshape(4, 4, new_sizes));
}
}
TEST(UMatTestReshape, reshape_ndims_4)
{
const int sizes[] = { 2, 6, 4, 12 };
const cv::UMat A(4, sizes, CV_8UC3);
cv::UMat B;
{
int new_sizes_mask[] = { 0, 864 };
int new_sizes_real[] = { 2, 864 };
ASSERT_NO_THROW(B = A.reshape(1, 2, new_sizes_mask));
check_ndim_shape(B, 1, 2, new_sizes_real);
EXPECT_EQ(B.rows, new_sizes_real[0]);
EXPECT_EQ(B.cols, new_sizes_real[1]);
}
{
int new_sizes_mask[] = { 4, 0, 0, 2, 3 };
int new_sizes_real[] = { 4, 6, 4, 2, 3 };
ASSERT_NO_THROW(B = A.reshape(0, 5, new_sizes_mask));
check_ndim_shape(B, 3, 5, new_sizes_real);
}
{
int new_sizes_mask[] = { 1, 1 };
ASSERT_ANY_THROW(A.reshape(0, 2, new_sizes_mask));
}
{
int new_sizes_mask[] = { 4, 6, 3, 3, 0 };
ASSERT_ANY_THROW(A.reshape(0, 5, new_sizes_mask));
}
}
////////////////////////////////////////////////////////////////// ROI testing ///////////////////////////////////////////////////////////////
PARAM_TEST_CASE(UMatTestRoi, int, int, Size)
{
Mat a, roi_a;
UMat ua, roi_ua;
int type;
int depth;
int cn;
Size size;
Size roi_size;
virtual void SetUp()
{
depth = GET_PARAM(0);
cn = GET_PARAM(1);
size = GET_PARAM(2);
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(UMatTestRoi, createRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
a = randomMat(size, type, -100, 100);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
roi_a = Mat(a, roi);
a.copyTo(ua);
roi_ua = UMat(ua, roi);
EXPECT_MAT_NEAR(roi_a, roi_ua, 0);
}
TEST_P(UMatTestRoi, locateRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
a = randomMat(size, type, -100, 100);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
roi_a = Mat(a, roi);
a.copyTo(ua);
roi_ua = UMat(ua,roi);
Size sz, usz;
Point p, up;
roi_a.locateROI(sz, p);
roi_ua.locateROI(usz, up);
ASSERT_EQ(sz, usz);
ASSERT_EQ(p, up);
}
TEST_P(UMatTestRoi, adjustRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
a = randomMat(size, type, -100, 100);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
a.copyTo(ua);
roi_ua = UMat( ua, roi);
int adjLeft = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
int adjRight = randomInt(-(roi_ua.cols/2), (size.width-1)/2);
int adjTop = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
int adjBot = randomInt(-(roi_ua.rows/2), (size.height-1)/2);
roi_ua.adjustROI(adjTop, adjBot, adjLeft, adjRight);
roi_shift_x = std::max(0, roi.x-adjLeft);
roi_shift_y = std::max(0, roi.y-adjTop);
Rect new_roi( roi_shift_x, roi_shift_y, std::min(roi.width+adjRight+adjLeft, size.width-roi_shift_x), std::min(roi.height+adjBot+adjTop, size.height-roi_shift_y) );
UMat test_roi = UMat(ua, new_roi);
EXPECT_MAT_NEAR(roi_ua, test_roi, 0);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestRoi, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES ));
TEST(UMatTestRoi, adjustRoiOverflow)
{
UMat m(15, 10, CV_32S);
UMat roi(m, cv::Range(2, 10), cv::Range(3,6));
int rowsInROI = roi.rows;
roi.adjustROI(1, 0, 0, 0);
ASSERT_EQ(roi.rows, rowsInROI + 1);
roi.adjustROI(-m.rows, -m.rows, 0, 0);
ASSERT_EQ(roi.rows, m.rows);
}
/////////////////////////////////////////////////////////////// Size ////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(UMatTestSizeOperations, int, int, Size, bool)
{
Mat a, b, roi_a, roi_b;
UMat ua, ub, roi_ua, roi_ub;
int type;
int depth;
int cn;
Size size;
Size roi_size;
bool useRoi;
virtual void SetUp()
{
depth = GET_PARAM(0);
cn = GET_PARAM(1);
size = GET_PARAM(2);
useRoi = GET_PARAM(3);
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(UMatTestSizeOperations, copySize)
{
Size s = randomSize(1,300);
a = randomMat(size, type, -100, 100);
b = randomMat(s, type, -100, 100);
a.copyTo(ua);
b.copyTo(ub);
if(useRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
ua = UMat(ua,roi);
roi_shift_x = randomInt(0, s.width-1);
roi_shift_y = randomInt(0, s.height-1);
roi_size = Size(s.width - roi_shift_x, s.height - roi_shift_y);
roi = Rect(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
ub = UMat(ub, roi);
}
ua.copySize(ub);
ASSERT_EQ(ua.size, ub.size);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestSizeOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool() ));
///////////////////////////////////////////////////////////////// UMat operations ////////////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(UMatTestUMatOperations, int, int, Size, bool)
{
Mat a, b;
UMat ua, ub;
int type;
int depth;
int cn;
Size size;
Size roi_size;
bool useRoi;
virtual void SetUp()
{
depth = GET_PARAM(0);
cn = GET_PARAM(1);
size = GET_PARAM(2);
useRoi = GET_PARAM(3);
type = CV_MAKE_TYPE(depth, cn);
}
};
TEST_P(UMatTestUMatOperations, diag)
{
a = randomMat(size, type, -100, 100);
a.copyTo(ua);
Mat new_diag;
if(useRoi)
{
int roi_shift_x = randomInt(0, size.width-1);
int roi_shift_y = randomInt(0, size.height-1);
roi_size = Size(size.width - roi_shift_x, size.height - roi_shift_y);
Rect roi(roi_shift_x, roi_shift_y, roi_size.width, roi_size.height);
ua = UMat(ua,roi);
a = Mat(a, roi);
}
int n = randomInt(0, ua.cols-1);
ub = ua.diag(n);
b = a.diag(n);
EXPECT_MAT_NEAR(b, ub, 0);
new_diag = randomMat(Size(ua.rows, 1), type, -100, 100);
new_diag.copyTo(ub);
ua = cv::UMat::diag(ub);
EXPECT_MAT_NEAR(ua.diag(), new_diag.t(), 0);
}
INSTANTIATE_TEST_CASE_P(UMat, UMatTestUMatOperations, Combine(OCL_ALL_DEPTHS, OCL_ALL_CHANNELS, UMAT_TEST_SIZES, Bool()));
/////////////////////////////////////////////////////////////// getUMat -> GetMat ///////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(getUMat, int, int, Size, bool)
{
int type;
Size size;
virtual void SetUp()
{
int depth = GET_PARAM(0);
int cn = GET_PARAM(1);
size = GET_PARAM(2);
useOpenCL = GET_PARAM(3);
type = CV_MAKE_TYPE(depth, cn);
isOpenCL_enabled = cv::ocl::useOpenCL();
cv::ocl::setUseOpenCL(useOpenCL);
}
virtual void TearDown()
{
cv::ocl::setUseOpenCL(isOpenCL_enabled);
}
// UMat created from user allocated host memory (USE_HOST_PTR)
void custom_ptr_test(size_t align_base, size_t align_offset)
{
void* pData_allocated = new unsigned char [size.area() * CV_ELEM_SIZE(type) + (align_base + align_offset)];
void* pData = (char*)alignPtr(pData_allocated, (int)align_base) + align_offset;
size_t step = size.width * CV_ELEM_SIZE(type);
{
Mat m = Mat(size, type, pData, step);
m.setTo(cv::Scalar::all(2));
UMat u = m.getUMat(ACCESS_RW);
cv::add(u, cv::Scalar::all(2), u);
Mat d = u.getMat(ACCESS_READ);
Mat expected(m.size(), m.type(), cv::Scalar::all(4));
double norm = cvtest::norm(d, expected, NORM_INF);
EXPECT_EQ(0, norm);
}
delete[] (unsigned char*)pData_allocated;
}
private:
bool useOpenCL;
bool isOpenCL_enabled;
};
TEST_P(getUMat, custom_ptr_align_4Kb)
{
custom_ptr_test(4096, 0);
}
TEST_P(getUMat, custom_ptr_align_64b)
{
custom_ptr_test(4096, 64);
}
TEST_P(getUMat, custom_ptr_align_none)
{
custom_ptr_test(4096, cv::alignSize(CV_ELEM_SIZE(type), 4));
}
TEST_P(getUMat, self_allocated)
{
Mat m = Mat(size, type);
m.setTo(cv::Scalar::all(2));
UMat u = m.getUMat(ACCESS_RW);
cv::add(u, cv::Scalar::all(2), u);
Mat d = u.getMat(ACCESS_READ);
Mat expected(m.size(), m.type(), cv::Scalar::all(4));
double norm = cvtest::norm(d, expected, NORM_INF);
EXPECT_EQ(0, norm);
}
INSTANTIATE_TEST_CASE_P(UMat, getUMat, Combine(
Values(CV_8U, CV_64F), // depth
Values(1, 3), // channels
Values(cv::Size(1, 1), cv::Size(255, 255), cv::Size(256, 256)), // Size
Bool() // useOpenCL
));
///////////////////////////////////////////////////////////////// OpenCL ////////////////////////////////////////////////////////////////////////////
#ifdef HAVE_OPENCL
TEST(UMat, BufferPoolGrowing)
{
#ifdef _DEBUG
const int ITERATIONS = 100;
#else
const int ITERATIONS = 200;
#endif
const Size sz(1920, 1080);
BufferPoolController* c = cv::ocl::getOpenCLAllocator()->getBufferPoolController();
if (c)
{
size_t oldMaxReservedSize = c->getMaxReservedSize();
c->freeAllReservedBuffers();
c->setMaxReservedSize(sz.area() * 10);
for (int i = 0; i < ITERATIONS; i++)
{
UMat um(Size(sz.width + i, sz.height + i), CV_8UC1);
UMat um2(Size(sz.width + 2 * i, sz.height + 2 * i), CV_8UC1);
}
c->setMaxReservedSize(oldMaxReservedSize);
c->freeAllReservedBuffers();
}
else
std::cout << "Skipped, no OpenCL" << std::endl;
}
#endif
class CV_UMatTest :
public cvtest::BaseTest
{
public:
CV_UMatTest() {}
~CV_UMatTest() {}
protected:
void run(int);
struct test_excep
{
test_excep(const string& _s=string("")) : s(_s) { }
string s;
};
bool TestUMat();
void checkDiff(const Mat& m1, const Mat& m2, const string& s)
{
if (cvtest::norm(m1, m2, NORM_INF) != 0)
throw test_excep(s);
}
void checkDiffF(const Mat& m1, const Mat& m2, const string& s)
{
if (cvtest::norm(m1, m2, NORM_INF) > 1e-5)
throw test_excep(s);
}
};
#define STR(a) STR2(a)
#define STR2(a) #a
#define CHECK_DIFF(a, b) checkDiff(a, b, "(" #a ") != (" #b ") at l." STR(__LINE__))
#define CHECK_DIFF_FLT(a, b) checkDiffF(a, b, "(" #a ") !=(eps) (" #b ") at l." STR(__LINE__))
bool CV_UMatTest::TestUMat()
{
try
{
Mat a(100, 100, CV_16SC2), b, c;
randu(a, Scalar::all(-100), Scalar::all(100));
Rect roi(1, 3, 5, 4);
Mat ra(a, roi), rb, rc, rc0;
UMat ua, ura, ub, urb, uc, urc;
a.copyTo(ua);
ua.copyTo(b);
CHECK_DIFF(a, b);
ura = ua(roi);
ura.copyTo(rb);
CHECK_DIFF(ra, rb);
ra += Scalar::all(1.f);
{
Mat temp = ura.getMat(ACCESS_RW);
temp += Scalar::all(1.f);
}
ra.copyTo(rb);
CHECK_DIFF(ra, rb);
b = a.clone();
ra = a(roi);
rb = b(roi);
randu(b, Scalar::all(-100), Scalar::all(100));
b.copyTo(ub);
urb = ub(roi);
/*std::cout << "==============================================\nbefore op (CPU):\n";
std::cout << "ra: " << ra << std::endl;
std::cout << "rb: " << rb << std::endl;*/
ra.copyTo(ura);
rb.copyTo(urb);
ra.release();
rb.release();
ura.copyTo(ra);
urb.copyTo(rb);
/*std::cout << "==============================================\nbefore op (GPU):\n";
std::cout << "ra: " << ra << std::endl;
std::cout << "rb: " << rb << std::endl;*/
cv::max(ra, rb, rc);
cv::max(ura, urb, urc);
urc.copyTo(rc0);
/*std::cout << "==============================================\nafter op:\n";
std::cout << "rc: " << rc << std::endl;
std::cout << "rc0: " << rc0 << std::endl;*/
CHECK_DIFF(rc0, rc);
{
UMat tmp = rc0.getUMat(ACCESS_WRITE);
cv::max(ura, urb, tmp);
}
CHECK_DIFF(rc0, rc);
ura.copyTo(urc);
cv::max(urc, urb, urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
rc = ra ^ rb;
cv::bitwise_xor(ura, urb, urc);
urc.copyTo(rc0);
/*std::cout << "==============================================\nafter op:\n";
std::cout << "ra: " << rc0 << std::endl;
std::cout << "rc: " << rc << std::endl;*/
CHECK_DIFF(rc0, rc);
rc = ra + rb;
cv::add(ura, urb, urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
cv::subtract(ra, Scalar::all(5), rc);
cv::subtract(ura, Scalar::all(5), urc);
urc.copyTo(rc0);
CHECK_DIFF(rc0, rc);
}
catch (const test_excep& e)
{
ts->printf(cvtest::TS::LOG, "%s\n", e.s.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
return true;
}
void CV_UMatTest::run( int /* start_from */)
{
printf("Use OpenCL: %s\nHave OpenCL: %s\n",
cv::ocl::useOpenCL() ? "TRUE" : "FALSE",
cv::ocl::haveOpenCL() ? "TRUE" : "FALSE" );
if (!TestUMat())
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Core_UMat, base) { CV_UMatTest test; test.safe_run(); }
TEST(Core_UMat, getUMat)
{
{
int a[3] = { 1, 2, 3 };
Mat m = Mat(1, 1, CV_32SC3, a);
UMat u = m.getUMat(ACCESS_READ);
EXPECT_NE((void*)NULL, u.u);
}
{
Mat m(10, 10, CV_8UC1), ref;
for (int y = 0; y < m.rows; ++y)
{
uchar * const ptr = m.ptr<uchar>(y);
for (int x = 0; x < m.cols; ++x)
ptr[x] = (uchar)(x + y * 2);
}
ref = m.clone();
Rect r(1, 1, 8, 8);
ref(r).setTo(17);
{
UMat um = m(r).getUMat(ACCESS_WRITE);
um.setTo(17);
}
double err = cvtest::norm(m, ref, NORM_INF);
if (err > 0)
{
std::cout << "m: " << std::endl << m << std::endl;
std::cout << "ref: " << std::endl << ref << std::endl;
}
EXPECT_EQ(0., err);
}
}
#include "test_precomp.hpp"
TEST(Core_UMat, construct_from_vector)
{
std::vector<int> src = {1, 2, 3, 4};
UMat um(src); // copyData parameter is deprecated and ignored
src[0] = 100; // modify source to ensure data was copied
Mat result;
um.copyTo(result);
ASSERT_EQ(4, result.rows);
ASSERT_EQ(1, result.cols);
ASSERT_EQ(CV_32S, result.type());
EXPECT_EQ(1, result.at<int>(0));
EXPECT_EQ(2, result.at<int>(1));
EXPECT_EQ(3, result.at<int>(2));
EXPECT_EQ(4, result.at<int>(3));
}
TEST(UMat, Sync)
{
UMat um(10, 10, CV_8UC1);
{
Mat m = um.getMat(ACCESS_WRITE);
m.setTo(cv::Scalar::all(17));
}
um.setTo(cv::Scalar::all(19));
EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
}
TEST(UMat, SyncTemp)
{
Mat m(10, 10, CV_8UC1);
{
UMat um = m.getUMat(ACCESS_WRITE);
{
Mat m2 = um.getMat(ACCESS_WRITE);
m2.setTo(cv::Scalar::all(17));
}
um.setTo(cv::Scalar::all(19));
EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), cv::Mat(um.size(), um.type(), 19), NORM_INF));
}
}
TEST(UMat, CopyToIfDeviceCopyIsObsolete)
{
UMat um(7, 2, CV_8UC1);
Mat m(um.size(), um.type());
m.setTo(Scalar::all(0));
{
// make obsolete device copy of UMat
Mat temp = um.getMat(ACCESS_WRITE);
temp.setTo(Scalar::all(10));
}
m.copyTo(um);
um.setTo(Scalar::all(17));
EXPECT_EQ(0, cvtest::norm(um.getMat(ACCESS_READ), Mat(um.size(), um.type(), 17), NORM_INF));
}
TEST(UMat, setOpenCL)
{
#ifndef HAVE_OPENCL
return; // test skipped
#else
// save the current state
bool useOCL = cv::ocl::useOpenCL();
Mat m = (Mat_<uchar>(3,3)<<0,1,2,3,4,5,6,7,8);
cv::ocl::setUseOpenCL(true);
UMat um1;
m.copyTo(um1);
cv::ocl::setUseOpenCL(false);
UMat um2;
m.copyTo(um2);
cv::ocl::setUseOpenCL(true);
countNonZero(um1);
countNonZero(um2);
um1.copyTo(um2);
EXPECT_MAT_NEAR(um1, um2, 0);
EXPECT_MAT_NEAR(um1, m, 0);
um2.copyTo(um1);
EXPECT_MAT_NEAR(um1, m, 0);
EXPECT_MAT_NEAR(um1, um2, 0);
cv::ocl::setUseOpenCL(false);
countNonZero(um1);
countNonZero(um2);
um1.copyTo(um2);
EXPECT_MAT_NEAR(um1, um2, 0);
EXPECT_MAT_NEAR(um1, m, 0);
um2.copyTo(um1);
EXPECT_MAT_NEAR(um1, um2, 0);
EXPECT_MAT_NEAR(um1, m, 0);
// reset state to the previous one
cv::ocl::setUseOpenCL(useOCL);
#endif
}
TEST(UMat, ReadBufferRect)
{
UMat m(1, 10000, CV_32FC2, Scalar::all(-1));
Mat t(1, 9000, CV_32FC2, Scalar::all(-200)), t2(1, 9000, CV_32FC2, Scalar::all(-1));
m.colRange(0, 9000).copyTo(t);
EXPECT_MAT_NEAR(t, t2, 0);
}
// Use iGPU or OPENCV_OPENCL_DEVICE=:CPU: to catch problem
TEST(UMat, synchronization_map_unmap)
{
class TestParallelLoopBody : public cv::ParallelLoopBody
{
UMat u_;
public:
TestParallelLoopBody(const UMat& u) : u_(u) { }
void operator() (const cv::Range& range) const
{
printf("range: %d, %d -- begin\n", range.start, range.end);
for (int i = 0; i < 10; i++)
{
printf("%d: %d map...\n", range.start, i);
Mat m = u_.getMat(cv::ACCESS_READ);
printf("%d: %d unmap...\n", range.start, i);
m.release();
}
printf("range: %d, %d -- end\n", range.start, range.end);
}
};
try
{
UMat u(1000, 1000, CV_32FC1, Scalar::all(0));
parallel_for_(cv::Range(0, 2), TestParallelLoopBody(u));
}
catch (const cv::Exception& e)
{
FAIL() << "Exception: " << e.what();
ADD_FAILURE();
}
catch (...)
{
FAIL() << "Exception!";
}
}
TEST(UMat, async_unmap)
{
for (int i = 0; i < 20; i++)
{
try
{
Mat m = Mat(1000, 1000, CV_8UC1, Scalar::all(0));
UMat u = m.getUMat(ACCESS_READ);
UMat dst;
cv::add(u, Scalar::all(0), dst); // start async operation
u.release();
m.release();
}
catch (const cv::Exception& e)
{
printf("i = %d... %s\n", i, e.what());
ADD_FAILURE();
}
catch (...)
{
printf("i = %d...\n", i);
ADD_FAILURE();
}
}
}
TEST(UMat, unmap_in_class)
{
class Logic
{
public:
Logic() {}
void processData(InputArray input)
{
Mat m = input.getMat();
{
Mat dst;
m.convertTo(dst, CV_32FC1);
// some additional CPU-based per-pixel processing into dst
intermediateResult = dst.getUMat(ACCESS_READ); // this violates lifetime of base(dst) / derived (intermediateResult) objects. Use copyTo?
std::cout << "data processed..." << std::endl;
} // problem is here: dst::~Mat()
std::cout << "leave ProcessData()" << std::endl;
}
UMat getResult() const { return intermediateResult; }
protected:
UMat intermediateResult;
};
try
{
Mat m = Mat(1000, 1000, CV_8UC1, Scalar::all(0));
Logic l;
l.processData(m);
UMat result = l.getResult();
}
catch (const cv::Exception& e)
{
printf("exception... %s\n", e.what());
ADD_FAILURE();
}
catch (...)
{
printf("exception... \n");
ADD_FAILURE();
}
}
TEST(UMat, map_unmap_counting)
{
if (!cv::ocl::useOpenCL())
{
std::cout << "OpenCL is not enabled. Skip test" << std::endl;
return;
}
std::cout << "Host memory: " << cv::ocl::Device::getDefault().hostUnifiedMemory() << std::endl;
Mat m(Size(10, 10), CV_8UC1, Scalar::all(0));
UMat um = m.getUMat(ACCESS_RW);
{
Mat d1 = um.getMat(ACCESS_RW);
Mat d2 = um.getMat(ACCESS_RW);
d1.release();
}
void* h = NULL;
EXPECT_NO_THROW(h = um.handle(ACCESS_RW));
std::cout << "Handle: " << h << std::endl;
}
static void process_with_async_cleanup(Mat& frame)
{
UMat blurResult;
{
UMat umat_buffer = frame.getUMat(ACCESS_READ);
cv::blur(umat_buffer, blurResult, Size(3, 3)); // UMat doesn't support inplace, this call is not synchronized
}
Mat result;
blurResult.copyTo(result);
swap(result, frame);
// umat_buffer cleanup is done asynchronously, silence warning about original 'frame' cleanup here (through 'result')
// - release input 'frame' (as 'result')
// - release 'umat_buffer' asynchronously and silence warning about "parent" buffer (in debug builds)
}
TEST(UMat, async_cleanup_without_call_chain_warning)
{
Mat frame(Size(640, 480), CV_8UC1, Scalar::all(128));
for (int i = 0; i < 10; i++)
{
process_with_async_cleanup(frame);
}
}
///////////// oclCleanupCallback threadsafe check (#5062) /////////////////////
// Case 1: reuse of old src Mat in OCL pipe. Hard to catch!
OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_1_VeryLongTest)
{
if (!cv::ocl::useOpenCL())
{
std::cout << "OpenCL is not enabled. Skip test" << std::endl;
return;
}
for (int j = 0; j < 100; j++)
{
const Size srcSize(320, 240);
const int type = CV_8UC1;
const int dtype = CV_16UC1;
Mat src(srcSize, type, Scalar::all(0));
Mat dst_ref(srcSize, dtype);
// Generate reference data as additional check
OCL_OFF(src.convertTo(dst_ref, dtype));
cv::ocl::setUseOpenCL(true); // restore OpenCL state
UMat dst(srcSize, dtype);
// Use multiple iterations to increase chance of data race catching
for(int k = 0; k < 10000; k++)
{
UMat tmpUMat = src.getUMat(ACCESS_RW);
tmpUMat.convertTo(dst, dtype);
::cv::ocl::finish(); // force kernel to complete to start cleanup sooner
}
EXPECT_MAT_NEAR(dst_ref, dst, 1);
printf(".\n"); fflush(stdout);
}
}
// Case 2: concurrent deallocation of UMatData between UMat and Mat deallocators. Hard to catch!
OCL_TEST(UMat, DISABLED_OCL_ThreadSafe_CleanupCallback_2_VeryLongTest)
{
if (!cv::ocl::useOpenCL())
{
std::cout << "OpenCL is not enabled. Skip test" << std::endl;
return;
}
for (int j = 0; j < 100; j++)
{
const Size srcSize(320, 240);
const int type = CV_8UC1;
const int dtype = CV_16UC1;
// This test is only relevant for OCL
UMat dst(srcSize, dtype);
// Use multiple iterations to increase chance of data race catching
for(int k = 0; k < 10000; k++)
{
Mat src(srcSize, type, Scalar::all(0)); // Declare src inside loop now to catch its destruction on stack
{
UMat tmpUMat = src.getUMat(ACCESS_RW);
tmpUMat.convertTo(dst, dtype);
}
::cv::ocl::finish(); // force kernel to complete to start cleanup sooner
}
printf(".\n"); fflush(stdout);
}
}
TEST(UMat, DISABLED_Test_same_behaviour_read_and_read)
{
bool exceptionDetected = false;
try
{
UMat u(Size(10, 10), CV_8UC1, Scalar::all(0));
Mat m = u.getMat(ACCESS_READ);
UMat dst;
cv::add(u, Scalar::all(1), dst);
}
catch (...)
{
exceptionDetected = true;
}
ASSERT_FALSE(exceptionDetected); // no data race, 2+ reads are valid
}
// VP: this test (and probably others from same_behaviour series) is not valid in my opinion.
TEST(UMat, DISABLED_Test_same_behaviour_read_and_write)
{
bool exceptionDetected = false;
try
{
UMat u(Size(10, 10), CV_8UC1, Scalar::all(0));
Mat m = u.getMat(ACCESS_READ);
cv::add(u, Scalar::all(1), u);
}
catch (...)
{
exceptionDetected = true;
}
ASSERT_TRUE(exceptionDetected); // data race
}
TEST(UMat, DISABLED_Test_same_behaviour_write_and_read)
{
bool exceptionDetected = false;
try
{
UMat u(Size(10, 10), CV_8UC1, Scalar::all(0));
Mat m = u.getMat(ACCESS_WRITE);
UMat dst;
cv::add(u, Scalar::all(1), dst);
}
catch (...)
{
exceptionDetected = true;
}
ASSERT_TRUE(exceptionDetected); // data race
}
TEST(UMat, DISABLED_Test_same_behaviour_write_and_write)
{
bool exceptionDetected = false;
try
{
UMat u(Size(10, 10), CV_8UC1, Scalar::all(0));
Mat m = u.getMat(ACCESS_WRITE);
cv::add(u, Scalar::all(1), u);
}
catch (...)
{
exceptionDetected = true;
}
ASSERT_TRUE(exceptionDetected); // data race
}
TEST(UMat, mat_umat_sync)
{
UMat u(10, 10, CV_8UC1, Scalar(1));
{
Mat m = u.getMat(ACCESS_RW).reshape(1);
m.setTo(Scalar(255));
}
UMat uDiff;
cv::compare(u, 255, uDiff, CMP_NE);
ASSERT_EQ(0, countNonZero(uDiff));
}
TEST(UMat, testTempObjects_UMat)
{
UMat u(10, 10, CV_8UC1, Scalar(1));
{
UMat u2 = u.getMat(ACCESS_RW).getUMat(ACCESS_RW);
u2.setTo(Scalar(255));
}
UMat uDiff;
cv::compare(u, 255, uDiff, CMP_NE);
ASSERT_EQ(0, countNonZero(uDiff));
}
TEST(UMat, testTempObjects_Mat)
{
Mat m(10, 10, CV_8UC1, Scalar(1));
{
Mat m2;
ASSERT_ANY_THROW({
// Below is unwrapped version of this invalid expression:
// m2 = m.getUMat(ACCESS_RW).getMat(ACCESS_RW)
UMat u = m.getUMat(ACCESS_RW);
m2 = u.getMat(ACCESS_RW);
u.release();
});
}
}
TEST(UMat, testWrongLifetime_UMat)
{
UMat u(10, 10, CV_8UC1, Scalar(1));
{
UMat u2 = u.getMat(ACCESS_RW).getUMat(ACCESS_RW);
u.release(); // base object
u2.release(); // derived object, should show warning message
}
}
TEST(UMat, testWrongLifetime_Mat)
{
Mat m(10, 10, CV_8UC1, Scalar(1));
{
UMat u = m.getUMat(ACCESS_RW);
Mat m2 = u.getMat(ACCESS_RW);
m.release(); // base object
m2.release(); // map of derived object
u.release(); // derived object, should show warning message
}
}
TEST(UMat, DISABLED_regression_5991)
{
int sz[] = {2,3,2};
UMat mat(3, sz, CV_32F, Scalar(1));
ASSERT_NO_THROW(mat.convertTo(mat, CV_8U));
EXPECT_EQ(sz[0], mat.size[0]);
EXPECT_EQ(sz[1], mat.size[1]);
EXPECT_EQ(sz[2], mat.size[2]);
EXPECT_EQ(0, cvtest::norm(mat.getMat(ACCESS_READ), Mat(3, sz, CV_8U, Scalar(1)), NORM_INF));
}
TEST(UMat, testTempObjects_Mat_issue_8693)
{
UMat srcUMat(3, 4, CV_32FC1);
Mat srcMat;
randu(srcUMat, -1.f, 1.f);
srcUMat.copyTo(srcMat);
reduce(srcUMat, srcUMat, 0, REDUCE_SUM);
reduce(srcMat, srcMat, 0, REDUCE_SUM);
srcUMat.convertTo(srcUMat, CV_64FC1);
srcMat.convertTo(srcMat, CV_64FC1);
EXPECT_EQ(0, cvtest::norm(srcUMat.getMat(ACCESS_READ), srcMat, NORM_INF));
}
TEST(UMat, resize_Mat_issue_13577)
{
// save the current state
bool useOCL = cv::ocl::useOpenCL();
cv::ocl::setUseOpenCL(false);
UMat foo(10, 10, CV_32FC1);
cv::resize(foo, foo, cv::Size(), .5, .5);
cv::ocl::setUseOpenCL(useOCL); // restore state
}
TEST(UMat, exceptions_refcounts_issue_20594)
{
if (!cv::ocl::useOpenCL())
{
// skip test, difficult to create exception scenario without OpenCL
std::cout << "OpenCL is not enabled. Skip test" << std::endl;
return;
}
UMat umat1(10, 10, CV_8UC1);
EXPECT_EQ(0, umat1.u->refcount);
// cause exception in underlying allocator
void* const original_handle = umat1.u->handle;
umat1.u->handle = NULL;
try
{
Mat mat1 = umat1.getMat(ACCESS_RW);
}
catch (...)
{
// nothing
}
// check for correct refcount, and no change of intentional bad handle
EXPECT_EQ(0, umat1.u->refcount);
EXPECT_EQ(NULL, umat1.u->handle);
// reset UMat to good state
umat1.u->refcount = 0;
umat1.u->handle = original_handle;
}
#include "test_precomp.hpp"
} } // namespace opencv_test::ocl
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