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Commit 77bbd65f authored by Andrey Pavlenko's avatar Andrey Pavlenko Committed by OpenCV Buildbot
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Merge pull request #2220 from ilya-lavrenov:tapi_accumulate

parents 66cc440c 0d19cbcc
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Showing with 561 additions and 26 deletions
modules/core/include/opencv2/core/opencl/ocl_defs.hpp
View file @ 77bbd65f
......@@ -22,6 +22,15 @@
fflush(stdout); \
} \
}
#elif defined CV_OPENCL_RUN_ASSERT
#define CV_OCL_RUN_(condition, func, ...) \
{ \
if (cv::ocl::useOpenCL() && (condition)) \
{ \
CV_Assert(func); \
return; \
} \
}
#else
#define CV_OCL_RUN_(condition, func, ...) \
if (cv::ocl::useOpenCL() && (condition) && func) \
......
modules/imgproc/perf/opencl/perf_accumulate.cpp 0 → 100644
View file @ 77bbd65f
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// 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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Nathan, liujun@multicorewareinc.com
//
// 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 Intel Corporation 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
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
/////////////////////////////////// Accumulate ///////////////////////////////////
typedef Size_MatType AccumulateFixture;
OCL_PERF_TEST_P(AccumulateFixture, Accumulate,
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
{
Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int srcType = get<1>(params), cn = CV_MAT_CN(srcType), dstType = CV_32FC(cn);
checkDeviceMaxMemoryAllocSize(srcSize, dstType);
UMat src(srcSize, srcType), dst(srcSize, dstType);
declare.in(src, dst, WARMUP_RNG).out(dst);
OCL_TEST_CYCLE() cv::accumulate(src, dst);
SANITY_CHECK_NOTHING();
}
/////////////////////////////////// AccumulateSquare ///////////////////////////////////
typedef Size_MatType AccumulateSquareFixture;
OCL_PERF_TEST_P(AccumulateSquareFixture, AccumulateSquare,
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
{
Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int srcType = get<1>(params), cn = CV_MAT_CN(srcType), dstType = CV_32FC(cn);
checkDeviceMaxMemoryAllocSize(srcSize, dstType);
UMat src(srcSize, srcType), dst(srcSize, dstType);
declare.in(src, dst, WARMUP_RNG);
OCL_TEST_CYCLE() cv::accumulateSquare(src, dst);
SANITY_CHECK_NOTHING();
}
/////////////////////////////////// AccumulateProduct ///////////////////////////////////
typedef Size_MatType AccumulateProductFixture;
OCL_PERF_TEST_P(AccumulateProductFixture, AccumulateProduct,
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
{
Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int srcType = get<1>(params), cn = CV_MAT_CN(srcType), dstType = CV_32FC(cn);
checkDeviceMaxMemoryAllocSize(srcSize, dstType);
UMat src1(srcSize, srcType), src2(srcSize, srcType), dst(srcSize, dstType);
declare.in(src1, src2, dst, WARMUP_RNG);
OCL_TEST_CYCLE() cv::accumulateProduct(src1, src2, dst);
SANITY_CHECK_NOTHING();
}
/////////////////////////////////// AccumulateWeighted ///////////////////////////////////
typedef Size_MatType AccumulateWeightedFixture;
OCL_PERF_TEST_P(AccumulateWeightedFixture, AccumulateWeighted,
::testing::Combine(OCL_TEST_SIZES, OCL_TEST_TYPES))
{
Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int srcType = get<1>(params), cn = CV_MAT_CN(srcType), dstType = CV_32FC(cn);
checkDeviceMaxMemoryAllocSize(srcSize, dstType);
UMat src(srcSize, srcType), dst(srcSize, dstType);
declare.in(src, dst, WARMUP_RNG);
OCL_TEST_CYCLE() cv::accumulateWeighted(src, dst, 2.0);
SANITY_CHECK_NOTHING();
}
} } // namespace cvtest::ocl
#endif
modules/imgproc/src/accum.cpp
View file @ 77bbd65f
......@@ -41,6 +41,7 @@
//M*/
#include "precomp.hpp"
#include "opencl_kernels.hpp"
namespace cv
{
......@@ -352,15 +353,83 @@ inline int getAccTabIdx(int sdepth, int ddepth)
sdepth == CV_64F && ddepth == CV_64F ? 6 : -1;
}
#ifdef HAVE_OPENCL
enum
{
ACCUMULATE = 0,
ACCUMULATE_SQUARE = 1,
ACCUMULATE_PRODUCT = 2,
ACCUMULATE_WEIGHTED = 3
};
static bool ocl_accumulate( InputArray _src, InputArray _src2, InputOutputArray _dst, double alpha,
InputArray _mask, int op_type )
{
CV_Assert(op_type == ACCUMULATE || op_type == ACCUMULATE_SQUARE ||
op_type == ACCUMULATE_PRODUCT || op_type == ACCUMULATE_WEIGHTED);
int stype = _src.type(), cn = CV_MAT_CN(stype);
int sdepth = CV_MAT_DEPTH(stype), ddepth = _dst.depth();
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0,
haveMask = !_mask.empty();
if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
return false;
const char * const opMap[4] = { "ACCUMULATE", "ACCUMULATE_SQUARE", "ACCUMULATE_PRODUCT",
"ACCUMULATE_WEIGHTED" };
ocl::Kernel k("accumulate", ocl::imgproc::accumulate_oclsrc,
format("-D %s%s -D srcT=%s -D cn=%d -D dstT=%s%s",
opMap[op_type], haveMask ? " -D HAVE_MASK" : "",
ocl::typeToStr(sdepth), cn, ocl::typeToStr(ddepth),
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
UMat src = _src.getUMat(), src2 = _src2.getUMat(), dst = _dst.getUMat(), mask = _mask.getUMat();
ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src),
src2arg = ocl::KernelArg::ReadOnlyNoSize(src2),
dstarg = ocl::KernelArg::ReadWrite(dst),
maskarg = ocl::KernelArg::ReadOnlyNoSize(mask);
int argidx = k.set(0, srcarg);
if (op_type == ACCUMULATE_PRODUCT)
argidx = k.set(argidx, src2arg);
argidx = k.set(argidx, dstarg);
if (op_type == ACCUMULATE_WEIGHTED)
{
if (ddepth == CV_32F)
argidx = k.set(argidx, (float)alpha);
else
argidx = k.set(argidx, alpha);
}
if (haveMask)
argidx = k.set(argidx, maskarg);
size_t globalsize[2] = { src.cols, src.rows };
return k.run(2, globalsize, NULL, false);
}
#endif
}
void cv::accumulate( InputArray _src, InputOutputArray _dst, InputArray _mask )
{
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, 0.0, _mask, ACCUMULATE))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accTab[fidx] : 0;
......@@ -372,17 +441,21 @@ void cv::accumulate( InputArray _src, InputOutputArray _dst, InputArray _mask )
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
func(ptrs[0], ptrs[1], ptrs[2], len, scn);
}
void cv::accumulateSquare( InputArray _src, InputOutputArray _dst, InputArray _mask )
{
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, 0.0, _mask, ACCUMULATE_SQUARE))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accSqrTab[fidx] : 0;
......@@ -394,18 +467,23 @@ void cv::accumulateSquare( InputArray _src, InputOutputArray _dst, InputArray _m
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
func(ptrs[0], ptrs[1], ptrs[2], len, scn);
}
void cv::accumulateProduct( InputArray _src1, InputArray _src2,
InputOutputArray _dst, InputArray _mask )
{
Mat src1 = _src1.getMat(), src2 = _src2.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src1.depth(), ddepth = dst.depth(), cn = src1.channels();
int stype = _src1.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src1.sameSize(_src2) && stype == _src2.type() );
CV_Assert( _src1.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src1.sameSize(_mask) && _mask.type() == CV_8U) );
CV_Assert( src2.size && src1.size && src2.type() == src1.type() );
CV_Assert( dst.size == src1.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src1.size && mask.type() == CV_8U) );
CV_OCL_RUN(_src1.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src1, _src2, _dst, 0.0, _mask, ACCUMULATE_PRODUCT))
Mat src1 = _src1.getMat(), src2 = _src2.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int fidx = getAccTabIdx(sdepth, ddepth);
AccProdFunc func = fidx >= 0 ? accProdTab[fidx] : 0;
......@@ -417,18 +495,22 @@ void cv::accumulateProduct( InputArray _src1, InputArray _src2,
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], ptrs[3], len, cn);
func(ptrs[0], ptrs[1], ptrs[2], ptrs[3], len, scn);
}
void cv::accumulateWeighted( InputArray _src, InputOutputArray _dst,
double alpha, InputArray _mask )
{
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
int stype = _src.type(), sdepth = CV_MAT_DEPTH(stype), scn = CV_MAT_CN(stype);
int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), dcn = CV_MAT_CN(dtype);
CV_Assert( _src.sameSize(_dst) && dcn == scn );
CV_Assert( _mask.empty() || (_src.sameSize(_mask) && _mask.type() == CV_8U) );
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
ocl_accumulate(_src, noArray(), _dst, alpha, _mask, ACCUMULATE_WEIGHTED))
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int fidx = getAccTabIdx(sdepth, ddepth);
AccWFunc func = fidx >= 0 ? accWTab[fidx] : 0;
......@@ -440,7 +522,7 @@ void cv::accumulateWeighted( InputArray _src, InputOutputArray _dst,
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn, alpha);
func(ptrs[0], ptrs[1], ptrs[2], len, scn, alpha);
}
......
modules/imgproc/src/opencl/accumulate.cl 0 → 100644
View file @ 77bbd65f
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
#ifdef DOUBLE_SUPPORT
#ifdef cl_amd_fp64
#pragma OPENCL EXTENSION cl_amd_fp64:enable
#elif defined (cl_khr_fp64)
#pragma OPENCL EXTENSION cl_khr_fp64:enable
#endif
#endif
__kernel void accumulate(__global const uchar * srcptr, int src_step, int src_offset,
#ifdef ACCUMULATE_PRODUCT
__global const uchar * src2ptr, int src2_step, int src2_offset,
#endif
__global uchar * dstptr, int dst_step, int dst_offset, int dst_rows, int dst_cols
#ifdef ACCUMULATE_WEIGHTED
, dstT alpha
#endif
#ifdef HAVE_MASK
, __global const uchar * mask, int mask_step, int mask_offset
#endif
)
{
int x = get_global_id(0);
int y = get_global_id(1);
if (x < dst_cols && y < dst_rows)
{
int src_index = mad24(y, src_step, src_offset + x * cn * (int)sizeof(srcT));
#ifdef HAVE_MASK
int mask_index = mad24(y, mask_step, mask_offset + x);
mask += mask_index;
#endif
int dst_index = mad24(y, dst_step, dst_offset + x * cn * (int)sizeof(dstT));
__global const srcT * src = (__global const srcT *)(srcptr + src_index);
#ifdef ACCUMULATE_PRODUCT
int src2_index = mad24(y, src2_step, src2_offset + x * cn * (int)sizeof(srcT));
__global const srcT * src2 = (__global const srcT *)(src2ptr + src2_index);
#endif
__global dstT * dst = (__global dstT *)(dstptr + dst_index);
#pragma unroll
for (int c = 0; c < cn; ++c)
#ifdef HAVE_MASK
if (mask[0])
#endif
#ifdef ACCUMULATE
dst[c] += src[c];
#elif defined ACCUMULATE_SQUARE
dst[c] += src[c] * src[c];
#elif defined ACCUMULATE_PRODUCT
dst[c] += src[c] * src2[c];
#elif defined ACCUMULATE_WEIGHTED
dst[c] = (1 - alpha) * dst[c] + src[c] * alpha;
#else
#error "Unknown accumulation type"
#endif
}
}
modules/imgproc/test/ocl/test_accumulate.cpp 0 → 100644
View file @ 77bbd65f
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// 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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Nathan, liujun@multicorewareinc.com
//
// 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 Intel Corporation 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
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
#include "cvconfig.h"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
PARAM_TEST_CASE(AccumulateBase, std::pair<MatDepth, MatDepth>, Channels, bool)
{
int sdepth, ddepth, channels;
bool useRoi;
double alpha;
TEST_DECLARE_INPUT_PARAMETER(src)
TEST_DECLARE_INPUT_PARAMETER(mask)
TEST_DECLARE_INPUT_PARAMETER(src2)
TEST_DECLARE_OUTPUT_PARAMETER(dst)
virtual void SetUp()
{
const std::pair<MatDepth, MatDepth> depths = GET_PARAM(0);
sdepth = depths.first, ddepth = depths.second;
channels = GET_PARAM(1);
useRoi = GET_PARAM(2);
}
void random_roi()
{
const int stype = CV_MAKE_TYPE(sdepth, channels),
dtype = CV_MAKE_TYPE(ddepth, channels);
Size roiSize = randomSize(1, 10);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, stype, -MAX_VALUE, MAX_VALUE);
Border maskBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(mask, mask_roi, roiSize, maskBorder, CV_8UC1, -MAX_VALUE, MAX_VALUE);
threshold(mask, mask, 80, 255, THRESH_BINARY);
Border src2Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src2, src2_roi, roiSize, src2Border, stype, -MAX_VALUE, MAX_VALUE);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst, dst_roi, roiSize, dstBorder, dtype, -MAX_VALUE, MAX_VALUE);
UMAT_UPLOAD_INPUT_PARAMETER(src)
UMAT_UPLOAD_INPUT_PARAMETER(mask)
UMAT_UPLOAD_INPUT_PARAMETER(src2)
UMAT_UPLOAD_OUTPUT_PARAMETER(dst)
alpha = randomDouble(-5, 5);
}
};
/////////////////////////////////// Accumulate ///////////////////////////////////
typedef AccumulateBase Accumulate;
OCL_TEST_P(Accumulate, Mat)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulate(src_roi, dst_roi));
OCL_ON(cv::accumulate(usrc_roi, udst_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-6);
}
}
OCL_TEST_P(Accumulate, Mask)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulate(src_roi, dst_roi, mask_roi));
OCL_ON(cv::accumulate(usrc_roi, udst_roi, umask_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-6);
}
}
/////////////////////////////////// AccumulateSquare ///////////////////////////////////
typedef AccumulateBase AccumulateSquare;
OCL_TEST_P(AccumulateSquare, Mat)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateSquare(src_roi, dst_roi));
OCL_ON(cv::accumulateSquare(usrc_roi, udst_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
OCL_TEST_P(AccumulateSquare, Mask)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateSquare(src_roi, dst_roi, mask_roi));
OCL_ON(cv::accumulateSquare(usrc_roi, udst_roi, umask_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
/////////////////////////////////// AccumulateProduct ///////////////////////////////////
typedef AccumulateBase AccumulateProduct;
OCL_TEST_P(AccumulateProduct, Mat)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateProduct(src_roi, src2_roi, dst_roi));
OCL_ON(cv::accumulateProduct(usrc_roi, usrc2_roi, udst_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
OCL_TEST_P(AccumulateProduct, Mask)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateProduct(src_roi, src2_roi, dst_roi, mask_roi));
OCL_ON(cv::accumulateProduct(usrc_roi, usrc2_roi, udst_roi, umask_roi));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
/////////////////////////////////// AccumulateWeighted ///////////////////////////////////
typedef AccumulateBase AccumulateWeighted;
OCL_TEST_P(AccumulateWeighted, Mat)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateWeighted(src_roi, dst_roi, alpha));
OCL_ON(cv::accumulateWeighted(usrc_roi, udst_roi, alpha));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
OCL_TEST_P(AccumulateWeighted, Mask)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::accumulateWeighted(src_roi, dst_roi, alpha));
OCL_ON(cv::accumulateWeighted(usrc_roi, udst_roi, alpha));
OCL_EXPECT_MATS_NEAR(dst, 1e-2);
}
}
/////////////////////////////////// Instantiation ///////////////////////////////////
#define OCL_DEPTH_ALL_COMBINATIONS \
testing::Values(std::make_pair<MatDepth, MatDepth>(CV_8U, CV_32F), \
std::make_pair<MatDepth, MatDepth>(CV_16U, CV_32F), \
std::make_pair<MatDepth, MatDepth>(CV_32F, CV_32F), \
std::make_pair<MatDepth, MatDepth>(CV_8U, CV_64F), \
std::make_pair<MatDepth, MatDepth>(CV_16U, CV_64F), \
std::make_pair<MatDepth, MatDepth>(CV_32F, CV_64F), \
std::make_pair<MatDepth, MatDepth>(CV_64F, CV_64F))
OCL_INSTANTIATE_TEST_CASE_P(ImgProc, Accumulate, Combine(OCL_DEPTH_ALL_COMBINATIONS, OCL_ALL_CHANNELS, Bool()));
OCL_INSTANTIATE_TEST_CASE_P(ImgProc, AccumulateSquare, Combine(OCL_DEPTH_ALL_COMBINATIONS, OCL_ALL_CHANNELS, Bool()));
OCL_INSTANTIATE_TEST_CASE_P(ImgProc, AccumulateProduct, Combine(OCL_DEPTH_ALL_COMBINATIONS, OCL_ALL_CHANNELS, Bool()));
OCL_INSTANTIATE_TEST_CASE_P(ImgProc, AccumulateWeighted, Combine(OCL_DEPTH_ALL_COMBINATIONS, OCL_ALL_CHANNELS, Bool()));
} } // namespace cvtest::ocl
#endif
modules/imgproc/test/ocl/test_blend.cpp
View file @ 77bbd65f
......@@ -75,7 +75,7 @@ PARAM_TEST_CASE(BlendLinear, MatDepth, Channels, bool)
const int type = CV_MAKE_TYPE(depth, channels);
const double upValue = 256;
Size roiSize = randomSize(1, 20);
Size roiSize = randomSize(1, MAX_VALUE);
Border src1Border = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src1, src1_roi, roiSize, src1Border, type, -upValue, upValue);
......@@ -104,8 +104,7 @@ PARAM_TEST_CASE(BlendLinear, MatDepth, Channels, bool)
void Near(double eps = 0.0)
{
EXPECT_MAT_NEAR(dst, udst, eps);
EXPECT_MAT_NEAR(dst_roi, udst_roi, eps);
OCL_EXPECT_MATS_NEAR(dst, eps)
}
};
......
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