Open Source Computer Vision Library https://opencv.org/
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/*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, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
12 years ago
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Niko Li, newlife20080214@gmail.com
// Jia Haipeng, jiahaipeng95@gmail.com
// Shengen Yan, yanshengen@gmail.com
// Jiang Liyuan, lyuan001.good@163.com
// Rock Li, Rock.Li@amd.com
// Wu Zailong, bullet@yeah.net
// Xu Pang, pangxu010@163.com
// Sen Liu, swjtuls1987@126.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
11 years ago
// 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"
#ifdef HAVE_OPENCL
using namespace testing;
using namespace std;
using namespace cv;
///////////////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(ImgprocTestBase, MatType,
int, // blockSize
int, // border type
bool) // roi or not
{
int type, borderType, blockSize;
bool useRoi;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = GET_PARAM(0);
blockSize = GET_PARAM(1);
borderType = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
virtual void random_roi()
{
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, type, 5, 16);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
}
void Near(double threshold = 0.0, bool relative = false)
{
Mat roi, whole;
gdst_whole.download(whole);
gdst_roi.download(roi);
if (relative)
{
EXPECT_MAT_NEAR_RELATIVE(dst_whole, whole, threshold);
EXPECT_MAT_NEAR_RELATIVE(dst_roi, roi, threshold);
}
else
{
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
}
};
////////////////////////////////copyMakeBorder////////////////////////////////////////////
PARAM_TEST_CASE(CopyMakeBorder, MatDepth, // depth
Channels, // channels
bool, // isolated or not
Border, // border type
bool) // roi or not
{
int type, borderType;
bool useRoi;
Border border;
Scalar val;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
type = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
borderType = GET_PARAM(3);
if (GET_PARAM(2))
borderType |= BORDER_ISOLATED;
useRoi = GET_PARAM(4);
}
void random_roi()
{
border = randomBorder(0, MAX_VALUE << 2);
val = randomScalar(-MAX_VALUE, MAX_VALUE);
Size roiSize = randomSize(1, MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, -MAX_VALUE, MAX_VALUE);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
dstBorder.top += border.top;
dstBorder.lef += border.lef;
dstBorder.rig += border.rig;
dstBorder.bot += border.bot;
randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
OCL_TEST_P(CopyMakeBorder, Mat)
{
for (int i = 0; i < LOOP_TIMES; ++i)
{
random_roi();
cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val);
ocl::copyMakeBorder(gsrc_roi, gdst_roi, border.top, border.bot, border.lef, border.rig, borderType, val);
Near();
}
}
////////////////////////////////equalizeHist//////////////////////////////////////////////
typedef ImgprocTestBase EqualizeHist;
OCL_TEST_P(EqualizeHist, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
equalizeHist(src_roi, dst_roi);
ocl::equalizeHist(gsrc_roi, gdst_roi);
Near(1.1);
}
}
////////////////////////////////cornerMinEigenVal//////////////////////////////////////////
struct CornerTestBase :
public ImgprocTestBase
{
virtual void random_roi()
{
Mat image = readImageType("gpu/stereobm/aloe-L.png", type);
ASSERT_FALSE(image.empty());
bool isFP = CV_MAT_DEPTH(type) >= CV_32F;
float val = 255.0f;
if (isFP)
{
image.convertTo(image, -1, 1.0 / 255);
val /= 255.0f;
}
Size roiSize = image.size();
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
Size wholeSize = Size(roiSize.width + srcBorder.lef + srcBorder.rig, roiSize.height + srcBorder.top + srcBorder.bot);
src = randomMat(wholeSize, type, -val, val, false);
src_roi = src(Rect(srcBorder.lef, srcBorder.top, roiSize.width, roiSize.height));
image.copyTo(src_roi);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
}
};
typedef CornerTestBase CornerMinEigenVal;
OCL_TEST_P(CornerMinEigenVal, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
int apertureSize = 3;
cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType);
ocl::cornerMinEigenVal(gsrc_roi, gdst_roi, blockSize, apertureSize, borderType);
Near(1e-5, true);
}
}
////////////////////////////////cornerHarris//////////////////////////////////////////
struct CornerHarris :
public ImgprocTestBase
{
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
absdiff(whole, dst_whole, whole);
absdiff(roi, dst_roi, roi);
divide(whole, dst_whole, whole);
divide(roi, dst_roi, roi);
absdiff(dst_whole, dst_whole, dst_whole);
absdiff(dst_roi, dst_roi, dst_roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
OCL_TEST_P(CornerHarris, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
int apertureSize = 3;
double k = randomDouble(0.01, 0.9);
cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType);
ocl::cornerHarris(gsrc_roi, gdst_roi, blockSize, apertureSize, k, borderType);
Near(1e-5);
}
}
//////////////////////////////////integral/////////////////////////////////////////////////
struct Integral :
public ImgprocTestBase
{
int sdepth;
virtual void SetUp()
{
type = GET_PARAM(0);
blockSize = GET_PARAM(1);
sdepth = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
};
OCL_TEST_P(Integral, Mat1)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
ocl::integral(gsrc_roi, gdst_roi, sdepth);
integral(src_roi, dst_roi, sdepth);
Near();
}
}
OCL_TEST_P(Integral, Mat2)
{
Mat dst1;
ocl::oclMat gdst1;
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
integral(src_roi, dst_roi, dst1, sdepth);
ocl::integral(gsrc_roi, gdst_roi, gdst1, sdepth);
Near();
if(gdst1.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE))
EXPECT_MAT_NEAR(dst1, Mat(gdst1), 0.);
}
}
///////////////////////////////////////////////////////////////////////////////////////////////////
//// threshold
struct Threshold :
public ImgprocTestBase
{
int thresholdType;
virtual void SetUp()
{
type = GET_PARAM(0);
blockSize = GET_PARAM(1);
thresholdType = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
};
OCL_TEST_P(Threshold, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
double maxVal = randomDouble(20.0, 127.0);
double thresh = randomDouble(0.0, maxVal);
threshold(src_roi, dst_roi, thresh, maxVal, thresholdType);
ocl::threshold(gsrc_roi, gdst_roi, thresh, maxVal, thresholdType);
Near(1);
}
}
/////////////////////////////////////////////////////////////////////////////////////////
// calcHist
static void calcHistGold(const Mat &src, Mat &hist)
{
hist = Mat(1, 256, CV_32SC1, Scalar::all(0));
int * const hist_row = hist.ptr<int>();
for (int y = 0; y < src.rows; ++y)
{
const uchar * const src_row = src.ptr(y);
for (int x = 0; x < src.cols; ++x)
++hist_row[src_row[x]];
}
}
typedef ImgprocTestBase CalcHist;
OCL_TEST_P(CalcHist, Mat)
{
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
calcHistGold(src_roi, dst_roi);
ocl::calcHist(gsrc_roi, gdst_roi);
Near();
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////////////
//// CLAHE
PARAM_TEST_CASE(CLAHETest, Size, double, bool)
{
Size gridSize;
double clipLimit;
bool useRoi;
Mat src, dst_whole, src_roi, dst_roi;
ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
virtual void SetUp()
{
gridSize = GET_PARAM(0);
clipLimit = GET_PARAM(1);
useRoi = GET_PARAM(2);
}
void random_roi()
{
Size roiSize = randomSize(std::max(gridSize.height, gridSize.width), MAX_VALUE);
Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, CV_8UC1, 5, 256);
Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(dst_whole, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16);
generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
}
void Near(double threshold = 0.0)
{
Mat whole, roi;
gdst_whole.download(whole);
gdst_roi.download(roi);
EXPECT_MAT_NEAR(dst_whole, whole, threshold);
EXPECT_MAT_NEAR(dst_roi, roi, threshold);
}
};
OCL_TEST_P(CLAHETest, Accuracy)
{
for (int i = 0; i < LOOP_TIMES; ++i)
{
random_roi();
Ptr<CLAHE> clahe = ocl::createCLAHE(clipLimit, gridSize);
clahe->apply(gsrc_roi, gdst_roi);
Ptr<CLAHE> clahe_gold = createCLAHE(clipLimit, gridSize);
clahe_gold->apply(src_roi, dst_roi);
Near(1.0);
}
}
/////////////////////////////Convolve//////////////////////////////////
static void convolve_gold(const Mat & src, const Mat & kernel, Mat & dst)
{
for (int i = 0; i < src.rows; i++)
{
float * const dstptr = dst.ptr<float>(i);
for (int j = 0; j < src.cols; j++)
{
float temp = 0;
for (int m = 0; m < kernel.rows; m++)
{
const float * const kptr = kernel.ptr<float>(m);
for (int n = 0; n < kernel.cols; n++)
{
int r = clipInt(i - kernel.rows / 2 + m, 0, src.rows - 1);
int c = clipInt(j - kernel.cols / 2 + n, 0, src.cols - 1);
temp += src.ptr<float>(r)[c] * kptr[n];
}
}
dstptr[j] = temp;
}
}
}
typedef ImgprocTestBase Convolve;
OCL_TEST_P(Convolve, Mat)
{
Mat kernel, kernel_roi;
ocl::oclMat gkernel, gkernel_roi;
const Size roiSize(7, 7);
for (int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
Border kernelBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
randomSubMat(kernel, kernel_roi, roiSize, kernelBorder, type, 5, 16);
generateOclMat(gkernel, gkernel_roi, kernel, roiSize, kernelBorder);
convolve_gold(src_roi, kernel_roi, dst_roi);
ocl::convolve(gsrc_roi, gkernel_roi, gdst_roi);
Near(1);
}
}
////////////////////////////////// ColumnSum //////////////////////////////////////
static void columnSum_gold(const Mat & src, Mat & dst)
{
float * prevdptr = dst.ptr<float>(0);
const float * sptr = src.ptr<float>(0);
for (int x = 0; x < src.cols; ++x)
prevdptr[x] = sptr[x];
for (int y = 1; y < src.rows; ++y)
{
sptr = src.ptr<float>(y);
float * const dptr = dst.ptr<float>(y);
for (int x = 0; x < src.cols; ++x)
dptr[x] = prevdptr[x] + sptr[x];
prevdptr = dptr;
}
}
typedef ImgprocTestBase ColumnSum;
OCL_TEST_P(ColumnSum, Accuracy)
{
for (int i = 0; i < LOOP_TIMES; ++i)
{
random_roi();
columnSum_gold(src_roi, dst_roi);
ocl::columnSum(gsrc_roi, gdst_roi);
Near(1e-5);
}
}
/////////////////////////////////////////////////////////////////////////////////////
INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine(
Values((MatType)CV_8UC1),
Values(0), // not used
Values(0), // not used
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, CornerMinEigenVal, Combine(
Values((MatType)CV_8UC1, (MatType)CV_32FC1),
Values(3, 5),
Values((int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT101),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine(
Values((MatType)CV_8UC1, CV_32FC1),
Values(3, 5),
Values( (int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT_101),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine(
Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F
Values(0), // not used
Values((MatType)CV_32SC1, (MatType)CV_32FC1),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4,
CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
Values(0),
Values(ThreshOp(THRESH_BINARY),
ThreshOp(THRESH_BINARY_INV), ThreshOp(THRESH_TRUNC),
ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, CalcHist, Combine(
Values((MatType)CV_8UC1),
Values(0), // not used
Values(0), // not used
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, CLAHETest, Combine(
Values(Size(4, 4), Size(32, 8), Size(8, 64)),
Values(0.0, 10.0, 62.0, 300.0),
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, Convolve, Combine(
Values((MatType)CV_32FC1),
Values(0), // not used
Values(0), // not used
Bool()));
INSTANTIATE_TEST_CASE_P(Imgproc, ColumnSum, Combine(
Values(MatType(CV_32FC1)),
Values(0), // not used
Values(0), // not used
Bool()));
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine(
testing::Values((MatDepth)CV_8U, (MatDepth)CV_16S, (MatDepth)CV_32S, (MatDepth)CV_32F),
testing::Values(Channels(1), Channels(3), (Channels)4),
Bool(), // border isolated or not
Values((Border)BORDER_REPLICATE, (Border)BORDER_REFLECT,
(Border)BORDER_WRAP, (Border)BORDER_REFLECT_101),
Bool()));
#endif // HAVE_OPENCL