Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

502 lines
16 KiB

/*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.
// 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
// 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*/
11 years ago
#include "../test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
///////////////////////////////////////////////////////////////////////////////
PARAM_TEST_CASE(ImgprocTestBase, MatType,
int, // blockSize
int, // border type
bool) // roi or not
{
int type, borderType, blockSize;
bool useRoi;
TEST_DECLARE_INPUT_PARAMETER(src);
TEST_DECLARE_OUTPUT_PARAMETER(dst);
virtual void SetUp()
{
type = GET_PARAM(0);
blockSize = GET_PARAM(1);
borderType = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
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, dst_roi, roiSize, dstBorder, type, 5, 16);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
}
void Near(double threshold = 0.0, bool relative = false)
{
if (relative)
OCL_EXPECT_MATS_NEAR_RELATIVE(dst, threshold);
else
OCL_EXPECT_MATS_NEAR(dst, threshold);
}
};
//////////////////////////////// copyMakeBorder ////////////////////////////////////////////
PARAM_TEST_CASE(CopyMakeBorder, MatDepth, // depth
Channels, // channels
bool, // isolated or not
BorderType, // border type
bool) // roi or not
{
int type, borderType;
bool useRoi;
TestUtils::Border border;
Scalar val;
TEST_DECLARE_INPUT_PARAMETER(src);
TEST_DECLARE_OUTPUT_PARAMETER(dst);
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, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
}
void Near()
{
OCL_EXPECT_MATS_NEAR(dst, 0);
}
};
OCL_TEST_P(CopyMakeBorder, Mat)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
OCL_OFF(cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val));
OCL_ON(cv::copyMakeBorder(usrc_roi, udst_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 < test_loop_times; j++)
{
random_roi();
OCL_OFF(cv::equalizeHist(src_roi, dst_roi));
OCL_ON(cv::equalizeHist(usrc_roi, udst_roi));
Near(1);
}
}
//////////////////////////////// Corners test //////////////////////////////////////////
struct CornerTestBase :
public ImgprocTestBase
{
void random_roi()
{
11 years ago
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, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
}
};
typedef CornerTestBase CornerMinEigenVal;
11 years ago
OCL_TEST_P(CornerMinEigenVal, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
int apertureSize = 3;
OCL_OFF(cv::cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType));
OCL_ON(cv::cornerMinEigenVal(usrc_roi, udst_roi, blockSize, apertureSize, borderType));
// The corner kernel uses native_sqrt() which has implementation defined accuracy.
// If we're using a CL implementation that isn't intel, test with relaxed accuracy.
if (!ocl::useOpenCL() || ocl::Device::getDefault().isIntel())
Near(1e-5, true);
else
Near(0.1, true);
}
}
//////////////////////////////// cornerHarris //////////////////////////////////////////
typedef CornerTestBase CornerHarris;
11 years ago
OCL_TEST_P(CornerHarris, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
int apertureSize = 3;
double k = randomDouble(0.01, 0.9);
OCL_OFF(cv::cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType));
OCL_ON(cv::cornerHarris(usrc_roi, udst_roi, blockSize, apertureSize, k, borderType));
Near(1e-6, true);
}
}
//////////////////////////////// preCornerDetect //////////////////////////////////////////
typedef ImgprocTestBase PreCornerDetect;
OCL_TEST_P(PreCornerDetect, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
const int apertureSize = blockSize;
OCL_OFF(cv::preCornerDetect(src_roi, dst_roi, apertureSize, borderType));
OCL_ON(cv::preCornerDetect(usrc_roi, udst_roi, apertureSize, borderType));
Near(1e-6, true);
}
}
////////////////////////////////// integral /////////////////////////////////////////////////
struct Integral :
public ImgprocTestBase
{
int sdepth, sqdepth;
TEST_DECLARE_OUTPUT_PARAMETER(dst2);
virtual void SetUp()
{
type = GET_PARAM(0);
sdepth = GET_PARAM(1);
sqdepth = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
void random_roi()
{
ASSERT_EQ(CV_MAT_CN(type), 1);
Size roiSize = randomSize(1, MAX_VALUE), isize = Size(roiSize.width + 1, roiSize.height + 1);
Border srcBorder = randomBorder(0, useRoi ? 2 : 0);
randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256);
Border dstBorder = randomBorder(0, useRoi ? 2 : 0);
randomSubMat(dst, dst_roi, isize, dstBorder, sdepth, 5, 16);
Border dst2Border = randomBorder(0, useRoi ? 2 : 0);
randomSubMat(dst2, dst2_roi, isize, dst2Border, sqdepth, 5, 16);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst2);
}
void Near2(double threshold = 0.0, bool relative = false)
{
if (relative)
OCL_EXPECT_MATS_NEAR_RELATIVE(dst2, threshold);
else
OCL_EXPECT_MATS_NEAR(dst2, threshold);
}
};
OCL_TEST_P(Integral, Mat1)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
OCL_OFF(cv::integral(src_roi, dst_roi, sdepth));
OCL_ON(cv::integral(usrc_roi, udst_roi, sdepth));
Near();
}
}
OCL_TEST_P(Integral, Mat2)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
OCL_OFF(cv::integral(src_roi, dst_roi, dst2_roi, sdepth, sqdepth));
OCL_ON(cv::integral(usrc_roi, udst_roi, udst2_roi, sdepth, sqdepth));
Near();
sqdepth == CV_32F ? Near2(1e-6, true) : Near2();
}
}
//////////////////////////////////////// threshold //////////////////////////////////////////////
struct Threshold :
public ImgprocTestBase
{
int thresholdType;
virtual void SetUp()
{
type = GET_PARAM(0);
thresholdType = GET_PARAM(2);
useRoi = GET_PARAM(3);
}
};
OCL_TEST_P(Threshold, Mat)
{
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
double maxVal = randomDouble(20.0, 127.0);
double thresh = randomDouble(0.0, maxVal);
OCL_OFF(cv::threshold(src_roi, dst_roi, thresh, maxVal, thresholdType));
OCL_ON(cv::threshold(usrc_roi, udst_roi, thresh, maxVal, thresholdType));
Near(1);
}
}
/////////////////////////////////////////// CLAHE //////////////////////////////////////////////////
PARAM_TEST_CASE(CLAHETest, Size, double, bool)
{
Size gridSize;
double clipLimit;
bool useRoi;
TEST_DECLARE_INPUT_PARAMETER(src);
TEST_DECLARE_OUTPUT_PARAMETER(dst);
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, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16);
UMAT_UPLOAD_INPUT_PARAMETER(src);
UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
}
void Near(double threshold = 0.0)
{
OCL_EXPECT_MATS_NEAR(dst, threshold);
}
};
OCL_TEST_P(CLAHETest, Accuracy)
{
for (int i = 0; i < test_loop_times; ++i)
{
random_roi();
Ptr<CLAHE> clahe = cv::createCLAHE(clipLimit, gridSize);
OCL_OFF(clahe->apply(src_roi, dst_roi));
OCL_ON(clahe->apply(usrc_roi, udst_roi));
Near(1.0);
}
}
/////////////////////////////////////////////////////////////////////////////////////
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine(
Values((MatType)CV_8UC1),
Values(0), // not used
Values(0), // not used
Bool()));
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CornerMinEigenVal, Combine(
Values((MatType)CV_8UC1, (MatType)CV_32FC1),
Values(3, 5),
Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT101),
Bool()));
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine(
Values((MatType)CV_8UC1, CV_32FC1),
Values(3, 5),
Values( (BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101),
Bool()));
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, PreCornerDetect, Combine(
Values((MatType)CV_8UC1, CV_32FC1),
Values(3, 5),
Values( (BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101),
Bool()));
OCL_INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine(
Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F
Values(CV_32SC1, CV_32FC1), // desired sdepth
Values(CV_32FC1, CV_64FC1), // desired sqdepth
Bool()));
OCL_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()));
OCL_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()));
OCL_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((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE, (BorderType)BORDER_REFLECT,
(BorderType)BORDER_WRAP, (BorderType)BORDER_REFLECT_101),
Bool()));
} } // namespace opencv_test::ocl
#endif // HAVE_OPENCL