mirror of
https://github.com/opencv/opencv.git
synced 2024-11-30 06:10:02 +08:00
498 lines
16 KiB
C++
498 lines
16 KiB
C++
/*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*/
|
|
|
|
#include "../test_precomp.hpp"
|
|
#include "cvconfig.h"
|
|
#include "opencv2/ts/ocl_test.hpp"
|
|
|
|
#ifdef HAVE_OPENCL
|
|
|
|
namespace cvtest {
|
|
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()
|
|
{
|
|
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;
|
|
|
|
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));
|
|
|
|
Near(1e-5, true);
|
|
}
|
|
}
|
|
|
|
//////////////////////////////// cornerHarris //////////////////////////////////////////
|
|
|
|
typedef CornerTestBase CornerHarris;
|
|
|
|
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 cvtest::ocl
|
|
|
|
#endif // HAVE_OPENCL
|