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Merge branch '2.4'

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This commit is contained in:
Andrey Kamaev
2013-01-25 16:30:36 +04:00
parent 0487067964 d8f749da52
commit f4e27bcbbc
105 changed files with 4821 additions and 2883 deletions
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modules/ocl/test/precomp.hpp
+9
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@@ -38,6 +38,15 @@
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
modules/ocl/test/test_arithm.cpp
+5 -5
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@@ -1110,8 +1110,8 @@ TEST_P(Phase, Mat)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::phase(mat1_roi, mat2_roi, dst_roi, angelInDegrees);
cv::ocl::phase(gmat1, gmat2, gdst, angelInDegrees);
cv::phase(mat1_roi, mat2_roi, dst_roi, angelInDegrees ? true : false);
cv::ocl::phase(gmat1, gmat2, gdst, angelInDegrees ? true : false);
cv::Mat cpu_dst;
gdst_whole.download(cpu_dst);
@@ -1449,8 +1449,8 @@ TEST_P(MagnitudeSqr, Mat)
for(int j = 0; j < LOOP_TIMES; j++)
{
// random_roi();
int64 start, end;
start = cv::getTickCount();
// int64 start, end;
// start = cv::getTickCount();
for(int i = 0; i < mat1.rows; ++i)
for(int j = 0; j < mat1.cols; ++j)
{
@@ -1465,7 +1465,7 @@ TEST_P(MagnitudeSqr, Mat)
// ((float *)(dst.data))[i*dst.step/4 +j]= val1 * val1 +val2 * val2;
}
end = cv::getTickCount();
// end = cv::getTickCount();
modules/ocl/test/test_blend.cpp
+1 -1
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@@ -74,7 +74,7 @@ TEST_P(Blend, Accuracy)
else
blendLinearGold<float>(img1, img2, weights1, weights2, result_gold);
EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1 : 1e-5f, NULL)
EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1.f : 1e-5f, 0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Blend, Combine(
modules/ocl/test/test_color.cpp
+193
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@@ -0,0 +1,193 @@
/*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
// Peng Xiao, pengxiao@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 oclMaterials 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 "precomp.hpp"
#ifdef HAVE_OPENCL
//#define MAT_DEBUG
#ifdef MAT_DEBUG
#define MAT_DIFF(mat, mat2)\
{\
for(int i = 0; i < mat.rows; i ++)\
{\
for(int j = 0; j < mat.cols; j ++)\
{\
cv::Vec4b s = mat.at<cv::Vec4b>(i, j);\
cv::Vec4b s2 = mat2.at<cv::Vec4b>(i, j);\
if(s != s2) printf("*");\
else printf(".");\
}\
puts("\n");\
}\
}
#else
#define MAT_DIFF(mat, mat2)
#endif
namespace
{
///////////////////////////////////////////////////////////////////////////////////////////////////////
// cvtColor
PARAM_TEST_CASE(CvtColor, cv::Size, MatDepth)
{
cv::Size size;
int depth;
bool useRoi;
cv::Mat img;
virtual void SetUp()
{
size = GET_PARAM(0);
depth = GET_PARAM(1);
img = randomMat(size, CV_MAKE_TYPE(depth, 3), 0.0, depth == CV_32F ? 1.0 : 255.0);
}
};
#define CVTCODE(name) cv::COLOR_ ## name
#define TEST_P_CVTCOLOR(name) TEST_P(CvtColor, name)\
{\
cv::Mat src = img;\
cv::ocl::oclMat ocl_img, dst;\
ocl_img.upload(img);\
cv::ocl::cvtColor(ocl_img, dst, CVTCODE(name));\
cv::Mat dst_gold;\
cv::cvtColor(src, dst_gold, CVTCODE(name));\
cv::Mat dst_mat;\
dst.download(dst_mat);\
EXPECT_MAT_NEAR(dst_gold, dst_mat, 1e-5, "");\
}
//add new ones here using macro
TEST_P_CVTCOLOR(RGB2GRAY)
TEST_P_CVTCOLOR(BGR2GRAY)
TEST_P_CVTCOLOR(RGBA2GRAY)
TEST_P_CVTCOLOR(BGRA2GRAY)
TEST_P_CVTCOLOR(RGB2YUV)
TEST_P_CVTCOLOR(BGR2YUV)
TEST_P_CVTCOLOR(YUV2RGB)
TEST_P_CVTCOLOR(YUV2BGR)
TEST_P_CVTCOLOR(RGB2YCrCb)
TEST_P_CVTCOLOR(BGR2YCrCb)
PARAM_TEST_CASE(CvtColor_Gray2RGB, cv::Size, MatDepth, int)
{
cv::Size size;
int code;
int depth;
cv::Mat img;
virtual void SetUp()
{
size = GET_PARAM(0);
depth = GET_PARAM(1);
code = GET_PARAM(2);
img = randomMat(size, CV_MAKETYPE(depth, 1), 0.0, depth == CV_32F ? 1.0 : 255.0);
}
};
TEST_P(CvtColor_Gray2RGB, Accuracy)
{
cv::Mat src = img;
cv::ocl::oclMat ocl_img, dst;
ocl_img.upload(src);
cv::ocl::cvtColor(ocl_img, dst, code);
cv::Mat dst_gold;
cv::cvtColor(src, dst_gold, code);
cv::Mat dst_mat;
dst.download(dst_mat);
EXPECT_MAT_NEAR(dst_gold, dst_mat, 1e-5, "");
}
PARAM_TEST_CASE(CvtColor_YUV420, cv::Size, int)
{
cv::Size size;
int code;
cv::Mat img;
virtual void SetUp()
{
size = GET_PARAM(0);
code = GET_PARAM(1);
img = randomMat(size, CV_8UC1, 0.0, 255.0);
}
};
TEST_P(CvtColor_YUV420, Accuracy)
{
cv::Mat src = img;
cv::ocl::oclMat ocl_img, dst;
ocl_img.upload(src);
cv::ocl::cvtColor(ocl_img, dst, code);
cv::Mat dst_gold;
cv::cvtColor(src, dst_gold, code);
cv::Mat dst_mat;
dst.download(dst_mat);
MAT_DIFF(dst_mat, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst_mat, 1e-5, "");
}
INSTANTIATE_TEST_CASE_P(OCL_ImgProc, CvtColor, testing::Combine(
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32F))
));
INSTANTIATE_TEST_CASE_P(OCL_ImgProc, CvtColor_YUV420, testing::Combine(
testing::Values(cv::Size(128, 45), cv::Size(46, 132), cv::Size(1024, 1023)),
testing::Values((int)CV_YUV2RGBA_NV12, (int)CV_YUV2BGRA_NV12, (int)CV_YUV2RGB_NV12, (int)CV_YUV2BGR_NV12)
));
INSTANTIATE_TEST_CASE_P(OCL_ImgProc, CvtColor_Gray2RGB, testing::Combine(
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32F)),
testing::Values((int)CV_GRAY2BGR, (int)CV_GRAY2BGRA, (int)CV_GRAY2RGB, (int)CV_GRAY2RGBA)
));
}
#endif
modules/ocl/test/test_haar.cpp
+9 -9
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@@ -109,15 +109,15 @@ TEST_F(Haar, FaceDetect)
//double t = 0;
vector<Rect> faces, oclfaces;
const static Scalar colors[] = { CV_RGB(0, 0, 255),
CV_RGB(0, 128, 255),
CV_RGB(0, 255, 255),
CV_RGB(0, 255, 0),
CV_RGB(255, 128, 0),
CV_RGB(255, 255, 0),
CV_RGB(255, 0, 0),
CV_RGB(255, 0, 255)
} ;
// const static Scalar colors[] = { CV_RGB(0, 0, 255),
// CV_RGB(0, 128, 255),
// CV_RGB(0, 255, 255),
// CV_RGB(0, 255, 0),
// CV_RGB(255, 128, 0),
// CV_RGB(255, 255, 0),
// CV_RGB(255, 0, 0),
// CV_RGB(255, 0, 255)
// } ;
Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
MemStorage storage(cvCreateMemStorage(0));
modules/ocl/test/test_imgproc.cpp
+3 -4
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@@ -498,11 +498,11 @@ TEST_P(bilateralFilter, Mat)
}
else
{
for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(size_t i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
if(((bordertype[i] != cv::BORDER_CONSTANT) && (bordertype[i] != cv::BORDER_REPLICATE)) && (mat1_roi.cols <= radius) || (mat1_roi.cols <= radius) || (mat1_roi.rows <= radius) || (mat1_roi.rows <= radius))
if(((bordertype[i] != cv::BORDER_CONSTANT) && (bordertype[i] != cv::BORDER_REPLICATE) && (mat1_roi.cols <= radius)) || (mat1_roi.cols <= radius) || (mat1_roi.rows <= radius) || (mat1_roi.rows <= radius))
{
continue;
}
@@ -563,7 +563,7 @@ TEST_P(CopyMakeBorder, Mat)
}
else
{
for(int i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(size_t i = 0; i < sizeof(bordertype) / sizeof(int); i++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
@@ -911,7 +911,6 @@ PARAM_TEST_CASE(Remap, MatType, MatType, MatType, int, int)
cv::RNG &rng = TS::ptr()->get_rng();
cv::Size srcSize = cv::Size(MWIDTH, MHEIGHT);
cv::Size dstSize = cv::Size(MWIDTH, MHEIGHT);
cv::Size map1Size = cv::Size(MWIDTH, MHEIGHT);
double min = 5, max = 16;
modules/ocl/test/test_match_template.cpp
+2 -2
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@@ -100,7 +100,7 @@ TEST_P(MatchTemplate8U, Accuracy)
EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
#if PERF_TEST
#ifdef PERF_TEST
{
P_TEST_FULL( {}, {cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);}, {});
P_TEST_FULL( {}, {cv::matchTemplate(image, templ, dst_gold, method);}, {});
@@ -145,7 +145,7 @@ TEST_P(MatchTemplate32F, Accuracy)
EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
#if PERF_TEST
#ifdef PERF_TEST
{
std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
modules/ocl/test/test_pyrlk.cpp
+5 -5
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@@ -118,9 +118,9 @@ TEST_P(Sparse, Mat)
cv::Mat status_mat(1, d_status.cols, CV_8UC1, (void *)&status[0]);
d_status.download(status_mat);
//std::vector<float> err(d_err.cols);
//cv::Mat err_mat(1, d_err.cols, CV_32FC1, (void*)&err[0]);
//d_err.download(err_mat);
std::vector<float> err(d_err.cols);
cv::Mat err_mat(1, d_err.cols, CV_32FC1, (void*)&err[0]);
d_err.download(err_mat);
std::vector<cv::Point2f> nextPts_gold;
std::vector<unsigned char> status_gold;
@@ -153,9 +153,9 @@ TEST_P(Sparse, Mat)
}
}
double bad_ratio = static_cast<double>(mistmatch) / (nextPts.size() * 2);
double bad_ratio = static_cast<double>(mistmatch) / (nextPts.size());
ASSERT_LE(bad_ratio, 0.05f);
ASSERT_LE(bad_ratio, 0.02f);
}
modules/ocl/test/utility.hpp
+6 -6
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@@ -76,12 +76,12 @@ double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
EXPECT_LE(checkNorm(cv::Mat(mat)), eps) \
}
//#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
//{ \
// ASSERT_EQ(mat1.type(), mat2.type()); \
// ASSERT_EQ(mat1.size(), mat2.size()); \
// EXPECT_LE(checkNorm(cv::Mat(mat1), cv::Mat(mat2)), eps); \
//}
/*#define EXPECT_MAT_NEAR(mat1, mat2, eps) \
{ \
ASSERT_EQ(mat1.type(), mat2.type()); \
ASSERT_EQ(mat1.size(), mat2.size()); \
EXPECT_LE(checkNorm(cv::Mat(mat1), cv::Mat(mat2)), eps); \
}*/
#define EXPECT_MAT_NEAR(mat1, mat2, eps,s) \
{ \