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Normalize line endings and whitespace

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This commit is contained in:
OpenCV Buildbot
2012-10-17 03:18:30 +04:00
committed by Andrey Kamaev
parent 69020da607
commit 04384a71e4
1516 changed files with 258846 additions and 258162 deletions
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modules/imgproc/include/opencv2/imgproc/imgproc_c.h
+1 -1
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@@ -67,7 +67,7 @@ CVAPI(void) cvMultiplyAcc( const CvArr* image1, const CvArr* image2, CvArr* acc
/* Adds image to accumulator with weights: acc = acc*(1-alpha) + image*alpha */
CVAPI(void) cvRunningAvg( const CvArr* image, CvArr* acc, double alpha,
const CvArr* mask CV_DEFAULT(NULL) );
/****************************************************************************************\
* Image Processing *
\****************************************************************************************/
modules/imgproc/perf/perf_bilateral.cpp
+38 -38
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@@ -1,38 +1,38 @@
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using namespace testing;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(Mat_Type, CV_8UC1, CV_8UC3, CV_32FC1, CV_32FC3)
typedef TestBaseWithParam< tr1::tuple<Size, int, Mat_Type> > TestBilateralFilter;
PERF_TEST_P( TestBilateralFilter, BilateralFilter,
Combine(
Values( szVGA, sz1080p ), // image size
Values( 3, 5 ), // d
ValuesIn( Mat_Type::all() ) // image type
)
)
{
Size sz;
int d, type;
const double sigmaColor = 1., sigmaSpace = 1.;
sz = get<0>(GetParam());
d = get<1>(GetParam());
type = get<2>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst).time(20);
TEST_CYCLE() bilateralFilter(src, dst, d, sigmaColor, sigmaSpace, BORDER_DEFAULT);
SANITY_CHECK(dst);
}
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using namespace testing;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(Mat_Type, CV_8UC1, CV_8UC3, CV_32FC1, CV_32FC3)
typedef TestBaseWithParam< tr1::tuple<Size, int, Mat_Type> > TestBilateralFilter;
PERF_TEST_P( TestBilateralFilter, BilateralFilter,
Combine(
Values( szVGA, sz1080p ), // image size
Values( 3, 5 ), // d
ValuesIn( Mat_Type::all() ) // image type
)
)
{
Size sz;
int d, type;
const double sigmaColor = 1., sigmaSpace = 1.;
sz = get<0>(GetParam());
d = get<1>(GetParam());
type = get<2>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst).time(20);
TEST_CYCLE() bilateralFilter(src, dst, d, sigmaColor, sigmaSpace, BORDER_DEFAULT);
SANITY_CHECK(dst);
}
modules/imgproc/perf/perf_cornerEigenValsAndVecs.cpp
+1 -1
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@@ -28,7 +28,7 @@ PERF_TEST_P(Img_BlockSize_ApertureSize_BorderType, cornerEigenValsAndVecs,
Mat src = imread(filename, IMREAD_GRAYSCALE);
if (src.empty())
FAIL() << "Unable to load source image" << filename;
Mat dst;
TEST_CYCLE() cornerEigenValsAndVecs(src, dst, blockSize, apertureSize, borderType);
modules/imgproc/perf/perf_cornerHarris.cpp
+1 -1
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@@ -30,7 +30,7 @@ PERF_TEST_P(Img_BlockSize_ApertureSize_k_BorderType, cornerHarris,
Mat src = imread(filename, IMREAD_GRAYSCALE);
if (src.empty())
FAIL() << "Unable to load source image" << filename;
Mat dst;
TEST_CYCLE() cornerHarris(src, dst, blockSize, apertureSize, k, borderType);
modules/imgproc/perf/perf_filter2d.cpp
+76 -76
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@@ -1,76 +1,76 @@
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using namespace testing;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT_101);
typedef TestBaseWithParam< tr1::tuple<Size, int, BorderMode> > TestFilter2d;
typedef TestBaseWithParam< tr1::tuple<String, int> > Image_KernelSize;
PERF_TEST_P( TestFilter2d, Filter2d,
Combine(
Values( Size(320, 240), szVGA, sz720p, sz1080p ),
Values( 3, 5 ),
ValuesIn( BorderMode::all() )
)
)
{
Size sz;
int borderMode, kSize;
sz = get<0>(GetParam());
kSize = get<1>(GetParam());
borderMode = get<2>(GetParam());
Mat src(sz, CV_8UC4);
Mat dst(sz, CV_8UC4);
Mat kernel(kSize, kSize, CV_32FC1);
randu(kernel, -3, 10);
double s = fabs( sum(kernel)[0] );
if(s > 1e-3) kernel /= s;
declare.in(src, WARMUP_RNG).out(dst).time(20);
TEST_CYCLE() filter2D(src, dst, CV_8UC4, kernel, Point(1, 1), 0., borderMode);
SANITY_CHECK(dst);
}
PERF_TEST_P( Image_KernelSize, GaborFilter2d,
Combine(
Values("stitching/a1.png", "cv/shared/pic5.png"),
Values(16, 32, 64) )
)
{
String fileName = getDataPath(get<0>(GetParam()));
Mat sourceImage = imread(fileName, IMREAD_GRAYSCALE);
if( sourceImage.empty() )
{
FAIL() << "Unable to load source image" << fileName;
}
int kernelSize = get<1>(GetParam());
double sigma = 4;
double lambda = 11;
double theta = 47;
double gamma = 0.5;
Mat gaborKernel = getGaborKernel(Size(kernelSize, kernelSize), sigma, theta, lambda, gamma);
Mat filteredImage;
declare.in(sourceImage);
TEST_CYCLE()
{
filter2D(sourceImage, filteredImage, CV_32F, gaborKernel);
}
SANITY_CHECK(filteredImage);
}
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using namespace testing;
using std::tr1::make_tuple;
using std::tr1::get;
CV_ENUM(BorderMode, BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT_101);
typedef TestBaseWithParam< tr1::tuple<Size, int, BorderMode> > TestFilter2d;
typedef TestBaseWithParam< tr1::tuple<String, int> > Image_KernelSize;
PERF_TEST_P( TestFilter2d, Filter2d,
Combine(
Values( Size(320, 240), szVGA, sz720p, sz1080p ),
Values( 3, 5 ),
ValuesIn( BorderMode::all() )
)
)
{
Size sz;
int borderMode, kSize;
sz = get<0>(GetParam());
kSize = get<1>(GetParam());
borderMode = get<2>(GetParam());
Mat src(sz, CV_8UC4);
Mat dst(sz, CV_8UC4);
Mat kernel(kSize, kSize, CV_32FC1);
randu(kernel, -3, 10);
double s = fabs( sum(kernel)[0] );
if(s > 1e-3) kernel /= s;
declare.in(src, WARMUP_RNG).out(dst).time(20);
TEST_CYCLE() filter2D(src, dst, CV_8UC4, kernel, Point(1, 1), 0., borderMode);
SANITY_CHECK(dst);
}
PERF_TEST_P( Image_KernelSize, GaborFilter2d,
Combine(
Values("stitching/a1.png", "cv/shared/pic5.png"),
Values(16, 32, 64) )
)
{
String fileName = getDataPath(get<0>(GetParam()));
Mat sourceImage = imread(fileName, IMREAD_GRAYSCALE);
if( sourceImage.empty() )
{
FAIL() << "Unable to load source image" << fileName;
}
int kernelSize = get<1>(GetParam());
double sigma = 4;
double lambda = 11;
double theta = 47;
double gamma = 0.5;
Mat gaborKernel = getGaborKernel(Size(kernelSize, kernelSize), sigma, theta, lambda, gamma);
Mat filteredImage;
declare.in(sourceImage);
TEST_CYCLE()
{
filter2D(sourceImage, filteredImage, CV_32F, gaborKernel);
}
SANITY_CHECK(filteredImage);
}
modules/imgproc/perf/perf_houghLines.cpp
+3 -3
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@@ -16,7 +16,7 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
testing::Values( "cv/shared/pic5.png", "stitching/a1.png" ),
testing::Values( 1, 10 ),
testing::Values( 0.01, 0.1 ),
testing::Values( 300, 500 )
testing::Values( 300, 500 )
)
)
{
@@ -28,9 +28,9 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
Mat image = imread(filename, IMREAD_GRAYSCALE);
if (image.empty())
FAIL() << "Unable to load source image" << filename;
Canny(image, image, 0, 0);
Mat lines;
declare.time(7);
modules/imgproc/perf/perf_integral.cpp
+82 -82
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@@ -1,82 +1,82 @@
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
typedef std::tr1::tuple<Size, MatType, MatDepth> Size_MatType_OutMatDepth_t;
typedef perf::TestBaseWithParam<Size_MatType_OutMatDepth_t> Size_MatType_OutMatDepth;
PERF_TEST_P(Size_MatType_OutMatDepth, integral,
testing::Combine(
testing::Values(TYPICAL_MAT_SIZES),
testing::Values(CV_8UC1, CV_8UC4),
testing::Values(CV_32S, CV_32F, CV_64F)
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum);
TEST_CYCLE() integral(src, sum, sdepth);
SANITY_CHECK(sum, 1e-6);
}
PERF_TEST_P(Size_MatType_OutMatDepth, integral_sqsum,
testing::Combine(
testing::Values(TYPICAL_MAT_SIZES),
testing::Values(CV_8UC1, CV_8UC4),
testing::Values(CV_32S, CV_32F, CV_64F)
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
Mat sqsum(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum, sqsum);
TEST_CYCLE() integral(src, sum, sqsum, sdepth);
SANITY_CHECK(sum, 1e-6);
SANITY_CHECK(sqsum, 1e-6);
}
PERF_TEST_P( Size_MatType_OutMatDepth, integral_sqsum_tilted,
testing::Combine(
testing::Values( TYPICAL_MAT_SIZES ),
testing::Values( CV_8UC1, CV_8UC4 ),
testing::Values( CV_32S, CV_32F, CV_64F )
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
Mat sqsum(sz, sdepth);
Mat tilted(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum, sqsum, tilted);
TEST_CYCLE() integral(src, sum, sqsum, tilted, sdepth);
SANITY_CHECK(sum, 1e-6);
SANITY_CHECK(sqsum, 1e-6);
SANITY_CHECK(tilted, 1e-6, tilted.depth() > CV_32S ? ERROR_RELATIVE : ERROR_ABSOLUTE);
}
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
typedef std::tr1::tuple<Size, MatType, MatDepth> Size_MatType_OutMatDepth_t;
typedef perf::TestBaseWithParam<Size_MatType_OutMatDepth_t> Size_MatType_OutMatDepth;
PERF_TEST_P(Size_MatType_OutMatDepth, integral,
testing::Combine(
testing::Values(TYPICAL_MAT_SIZES),
testing::Values(CV_8UC1, CV_8UC4),
testing::Values(CV_32S, CV_32F, CV_64F)
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum);
TEST_CYCLE() integral(src, sum, sdepth);
SANITY_CHECK(sum, 1e-6);
}
PERF_TEST_P(Size_MatType_OutMatDepth, integral_sqsum,
testing::Combine(
testing::Values(TYPICAL_MAT_SIZES),
testing::Values(CV_8UC1, CV_8UC4),
testing::Values(CV_32S, CV_32F, CV_64F)
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
Mat sqsum(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum, sqsum);
TEST_CYCLE() integral(src, sum, sqsum, sdepth);
SANITY_CHECK(sum, 1e-6);
SANITY_CHECK(sqsum, 1e-6);
}
PERF_TEST_P( Size_MatType_OutMatDepth, integral_sqsum_tilted,
testing::Combine(
testing::Values( TYPICAL_MAT_SIZES ),
testing::Values( CV_8UC1, CV_8UC4 ),
testing::Values( CV_32S, CV_32F, CV_64F )
)
)
{
Size sz = get<0>(GetParam());
int matType = get<1>(GetParam());
int sdepth = get<2>(GetParam());
Mat src(sz, matType);
Mat sum(sz, sdepth);
Mat sqsum(sz, sdepth);
Mat tilted(sz, sdepth);
declare.in(src, WARMUP_RNG).out(sum, sqsum, tilted);
TEST_CYCLE() integral(src, sum, sqsum, tilted, sdepth);
SANITY_CHECK(sum, 1e-6);
SANITY_CHECK(sqsum, 1e-6);
SANITY_CHECK(tilted, 1e-6, tilted.depth() > CV_32S ? ERROR_RELATIVE : ERROR_ABSOLUTE);
}
modules/imgproc/perf/perf_morph.cpp
+40 -40
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@@ -1,40 +1,40 @@
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
#define TYPICAL_MAT_TYPES_MORPH CV_8UC1, CV_8UC4
#define TYPICAL_MATS_MORPH testing::Combine(SZ_ALL_GA, testing::Values(TYPICAL_MAT_TYPES_MORPH))
PERF_TEST_P(Size_MatType, erode, TYPICAL_MATS_MORPH)
{
Size sz = get<0>(GetParam());
int type = get<1>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() erode(src, dst, noArray());
SANITY_CHECK(dst);
}
PERF_TEST_P(Size_MatType, dilate, TYPICAL_MATS_MORPH)
{
Size sz = get<0>(GetParam());
int type = get<1>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() dilate(src, dst, noArray());
SANITY_CHECK(dst);
}
#include "perf_precomp.hpp"
using namespace std;
using namespace cv;
using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
#define TYPICAL_MAT_TYPES_MORPH CV_8UC1, CV_8UC4
#define TYPICAL_MATS_MORPH testing::Combine(SZ_ALL_GA, testing::Values(TYPICAL_MAT_TYPES_MORPH))
PERF_TEST_P(Size_MatType, erode, TYPICAL_MATS_MORPH)
{
Size sz = get<0>(GetParam());
int type = get<1>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() erode(src, dst, noArray());
SANITY_CHECK(dst);
}
PERF_TEST_P(Size_MatType, dilate, TYPICAL_MATS_MORPH)
{
Size sz = get<0>(GetParam());
int type = get<1>(GetParam());
Mat src(sz, type);
Mat dst(sz, type);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() dilate(src, dst, noArray());
SANITY_CHECK(dst);
}
modules/imgproc/perf/perf_resize.cpp
+1 -1
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@@ -101,7 +101,7 @@ PERF_TEST_P(MatInfo_Size_Scale_Area, ResizeArea,
double scale = get<2>(GetParam());
cv::Mat src(from, matType);
Size to(cvRound(from.width * scale), cvRound(from.height * scale));
cv::Mat dst(to, matType);
modules/imgproc/perf/perf_threshold.cpp
+1 -1
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@@ -77,7 +77,7 @@ PERF_TEST_P(Size_AdaptThreshType_AdaptThreshMethod_BlockSize, adaptiveThreshold,
double maxValue = theRNG().uniform(1, 254);
double C = 10.0;
int type = CV_8UC1;
Mat src(sz, type);
Mat dst(sz, type);
modules/imgproc/src/accum.cpp
+41 -41
View File
@@ -49,18 +49,18 @@ template<typename T, typename AT> void
acc_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
if( !mask )
{
len *= cn;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = src[i] + dst[i];
t1 = src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
t0 = src[i+2] + dst[i+2];
t1 = src[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
@@ -86,7 +86,7 @@ acc_( const T* src, AT* dst, const uchar* mask, int len, int cn )
AT t0 = src[0] + dst[0];
AT t1 = src[1] + dst[1];
AT t2 = src[2] + dst[2];
dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
@@ -102,23 +102,23 @@ acc_( const T* src, AT* dst, const uchar* mask, int len, int cn )
}
}
template<typename T, typename AT> void
accSqr_( const T* src, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
if( !mask )
{
len *= cn;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = (AT)src[i]*src[i] + dst[i];
t1 = (AT)src[i+1]*src[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
t0 = (AT)src[i+2]*src[i+2] + dst[i+2];
t1 = (AT)src[i+3]*src[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
@@ -144,7 +144,7 @@ accSqr_( const T* src, AT* dst, const uchar* mask, int len, int cn )
AT t0 = (AT)src[0]*src[0] + dst[0];
AT t1 = (AT)src[1]*src[1] + dst[1];
AT t2 = (AT)src[2]*src[2] + dst[2];
dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
@@ -159,24 +159,24 @@ accSqr_( const T* src, AT* dst, const uchar* mask, int len, int cn )
}
}
}
template<typename T, typename AT> void
accProd_( const T* src1, const T* src2, AT* dst, const uchar* mask, int len, int cn )
{
int i = 0;
if( !mask )
{
len *= cn;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = (AT)src1[i]*src2[i] + dst[i];
t1 = (AT)src1[i+1]*src2[i+1] + dst[i+1];
dst[i] = t0; dst[i+1] = t1;
t0 = (AT)src1[i+2]*src2[i+2] + dst[i+2];
t1 = (AT)src1[i+3]*src2[i+3] + dst[i+3];
dst[i+2] = t0; dst[i+3] = t1;
@@ -202,7 +202,7 @@ accProd_( const T* src1, const T* src2, AT* dst, const uchar* mask, int len, int
AT t0 = (AT)src1[0]*src2[0] + dst[0];
AT t1 = (AT)src1[1]*src2[1] + dst[1];
AT t2 = (AT)src1[2]*src2[2] + dst[2];
dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
@@ -218,24 +218,24 @@ accProd_( const T* src1, const T* src2, AT* dst, const uchar* mask, int len, int
}
}
template<typename T, typename AT> void
accW_( const T* src, AT* dst, const uchar* mask, int len, int cn, double alpha )
{
AT a = (AT)alpha, b = 1 - a;
int i = 0;
if( !mask )
{
len *= cn;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; i <= len - 4; i += 4 )
{
AT t0, t1;
t0 = src[i]*a + dst[i]*b;
t1 = src[i+1]*a + dst[i+1]*b;
dst[i] = t0; dst[i+1] = t1;
t0 = src[i+2]*a + dst[i+2]*b;
t1 = src[i+3]*a + dst[i+3]*b;
dst[i+2] = t0; dst[i+3] = t1;
@@ -261,7 +261,7 @@ accW_( const T* src, AT* dst, const uchar* mask, int len, int cn, double alpha )
AT t0 = src[0]*a + dst[0]*b;
AT t1 = src[1]*a + dst[1]*b;
AT t2 = src[2]*a + dst[2]*b;
dst[0] = t0; dst[1] = t1; dst[2] = t2;
}
}
@@ -303,8 +303,8 @@ DEF_ACC_FUNCS(16u64f, ushort, double)
DEF_ACC_FUNCS(32f, float, float)
DEF_ACC_FUNCS(32f64f, float, double)
DEF_ACC_FUNCS(64f, double, double)
typedef void (*AccFunc)(const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccProdFunc)(const uchar*, const uchar*, uchar*, const uchar*, int, int);
typedef void (*AccWFunc)(const uchar*, uchar*, const uchar*, int, int, double);
@@ -350,27 +350,27 @@ inline int getAccTabIdx(int sdepth, int ddepth)
sdepth == CV_32F && ddepth == CV_32F ? 4 :
sdepth == CV_32F && ddepth == CV_64F ? 5 :
sdepth == CV_64F && ddepth == CV_64F ? 6 : -1;
}
}
}
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();
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
}
@@ -380,19 +380,19 @@ void cv::accumulateSquare( InputArray _src, InputOutputArray _dst, InputArray _m
{
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
int fidx = getAccTabIdx(sdepth, ddepth);
AccFunc func = fidx >= 0 ? accSqrTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
int len = (int)it.size;
for( size_t i = 0; i < it.nplanes; i++, ++it )
func(ptrs[0], ptrs[1], ptrs[2], len, cn);
}
@@ -402,20 +402,20 @@ void cv::accumulateProduct( InputArray _src1, InputArray _src2,
{
Mat src1 = _src1.getMat(), src2 = _src2.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src1.depth(), ddepth = dst.depth(), cn = src1.channels();
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) );
int fidx = getAccTabIdx(sdepth, ddepth);
AccProdFunc func = fidx >= 0 ? accProdTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src1, &src2, &dst, &mask, 0};
uchar* ptrs[4];
NAryMatIterator it(arrays, ptrs);
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);
}
@@ -426,19 +426,19 @@ void cv::accumulateWeighted( InputArray _src, InputOutputArray _dst,
{
Mat src = _src.getMat(), dst = _dst.getMat(), mask = _mask.getMat();
int sdepth = src.depth(), ddepth = dst.depth(), cn = src.channels();
CV_Assert( dst.size == src.size && dst.channels() == cn );
CV_Assert( mask.empty() || (mask.size == src.size && mask.type() == CV_8U) );
int fidx = getAccTabIdx(sdepth, ddepth);
AccWFunc func = fidx >= 0 ? accWTab[fidx] : 0;
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &dst, &mask, 0};
uchar* ptrs[3];
NAryMatIterator it(arrays, ptrs);
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);
}
modules/imgproc/src/approx.cpp
+1 -1
View File
@@ -648,7 +648,7 @@ icvApproxPolyDP( CvSeq* src_contour, int header_size,
dx = end_pt.x - start_pt.x;
dy = end_pt.y - start_pt.y;
dist = fabs((pt.x - start_pt.x)*dy - (pt.y - start_pt.y)*dx);
successive_inner_product = (pt.x - start_pt.x) * (end_pt.x - pt.x) +
successive_inner_product = (pt.x - start_pt.x) * (end_pt.x - pt.x) +
(pt.y - start_pt.y) * (end_pt.y - pt.y);
if( dist * dist <= 0.5*eps*(dx*dx + dy*dy) && dx != 0 && dy != 0 &&
modules/imgproc/src/canny.cpp
+6 -6
View File
@@ -47,7 +47,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
{
Mat src = _src.getMat();
CV_Assert( src.depth() == CV_8U );
_dst.create(src.size(), CV_8U);
Mat dst = _dst.getMat();
@@ -80,7 +80,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
{
low_thresh = std::min(32767.0, low_thresh);
high_thresh = std::min(32767.0, high_thresh);
if (low_thresh > 0) low_thresh *= low_thresh;
if (high_thresh > 0) high_thresh *= high_thresh;
}
@@ -89,7 +89,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
ptrdiff_t mapstep = src.cols + 2;
cv::AutoBuffer<uchar> buffer((src.cols+2)*(src.rows+2) + cn * mapstep * 3 * sizeof(int));
int* mag_buf[3];
mag_buf[0] = (int*)(uchar*)buffer;
mag_buf[1] = mag_buf[0] + mapstep*cn;
@@ -143,7 +143,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
for (int j = 0; j < src.cols*cn; j++)
_norm[j] = int(_dx[j])*_dx[j] + int(_dy[j])*_dy[j];
}
if (cn > 1)
{
for(int j = 0, jn = 0; j < src.cols; ++j, jn += cn)
@@ -160,7 +160,7 @@ void cv::Canny( InputArray _src, OutputArray _dst,
}
else
memset(_norm-1, 0, /* cn* */mapstep*sizeof(int));
// at the very beginning we do not have a complete ring
// buffer of 3 magnitude rows for non-maxima suppression
if (i == 0)
@@ -280,7 +280,7 @@ void cvCanny( const CvArr* image, CvArr* edges, double threshold1,
{
cv::Mat src = cv::cvarrToMat(image), dst = cv::cvarrToMat(edges);
CV_Assert( src.size == dst.size && src.depth() == CV_8U && dst.type() == CV_8U );
cv::Canny(src, dst, threshold1, threshold2, aperture_size & 255,
(aperture_size & CV_CANNY_L2_GRADIENT) != 0);
}
modules/imgproc/src/color.cpp
+23 -23
View File
@@ -1362,7 +1362,7 @@ struct RGB2Lab_f
_coeffs = sRGB2XYZ_D65;
if (!_whitept)
_whitept = D65;
float scale[] = { 1.0f / _whitept[0], 1.0f, 1.0f / _whitept[2] };
for( int i = 0; i < _3; i++ )
@@ -1371,7 +1371,7 @@ struct RGB2Lab_f
coeffs[j + (blueIdx ^ 2)] = _coeffs[j] * scale[i];
coeffs[j + 1] = _coeffs[j + 1] * scale[i];
coeffs[j + blueIdx] = _coeffs[j + 2] * scale[i];
CV_Assert( coeffs[j] >= 0 && coeffs[j + 1] >= 0 && coeffs[j + 2] >= 0 &&
coeffs[j] + coeffs[j + 1] + coeffs[j + 2] < 1.5f*LabCbrtTabScale );
}
@@ -1394,11 +1394,11 @@ struct RGB2Lab_f
float R = clip(src[0]);
float G = clip(src[1]);
float B = clip(src[2]);
// CV_Assert(R >= 0.0f && R <= 1.0f);
// CV_Assert(G >= 0.0f && G <= 1.0f);
// CV_Assert(B >= 0.0f && B <= 1.0f);
if (gammaTab)
{
R = splineInterpolate(R * gscale, gammaTab, GAMMA_TAB_SIZE);
@@ -1408,15 +1408,15 @@ struct RGB2Lab_f
float X = R*C0 + G*C1 + B*C2;
float Y = R*C3 + G*C4 + B*C5;
float Z = R*C6 + G*C7 + B*C8;
float FX = X > 0.008856 ? pow(X, _1_3) : (7.787f * X + _a);
float FY = Y > 0.008856 ? pow(Y, _1_3) : (7.787f * Y + _a);
float FZ = Z > 0.008856 ? pow(Z, _1_3) : (7.787f * Z + _a);
float L = Y > 0.008856 ? (116.f * FY - 16.f) : (903.3 * Y);
float a = 500.f * (FX - FY);
float b = 200.f * (FY - FZ);
dst[i] = L;
dst[i + 1] = a;
dst[i + 2] = b;
@@ -1427,22 +1427,22 @@ struct RGB2Lab_f
float coeffs[9];
bool srgb;
};
struct Lab2RGB_f
{
typedef float channel_type;
Lab2RGB_f( int _dstcn, int blueIdx, const float* _coeffs,
const float* _whitept, bool _srgb )
: dstcn(_dstcn), srgb(_srgb), blueInd(blueIdx)
{
initLabTabs();
if(!_coeffs)
_coeffs = XYZ2sRGB_D65;
if(!_whitept)
_whitept = D65;
for( int i = 0; i < 3; i++ )
{
coeffs[i+(blueIdx^2)*3] = _coeffs[i]*_whitept[i];
@@ -1450,7 +1450,7 @@ struct Lab2RGB_f
coeffs[i+blueIdx*3] = _coeffs[i+6]*_whitept[i];
}
}
void operator()(const float* src, float* dst, int n) const
{
int i, dcn = dstcn;
@@ -1461,7 +1461,7 @@ struct Lab2RGB_f
C6 = coeffs[6], C7 = coeffs[7], C8 = coeffs[8];
float alpha = ColorChannel<float>::max();
n *= 3;
static const float lThresh = 0.008856f * 903.3f;
static const float fThresh = 7.787f * 0.008856f + 16.0f / 116.0f;
for (i = 0; i < n; i += 3, dst += dcn)
@@ -1469,7 +1469,7 @@ struct Lab2RGB_f
float li = src[i];
float ai = src[i + 1];
float bi = src[i + 2];
float y, fy;
if (li <= lThresh)
{
@@ -1481,44 +1481,44 @@ struct Lab2RGB_f
fy = (li + 16.0f) / 116.0f;
y = fy * fy * fy;
}
float fxz[] = { ai / 500.0f + fy, fy - bi / 200.0f };
for (int j = 0; j < 2; j++)
if (fxz[j] <= fThresh)
fxz[j] = (fxz[j] - 16.0f / 116.0f) / 7.787f;
else
fxz[j] = fxz[j] * fxz[j] * fxz[j];
float x = fxz[0], z = fxz[1];
float ro = clip(C0 * x + C1 * y + C2 * z);
float go = clip(C3 * x + C4 * y + C5 * z);
float bo = clip(C6 * x + C7 * y + C8 * z);
// CV_Assert(ro >= 0.0f && ro <= 1.0f);
// CV_Assert(go >= 0.0f && go <= 1.0f);
// CV_Assert(bo >= 0.0f && bo <= 1.0f);
if (gammaTab)
{
ro = splineInterpolate(ro * gscale, gammaTab, GAMMA_TAB_SIZE);
go = splineInterpolate(go * gscale, gammaTab, GAMMA_TAB_SIZE);
bo = splineInterpolate(bo * gscale, gammaTab, GAMMA_TAB_SIZE);
}
dst[0] = ro, dst[1] = go, dst[2] = bo;
if( dcn == 4 )
dst[3] = alpha;
}
}
int dstcn;
float coeffs[9];
bool srgb;
int blueInd;
};
#undef clip
struct Lab2RGB_b
modules/imgproc/src/contours.cpp
+60 -60
View File
@@ -159,7 +159,7 @@ typedef struct _CvContourScanner
external contours and holes),
3 - full hierarchy;
4 - connected components of a multi-level image
*/
*/
int subst_flag;
int seq_type1; /* type of fetched contours */
int header_size1; /* hdr size of fetched contours */
@@ -190,7 +190,7 @@ cvStartFindContours( void* _img, CvMemStorage* storage,
if( CV_MAT_TYPE(mat->type) == CV_32SC1 && mode == CV_RETR_CCOMP )
mode = CV_RETR_FLOODFILL;
if( !((CV_IS_MASK_ARR( mat ) && mode < CV_RETR_FLOODFILL) ||
(CV_MAT_TYPE(mat->type) == CV_32SC1 && mode == CV_RETR_FLOODFILL)) )
CV_Error( CV_StsUnsupportedFormat, "[Start]FindContours support only 8uC1 and 32sC1 images" );
@@ -207,7 +207,7 @@ cvStartFindContours( void* _img, CvMemStorage* storage,
CvContourScanner scanner = (CvContourScanner)cvAlloc( sizeof( *scanner ));
memset( scanner, 0, sizeof(*scanner) );
scanner->storage1 = scanner->storage2 = storage;
scanner->img0 = (schar *) img;
scanner->img = (schar *) (img + step);
@@ -805,13 +805,13 @@ icvTraceContour_32s( int *ptr, int step, int *stop_ptr, int is_hole )
const int new_flag = (int)((unsigned)INT_MIN >> 1);
const int value_mask = ~(right_flag | new_flag);
const int ccomp_val = *i0 & value_mask;
/* initialize local state */
CV_INIT_3X3_DELTAS( deltas, step, 1 );
memcpy( deltas + 8, deltas, 8 * sizeof( deltas[0] ));
s_end = s = is_hole ? 0 : 4;
do
{
s = (s - 1) & 7;
@@ -820,9 +820,9 @@ icvTraceContour_32s( int *ptr, int step, int *stop_ptr, int is_hole )
break;
}
while( s != s_end );
i3 = i0;
/* check single pixel domain */
if( s != s_end )
{
@@ -830,17 +830,17 @@ icvTraceContour_32s( int *ptr, int step, int *stop_ptr, int is_hole )
for( ;; )
{
s_end = s;
for( ;; )
{
i4 = i3 + deltas[++s];
if( (*i4 & value_mask) == ccomp_val )
break;
}
if( i3 == stop_ptr || (i4 == i0 && i3 == i1) )
break;
i3 = i4;
s = (s + 4) & 7;
} /* end of border following loop */
@@ -869,24 +869,24 @@ icvFetchContourEx_32s( int* ptr,
const int ccomp_val = *i0 & value_mask;
const int nbd0 = ccomp_val | new_flag;
const int nbd1 = nbd0 | right_flag;
assert( (unsigned) _method <= CV_CHAIN_APPROX_SIMPLE );
/* initialize local state */
CV_INIT_3X3_DELTAS( deltas, step, 1 );
memcpy( deltas + 8, deltas, 8 * sizeof( deltas[0] ));
/* initialize writer */
cvStartAppendToSeq( contour, &writer );
if( method < 0 )
((CvChain *)contour)->origin = pt;
rect.x = rect.width = pt.x;
rect.y = rect.height = pt.y;
s_end = s = CV_IS_SEQ_HOLE( contour ) ? 0 : 4;
do
{
s = (s - 1) & 7;
@@ -895,7 +895,7 @@ icvFetchContourEx_32s( int* ptr,
break;
}
while( s != s_end );
if( s == s_end ) /* single pixel domain */
{
*i0 = nbd1;
@@ -908,12 +908,12 @@ icvFetchContourEx_32s( int* ptr,
{
i3 = i0;
prev_s = s ^ 4;
/* follow border */
for( ;; )
{
s_end = s;
for( ;; )
{
i4 = i3 + deltas[++s];
@@ -921,7 +921,7 @@ icvFetchContourEx_32s( int* ptr,
break;
}
s &= 7;
/* check "right" bound */
if( (unsigned) (s - 1) < (unsigned) s_end )
{
@@ -931,7 +931,7 @@ icvFetchContourEx_32s( int* ptr,
{
*i3 = nbd0;
}
if( method < 0 )
{
schar _s = (schar) s;
@@ -941,7 +941,7 @@ icvFetchContourEx_32s( int* ptr,
{
CV_WRITE_SEQ_ELEM( pt, writer );
}
if( s != prev_s )
{
/* update bounds */
@@ -949,37 +949,37 @@ icvFetchContourEx_32s( int* ptr,
rect.x = pt.x;
else if( pt.x > rect.width )
rect.width = pt.x;
if( pt.y < rect.y )
rect.y = pt.y;
else if( pt.y > rect.height )
rect.height = pt.y;
}
prev_s = s;
pt.x += icvCodeDeltas[s].x;
pt.y += icvCodeDeltas[s].y;
if( i4 == i0 && i3 == i1 ) break;
i3 = i4;
s = (s + 4) & 7;
} /* end of border following loop */
}
rect.width -= rect.x - 1;
rect.height -= rect.y - 1;
cvEndWriteSeq( &writer );
if( _method != CV_CHAIN_CODE )
((CvContour*)contour)->rect = rect;
assert( (writer.seq->total == 0 && writer.seq->first == 0) ||
writer.seq->total > writer.seq->first->count ||
(writer.seq->first->prev == writer.seq->first &&
writer.seq->first->next == writer.seq->first) );
if( _rect ) *_rect = rect;
}
@@ -1005,7 +1005,7 @@ cvFindNextContour( CvContourScanner scanner )
int nbd = scanner->nbd;
int prev = img[x - 1];
int new_mask = -2;
if( mode == CV_RETR_FLOODFILL )
{
prev = ((int*)img)[x - 1];
@@ -1017,13 +1017,13 @@ cvFindNextContour( CvContourScanner scanner )
int* img0_i = 0;
int* img_i = 0;
int p = 0;
if( mode == CV_RETR_FLOODFILL )
{
img0_i = (int*)img0;
img_i = (int*)img;
}
for( ; x < width; x++ )
{
if( img_i )
@@ -1036,10 +1036,10 @@ cvFindNextContour( CvContourScanner scanner )
for( ; x < width && (p = img[x]) == prev; x++ )
;
}
if( x >= width )
break;
{
_CvContourInfo *par_info = 0;
_CvContourInfo *l_cinfo = 0;
@@ -1053,7 +1053,7 @@ cvFindNextContour( CvContourScanner scanner )
{
/* check hole */
if( (!img_i && (p != 0 || prev < 1)) ||
(img_i && ((prev & new_mask) != 0 || (p & new_mask) != 0)))
(img_i && ((prev & new_mask) != 0 || (p & new_mask) != 0)))
goto resume_scan;
if( prev & new_mask )
@@ -1219,7 +1219,7 @@ cvFindNextContour( CvContourScanner scanner )
return l_cinfo->contour;
resume_scan:
prev = p;
/* update lnbd */
if( prev & -2 )
@@ -1663,7 +1663,7 @@ cvFindContours( void* img, CvMemStorage* storage,
if( !firstContour )
CV_Error( CV_StsNullPtr, "NULL double CvSeq pointer" );
*firstContour = 0;
if( method == CV_LINK_RUNS )
@@ -1733,7 +1733,7 @@ void cv::findContours( InputOutputArray _image, OutputArrayOfArrays _contours,
{
_hierarchy.create(1, total, CV_32SC4, -1, true);
Vec4i* hierarchy = _hierarchy.getMat().ptr<Vec4i>();
it = all_contours.begin();
for( i = 0; i < total; i++, ++it )
{
@@ -1768,19 +1768,19 @@ static void addChildContour(InputArrayOfArrays contours,
cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
!ci.empty() ? (void*)ci.data : 0, (int)ci.total(),
&seq[i], &block[i] );
int h_next = hierarchy[i][0], h_prev = hierarchy[i][1],
v_next = hierarchy[i][2], v_prev = hierarchy[i][3];
seq[i].h_next = (size_t)h_next < ncontours ? &seq[h_next] : 0;
seq[i].h_prev = (size_t)h_prev < ncontours ? &seq[h_prev] : 0;
seq[i].v_next = (size_t)v_next < ncontours ? &seq[v_next] : 0;
seq[i].v_prev = (size_t)v_prev < ncontours ? &seq[v_prev] : 0;
if( v_next >= 0 )
addChildContour(contours, ncontours, hierarchy, v_next, seq, block);
}
}
}
void cv::drawContours( InputOutputArray _image, InputArrayOfArrays _contours,
@@ -1798,20 +1798,20 @@ void cv::drawContours( InputOutputArray _image, InputArrayOfArrays _contours,
if( !last )
return;
seq.resize(last);
block.resize(last);
for( i = first; i < last; i++ )
seq[i].first = 0;
if( contourIdx >= 0 )
{
CV_Assert( 0 <= contourIdx && contourIdx < (int)last );
first = contourIdx;
last = contourIdx + 1;
}
for( i = first; i < last; i++ )
{
Mat ci = _contours.getMat((int)i);
@@ -1834,7 +1834,7 @@ void cv::drawContours( InputOutputArray _image, InputArrayOfArrays _contours,
size_t count = last - first;
CV_Assert(hierarchy.total() == ncontours && hierarchy.type() == CV_32SC4 );
const Vec4i* h = hierarchy.ptr<Vec4i>();
if( count == ncontours )
{
for( i = first; i < last; i++ )
@@ -1934,7 +1934,7 @@ double cv::matchShapes( InputArray _contour1,
CV_Assert(contour1.checkVector(2) >= 0 && contour2.checkVector(2) >= 0 &&
(contour1.depth() == CV_32F || contour1.depth() == CV_32S) &&
contour1.depth() == contour2.depth());
CvMat c1 = Mat(contour1), c2 = Mat(contour2);
return cvMatchShapes(&c1, &c2, method, parameter);
}
@@ -1945,13 +1945,13 @@ void cv::convexHull( InputArray _points, OutputArray _hull, bool clockwise, bool
Mat points = _points.getMat();
int nelems = points.checkVector(2), depth = points.depth();
CV_Assert(nelems >= 0 && (depth == CV_32F || depth == CV_32S));
if( nelems == 0 )
{
_hull.release();
return;
}
returnPoints = !_hull.fixedType() ? returnPoints : _hull.type() != CV_32S;
Mat hull(nelems, 1, returnPoints ? CV_MAKETYPE(depth, 2) : CV_32S);
CvMat _cpoints = points, _chull = hull;
@@ -1970,23 +1970,23 @@ void cv::convexityDefects( InputArray _points, InputArray _hull, OutputArray _de
Mat hull = _hull.getMat();
CV_Assert( hull.checkVector(1, CV_32S) > 2 );
Ptr<CvMemStorage> storage = cvCreateMemStorage();
CvMat c_points = points, c_hull = hull;
CvSeq* seq = cvConvexityDefects(&c_points, &c_hull, storage);
int i, n = seq->total;
if( n == 0 )
{
_defects.release();
return;
}
_defects.create(n, 1, CV_32SC4);
Mat defects = _defects.getMat();
SeqIterator<CvConvexityDefect> it = Seq<CvConvexityDefect>(seq).begin();
CvPoint* ptorg = (CvPoint*)points.data;
for( i = 0; i < n; i++, ++it )
{
CvConvexityDefect& d = *it;
@@ -2034,9 +2034,9 @@ void cv::fitLine( InputArray _points, OutputArray _line, int distType,
CvMat _cpoints = points.reshape(2 + (int)is3d);
float line[6];
cvFitLine(&_cpoints, distType, param, reps, aeps, &line[0]);
int out_size = (is2d)?( (is3d)? (points.channels() * points.rows * 2) : 4 ): 6;
_line.create(out_size, 1, CV_32F, -1, true);
Mat l = _line.getMat();
CV_Assert( l.isContinuous() );
modules/imgproc/src/corner.cpp
+14 -14
View File
@@ -55,7 +55,7 @@ calcMinEigenVal( const Mat& _cov, Mat& _dst )
#if CV_SSE
volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
#endif
if( _cov.isContinuous() && _dst.isContinuous() )
{
size.width *= size.height;
@@ -112,7 +112,7 @@ calcHarris( const Mat& _cov, Mat& _dst, double k )
#if CV_SSE
volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
#endif
if( _cov.isContinuous() && _dst.isContinuous() )
{
size.width *= size.height;
@@ -161,7 +161,7 @@ calcHarris( const Mat& _cov, Mat& _dst, double k )
}
}
void eigen2x2( const float* cov, float* dst, int n )
{
for( int j = 0; j < n; j++ )
@@ -169,16 +169,16 @@ void eigen2x2( const float* cov, float* dst, int n )
double a = cov[j*3];
double b = cov[j*3+1];
double c = cov[j*3+2];
double u = (a + c)*0.5;
double v = std::sqrt((a - c)*(a - c)*0.25 + b*b);
double l1 = u + v;
double l2 = u - v;
double x = b;
double y = l1 - a;
double e = fabs(x);
if( e + fabs(y) < 1e-4 )
{
y = b;
@@ -190,16 +190,16 @@ void eigen2x2( const float* cov, float* dst, int n )
x *= e, y *= e;
}
}
double d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
dst[6*j] = (float)l1;
dst[6*j + 2] = (float)(x*d);
dst[6*j + 3] = (float)(y*d);
x = b;
y = l2 - a;
e = fabs(x);
if( e + fabs(y) < 1e-4 )
{
y = b;
@@ -211,7 +211,7 @@ void eigen2x2( const float* cov, float* dst, int n )
x *= e, y *= e;
}
}
d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
dst[6*j + 1] = (float)l2;
dst[6*j + 4] = (float)(x*d);
@@ -250,7 +250,7 @@ cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::cornerEigenValsVecs(src, eigenv, block_size, aperture_size, op_type, k, borderType))
return;
#endif
#endif
int depth = src.depth();
double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
@@ -331,7 +331,7 @@ void cv::cornerEigenValsAndVecs( InputArray _src, OutputArray _dst, int blockSiz
Mat src = _src.getMat();
Size dsz = _dst.size();
int dtype = _dst.type();
if( dsz.height != src.rows || dsz.width*CV_MAT_CN(dtype) != src.cols*6 || CV_MAT_DEPTH(dtype) != CV_32F )
_dst.create( src.size(), CV_32FC(6) );
Mat dst = _dst.getMat();
@@ -346,7 +346,7 @@ void cv::preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int bord
CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );
_dst.create( src.size(), CV_32F );
Mat dst = _dst.getMat();
Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType );
Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType );
Sobel( src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
@@ -368,7 +368,7 @@ void cv::preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int bord
const float* d2xdata = (const float*)(D2x.data + i*D2x.step);
const float* d2ydata = (const float*)(D2y.data + i*D2y.step);
const float* dxydata = (const float*)(Dxy.data + i*Dxy.step);
for( j = 0; j < size.width; j++ )
{
float dx = dxdata[j];
modules/imgproc/src/cornersubpix.cpp
+2 -2
View File
@@ -46,7 +46,7 @@ cvFindCornerSubPix( const void* srcarr, CvPoint2D32f* corners,
CvTermCriteria criteria )
{
cv::AutoBuffer<float> buffer;
const int MAX_ITERS = 100;
const float drv[] = { -1.f, 0.f, 1.f };
float *maskX;
@@ -257,7 +257,7 @@ void cv::cornerSubPix( InputArray _image, InputOutputArray _corners,
CV_Assert( ncorners >= 0 && corners.depth() == CV_32F );
Mat image = _image.getMat();
CvMat c_image = image;
cvFindCornerSubPix( &c_image, (CvPoint2D32f*)corners.data, ncorners,
winSize, zeroZone, criteria );
}
modules/imgproc/src/deriv.cpp
+11 -11
View File
@@ -173,7 +173,7 @@ static void getSobelKernels( OutputArray _kx, OutputArray _ky,
_kx.create(ksizeX, 1, ktype, -1, true);
_ky.create(ksizeY, 1, ktype, -1, true);
Mat kx = _kx.getMat();
Mat ky = _ky.getMat();
Mat ky = _ky.getMat();
if( _ksize % 2 == 0 || _ksize > 31 )
CV_Error( CV_StsOutOfRange, "The kernel size must be odd and not larger than 31" );
@@ -484,7 +484,7 @@ static bool IPPDeriv(const Mat& src, Mat& dst, int ddepth, int dx, int dy, int k
}
}
#endif
void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
@@ -505,7 +505,7 @@ void cv::Sobel( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
return;
}
#endif
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
if(dx < 3 && dy < 3 && src.channels() == 1 && borderType == 1)
{
@@ -544,7 +544,7 @@ void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
if (tegra::scharr(src, dst, dx, dy, borderType))
return;
#endif
#if defined (HAVE_IPP) && (IPP_VERSION_MAJOR >= 7)
if(dx < 2 && dy < 2 && src.channels() == 1 && borderType == 1)
{
@@ -572,24 +572,24 @@ void cv::Scharr( InputArray _src, OutputArray _dst, int ddepth, int dx, int dy,
void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
double scale, double delta, int borderType )
{
Mat src = _src.getMat();
Mat src = _src.getMat();
if (ddepth < 0)
ddepth = src.depth();
_dst.create( src.size(), CV_MAKETYPE(ddepth, src.channels()) );
Mat dst = _dst.getMat();
#ifdef HAVE_TEGRA_OPTIMIZATION
if (scale == 1.0 && delta == 0)
{
if (ksize == 1 && tegra::laplace1(src, dst, borderType))
if (ksize == 1 && tegra::laplace1(src, dst, borderType))
return;
if (ksize == 3 && tegra::laplace3(src, dst, borderType))
if (ksize == 3 && tegra::laplace3(src, dst, borderType))
return;
if (ksize == 5 && tegra::laplace5(src, dst, borderType))
if (ksize == 5 && tegra::laplace5(src, dst, borderType))
return;
}
#endif
if( ksize == 1 || ksize == 3 )
{
float K[2][9] =
@@ -616,7 +616,7 @@ void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
int dy0 = std::min(std::max((int)(STRIPE_SIZE/(getElemSize(src.type())*src.cols)), 1), src.rows);
Ptr<FilterEngine> fx = createSeparableLinearFilter(src.type(),
wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
wtype, kd, ks, Point(-1,-1), 0, borderType, borderType, Scalar() );
Ptr<FilterEngine> fy = createSeparableLinearFilter(src.type(),
wtype, ks, kd, Point(-1,-1), 0, borderType, borderType, Scalar() );
modules/imgproc/src/distransform.cpp
+30 -30
View File
@@ -51,7 +51,7 @@ icvInitTopBottom( int* temp, int tempstep, CvSize size, int border )
{
int* ttop = (int*)(temp + i*tempstep);
int* tbottom = (int*)(temp + (size.height + border*2 - i - 1)*tempstep);
for( j = 0; j < size.width + border*2; j++ )
{
ttop[j] = ICV_INIT_DIST0;
@@ -87,7 +87,7 @@ icvDistanceTransform_3x3_C1R( const uchar* src, int srcstep, int* temp,
for( j = 0; j < BORDER; j++ )
tmp[-j-1] = tmp[size.width + j] = ICV_INIT_DIST0;
for( j = 0; j < size.width; j++ )
{
if( !s[j] )
@@ -111,7 +111,7 @@ icvDistanceTransform_3x3_C1R( const uchar* src, int srcstep, int* temp,
{
float* d = (float*)(dist + i*dststep);
int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
for( j = size.width - 1; j >= 0; j-- )
{
int t0 = tmp[j];
@@ -160,7 +160,7 @@ icvDistanceTransform_5x5_C1R( const uchar* src, int srcstep, int* temp,
for( j = 0; j < BORDER; j++ )
tmp[-j-1] = tmp[size.width + j] = ICV_INIT_DIST0;
for( j = 0; j < size.width; j++ )
{
if( !s[j] )
@@ -192,7 +192,7 @@ icvDistanceTransform_5x5_C1R( const uchar* src, int srcstep, int* temp,
{
float* d = (float*)(dist + i*dststep);
int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
for( j = size.width - 1; j >= 0; j-- )
{
int t0 = tmp[j];
@@ -230,7 +230,7 @@ icvDistanceTransformEx_5x5_C1R( const uchar* src, int srcstep, int* temp,
CvSize size, const float* metrics )
{
const int BORDER = 2;
int i, j;
const int HV_DIST = CV_FLT_TO_FIX( metrics[0], ICV_DIST_SHIFT );
const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], ICV_DIST_SHIFT );
@@ -253,7 +253,7 @@ icvDistanceTransformEx_5x5_C1R( const uchar* src, int srcstep, int* temp,
for( j = 0; j < BORDER; j++ )
tmp[-j-1] = tmp[size.width + j] = ICV_INIT_DIST0;
for( j = 0; j < size.width; j++ )
{
if( !s[j] )
@@ -327,7 +327,7 @@ icvDistanceTransformEx_5x5_C1R( const uchar* src, int srcstep, int* temp,
float* d = (float*)(dist + i*dststep);
int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER;
int* lls = (int*)(labels + i*lstep);
for( j = size.width - 1; j >= 0; j-- )
{
int t0 = tmp[j];
@@ -452,7 +452,7 @@ struct DTColumnInvoker
sat_tab = _sat_tab + src->rows*2 + 1;
sqr_tab = _sqr_tab;
}
void operator()( const BlockedRange& range ) const
{
int i, i1 = range.begin(), i2 = range.end();
@@ -460,19 +460,19 @@ struct DTColumnInvoker
size_t sstep = src->step, dstep = dst->step/sizeof(float);
AutoBuffer<int> _d(m);
int* d = _d;
for( i = i1; i < i2; i++ )
{
const uchar* sptr = src->data.ptr + i + (m-1)*sstep;
float* dptr = dst->data.fl + i;
int j, dist = m-1;
for( j = m-1; j >= 0; j--, sptr -= sstep )
{
dist = (dist + 1) & (sptr[0] == 0 ? 0 : -1);
d[j] = dist;
}
dist = m-1;
for( j = 0; j < m; j++, dptr += dstep )
{
@@ -482,14 +482,14 @@ struct DTColumnInvoker
}
}
}
const CvMat* src;
CvMat* dst;
const int* sat_tab;
const float* sqr_tab;
};
struct DTRowInvoker
{
DTRowInvoker( CvMat* _dst, const float* _sqr_tab, const float* _inv_tab )
@@ -498,7 +498,7 @@ struct DTRowInvoker
sqr_tab = _sqr_tab;
inv_tab = _inv_tab;
}
void operator()( const BlockedRange& range ) const
{
const float inf = 1e15f;
@@ -508,22 +508,22 @@ struct DTRowInvoker
float* f = (float*)(uchar*)_buf;
float* z = f + n;
int* v = alignPtr((int*)(z + n + 1), sizeof(int));
for( i = i1; i < i2; i++ )
{
float* d = (float*)(dst->data.ptr + i*dst->step);
int p, q, k;
v[0] = 0;
z[0] = -inf;
z[1] = inf;
f[0] = d[0];
for( q = 1, k = 0; q < n; q++ )
{
float fq = d[q];
f[q] = fq;
for(;;k--)
{
p = v[k];
@@ -538,7 +538,7 @@ struct DTRowInvoker
}
}
}
for( q = 0, k = 0; q < n; q++ )
{
while( z[k+1] < q )
@@ -548,7 +548,7 @@ struct DTRowInvoker
}
}
}
CvMat* dst;
const float* sqr_tab;
const float* inv_tab;
@@ -560,7 +560,7 @@ static void
icvTrueDistTrans( const CvMat* src, CvMat* dst )
{
const float inf = 1e15f;
if( !CV_ARE_SIZES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedSizes, "" );
@@ -586,11 +586,11 @@ icvTrueDistTrans( const CvMat* src, CvMat* dst )
for( ; i <= m*3; i++ )
sat_tab[i] = i - shift;
cv::parallel_for(cv::BlockedRange(0, n), cv::DTColumnInvoker(src, dst, sat_tab, sqr_tab));
cv::parallel_for(cv::BlockedRange(0, n), cv::DTColumnInvoker(src, dst, sat_tab, sqr_tab));
// stage 2: compute modified distance transform for each row
float* inv_tab = sqr_tab + n;
inv_tab[0] = sqr_tab[0] = 0.f;
for( i = 1; i < n; i++ )
{
@@ -634,7 +634,7 @@ icvDistanceATS_L1_8u( const CvMat* src, CvMat* dst )
int a;
uchar lut[256];
int x, y;
const uchar *sbase = src->data.ptr;
uchar *dbase = dst->data.ptr;
int srcstep = src->step;
@@ -738,7 +738,7 @@ cvDistTransform( const void* srcarr, void* dstarr,
icvTrueDistTrans( src, dst );
return;
}
if( labels )
{
labels = cvGetMat( labels, &lstub );
@@ -789,7 +789,7 @@ cvDistTransform( const void* srcarr, void* dstarr,
else
{
cvZero( labels );
if( labelType == CV_DIST_LABEL_CCOMP )
{
CvSeq *contours = 0;
@@ -799,7 +799,7 @@ cvDistTransform( const void* srcarr, void* dstarr,
cvCmpS( src_copy, 0, src_copy, CV_CMP_EQ );
cvFindContours( src_copy, st, &contours, sizeof(CvContour),
CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, cvPoint(-border, -border));
for( int label = 1; contours != 0; contours = contours->h_next, label++ )
{
CvScalar area_color = cvScalarAll(label);
@@ -813,7 +813,7 @@ cvDistTransform( const void* srcarr, void* dstarr,
{
const uchar* srcptr = src->data.ptr + src->step*i;
int* labelptr = (int*)(labels->data.ptr + labels->step*i);
for( int j = 0; j < src->cols; j++ )
if( srcptr[j] == 0 )
labelptr[j] = k++;
modules/imgproc/src/emd.cpp
+7 -7
View File
@@ -48,7 +48,7 @@
An implementation of the Earth Movers Distance.
Based of the solution for the Transportation problem as described in
"Introduction to Mathematical Programming" by F. S. Hillier and
"Introduction to Mathematical Programming" by F. S. Hillier and
G. J. Lieberman, McGraw-Hill, 1990.
Copyright (C) 1998 Yossi Rubner
@@ -347,7 +347,7 @@ static int icvInitEMD( const float* signature1, int size1,
sizeof( CvNode2D * ) + /* cols_x & rows_x */
sizeof( CvNode1D ) + /* u & v */
sizeof( float ) + /* s & d */
sizeof( int ) + sizeof(CvNode2D*)) + /* idx1 & idx2 */
sizeof( int ) + sizeof(CvNode2D*)) + /* idx1 & idx2 */
(size1+1) * (sizeof( float * ) + sizeof( char * ) + /* rows pointers for */
sizeof( float * )) + 256; /* cost, is_x and delta */
@@ -384,7 +384,7 @@ static int icvInitEMD( const float* signature1, int size1,
s_sum += weight;
state->s[ssize] = weight;
state->idx1[ssize++] = i;
}
else if( weight < 0 )
CV_Error(CV_StsOutOfRange, "");
@@ -416,7 +416,7 @@ static int icvInitEMD( const float* signature1, int size1,
{
state->s[ssize] = -diff;
state->idx1[ssize++] = -1;
}
}
else
{
state->d[dsize] = diff;
@@ -525,7 +525,7 @@ static int icvInitEMD( const float* signature1, int size1,
}
state->max_cost = max_cost;
memset( buffer, 0, buffer_end - buffer );
state->rows_x = (CvNode2D **) buffer;
@@ -1144,7 +1144,7 @@ float cv::EMD( InputArray _signature1, InputArray _signature2,
{
Mat signature1 = _signature1.getMat(), signature2 = _signature2.getMat();
Mat cost = _cost.getMat(), flow;
CvMat _csignature1 = signature1;
CvMat _csignature2 = signature2;
CvMat _ccost = cost, _cflow;
@@ -1154,7 +1154,7 @@ float cv::EMD( InputArray _signature1, InputArray _signature2,
flow = _flow.getMat();
_cflow = flow;
}
return cvCalcEMD2( &_csignature1, &_csignature2, distType, 0, cost.empty() ? 0 : &_ccost,
_flow.needed() ? &_cflow : 0, lowerBound, 0 );
}
modules/imgproc/src/featureselect.cpp
+6 -6
View File
@@ -51,14 +51,14 @@ template<typename T> struct greaterThanPtr
};
}
void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
int maxCorners, double qualityLevel, double minDistance,
InputArray _mask, int blockSize,
bool useHarrisDetector, double harrisK )
{
Mat image = _image.getMat(), mask = _mask.getMat();
CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) );
@@ -116,7 +116,7 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
int y = (int)(ofs / eig.step);
int x = (int)((ofs - y*eig.step)/sizeof(float));
bool good = true;
bool good = true;
int x_cell = x / cell_size;
int y_cell = y / cell_size;
@@ -135,7 +135,7 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
for( int yy = y1; yy <= y2; yy++ )
{
for( int xx = x1; xx <= x2; xx++ )
{
{
vector <Point2f> &m = grid[yy*grid_width + xx];
if( m.size() )
@@ -151,7 +151,7 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
goto break_out;
}
}
}
}
}
}
@@ -185,7 +185,7 @@ void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
break;
}
}
Mat(corners).convertTo(_corners, _corners.fixedType() ? _corners.type() : CV_32F);
/*
modules/imgproc/src/gabor.cpp
+7 -7
View File
@@ -56,34 +56,34 @@ cv::Mat cv::getGaborKernel( Size ksize, double sigma, double theta,
int nstds = 3;
int xmin, xmax, ymin, ymax;
double c = cos(theta), s = sin(theta);
if( ksize.width > 0 )
xmax = ksize.width/2;
else
xmax = cvRound(std::max(fabs(nstds*sigma_x*c), fabs(nstds*sigma_y*s)));
if( ksize.height > 0 )
ymax = ksize.height/2;
else
ymax = cvRound(std::max(fabs(nstds*sigma_x*s), fabs(nstds*sigma_y*c)));
xmin = -xmax;
ymin = -ymax;
CV_Assert( ktype == CV_32F || ktype == CV_64F );
Mat kernel(ymax - ymin + 1, xmax - xmin + 1, ktype);
double scale = 1;
double ex = -0.5/(sigma_x*sigma_x);
double ey = -0.5/(sigma_y*sigma_y);
double cscale = CV_PI*2/lambd;
for( int y = ymin; y <= ymax; y++ )
for( int x = xmin; x <= xmax; x++ )
{
double xr = x*c + y*s;
double yr = -x*s + y*c;
double v = scale*exp(ex*xr*xr + ey*yr*yr)*cos(cscale*xr + psi);
if( ktype == CV_32F )
kernel.at<float>(ymax - y, xmax - x) = (float)v;
modules/imgproc/src/geometry.cpp
+55 -55
View File
@@ -131,7 +131,7 @@ CV_IMPL double
cvPointPolygonTest( const CvArr* _contour, CvPoint2D32f pt, int measure_dist )
{
double result = 0;
CvSeqBlock block;
CvContour header;
CvSeq* contour = (CvSeq*)_contour;
@@ -256,7 +256,7 @@ cvPointPolygonTest( const CvArr* _contour, CvPoint2D32f pt, int measure_dist )
for( i = 0; i < total; i++ )
{
double dx, dy, dx1, dy1, dx2, dy2, dist_num, dist_denom = 1;
v0 = v;
if( is_float )
{
@@ -267,11 +267,11 @@ cvPointPolygonTest( const CvArr* _contour, CvPoint2D32f pt, int measure_dist )
CV_READ_SEQ_ELEM( iv, reader );
v = cvPointTo32f( iv );
}
dx = v.x - v0.x; dy = v.y - v0.y;
dx1 = pt.x - v0.x; dy1 = pt.y - v0.y;
dx2 = pt.x - v.x; dy2 = pt.y - v.y;
if( dx1*dx + dy1*dy <= 0 )
dist_num = dx1*dx1 + dy1*dy1;
else if( dx2*dx + dy2*dy >= 0 )
@@ -316,7 +316,7 @@ cvPointPolygonTest( const CvArr* _contour, CvPoint2D32f pt, int measure_dist )
This code is described in "Computational Geometry in C" (Second Edition),
Chapter 7. It is not written to be comprehensible without the
explanation in that book.
Written by Joseph O'Rourke.
Last modified: December 1997
Questions to orourke@cs.smith.edu.
@@ -345,7 +345,7 @@ static int areaSign( Point2f a, Point2f b, Point2f c )
static bool between( Point2f a, Point2f b, Point2f c )
{
Point2f ba, ca;
// If ab not vertical, check betweenness on x; else on y.
if ( a.x != b.x )
return ((a.x <= c.x) && (c.x <= b.x)) ||
@@ -394,38 +394,38 @@ static char segSegInt( Point2f a, Point2f b, Point2f c, Point2f d, Point2f& p, P
double s, t; // The two parameters of the parametric eqns.
double num, denom; // Numerator and denoninator of equations.
char code = '?'; // Return char characterizing intersection.
denom = a.x * (double)( d.y - c.y ) +
b.x * (double)( c.y - d.y ) +
d.x * (double)( b.y - a.y ) +
c.x * (double)( a.y - b.y );
// If denom is zero, then segments are parallel: handle separately.
if (denom == 0.0)
return parallelInt(a, b, c, d, p, q);
num = a.x * (double)( d.y - c.y ) +
c.x * (double)( a.y - d.y ) +
d.x * (double)( c.y - a.y );
if ( (num == 0.0) || (num == denom) ) code = 'v';
s = num / denom;
num = -( a.x * (double)( c.y - b.y ) +
b.x * (double)( a.y - c.y ) +
c.x * (double)( b.y - a.y ) );
if ( (num == 0.0) || (num == denom) ) code = 'v';
t = num / denom;
if ( (0.0 < s) && (s < 1.0) &&
(0.0 < t) && (t < 1.0) )
code = '1';
else if ( (0.0 > s) || (s > 1.0) ||
(0.0 > t) || (t > 1.0) )
code = '0';
p.x = (float)(a.x + s*(b.x - a.x));
p.y = (float)(a.y + s*(b.y - a.y));
return code;
}
@@ -446,7 +446,7 @@ static int advance( int a, int *aa, int n, bool inside, Point2f v, Point2f*& res
*result++ = v;
(*aa)++;
return (a+1) % n;
}
}
static void addSharedSeg( Point2f p, Point2f q, Point2f*& result )
{
@@ -469,19 +469,19 @@ static int intersectConvexConvex_( const Point2f* P, int n, const Point2f* Q, in
bool FirstPoint=true;// Is this the first point? (used to initialize).
Point2f p0; // The first point.
*result++ = Point2f(FLT_MAX, FLT_MAX);
do
{
// Computations of key variables.
int a1 = (a + n - 1) % n; // a-1, b-1 (resp.)
int b1 = (b + m - 1) % m;
Point2f A = P[a] - P[a1], B = Q[b] - Q[b1]; // directed edges on P and Q (resp.)
int cross = areaSign( Origin, A, B ); // sign of z-component of A x B
int aHB = areaSign( Q[b1], Q[b], P[a] ); // a in H(b).
int bHA = areaSign( P[a1], P[a], Q[b] ); // b in H(A);
// If A & B intersect, update inflag.
Point2f p, q;
int code = segSegInt( P[a1], P[a], Q[b1], Q[b], p, q );
@@ -496,20 +496,20 @@ static int intersectConvexConvex_( const Point2f* P, int n, const Point2f* Q, in
}
inflag = inOut( p, inflag, aHB, bHA, result );
}
//-----Advance rules-----
// Special case: A & B overlap and oppositely oriented.
if( code == 'e' && A.ddot(B) < 0 )
{
addSharedSeg( p, q, result );
return (int)(result - result0);
}
// Special case: A & B parallel and separated.
if( cross == 0 && aHB < 0 && bHA < 0 )
return (int)(result - result0);
// Special case: A & B collinear.
else if ( cross == 0 && aHB == 0 && bHA == 0 ) {
// Advance but do not output point.
@@ -518,7 +518,7 @@ static int intersectConvexConvex_( const Point2f* P, int n, const Point2f* Q, in
else
a = advance( a, &aa, n, inflag == Pin, P[a], result );
}
// Generic cases.
else if( cross >= 0 )
{
@@ -537,14 +537,14 @@ static int intersectConvexConvex_( const Point2f* P, int n, const Point2f* Q, in
// Quit when both adv. indices have cycled, or one has cycled twice.
}
while ( ((aa < n) || (ba < m)) && (aa < 2*n) && (ba < 2*m) );
// Deal with special cases: not implemented.
if( inflag == Unknown )
{
// The boundaries of P and Q do not cross.
// ...
}
int i, nr = (int)(result - result0);
double area = 0;
Point2f prev = result0[nr-1];
@@ -554,44 +554,44 @@ static int intersectConvexConvex_( const Point2f* P, int n, const Point2f* Q, in
area += (double)prev.x*result0[i].y - (double)prev.y*result0[i].x;
prev = result0[i];
}
*_area = (float)(area*0.5);
if( result0[nr-2] == result0[0] && nr > 1 )
nr--;
return nr-1;
}
}
float cv::intersectConvexConvex( InputArray _p1, InputArray _p2, OutputArray _p12, bool handleNested )
{
Mat p1 = _p1.getMat(), p2 = _p2.getMat();
CV_Assert( p1.depth() == CV_32S || p1.depth() == CV_32F );
CV_Assert( p2.depth() == CV_32S || p2.depth() == CV_32F );
int n = p1.checkVector(2, p1.depth(), true);
int m = p2.checkVector(2, p2.depth(), true);
CV_Assert( n >= 0 && m >= 0 );
if( n < 2 || m < 2 )
{
_p12.release();
return 0.f;
}
AutoBuffer<Point2f> _result(n*2 + m*2 + 1);
Point2f *fp1 = _result, *fp2 = fp1 + n;
Point2f* result = fp2 + m;
int orientation = 0;
for( int k = 1; k <= 2; k++ )
{
Mat& p = k == 1 ? p1 : p2;
int len = k == 1 ? n : m;
Point2f* dst = k == 1 ? fp1 : fp2;
Mat temp(p.size(), CV_MAKETYPE(CV_32F, p.channels()), dst);
p.convertTo(temp, CV_32F);
CV_Assert( temp.ptr<Point2f>() == dst );
@@ -610,7 +610,7 @@ float cv::intersectConvexConvex( InputArray _p1, InputArray _p2, OutputArray _p1
}
}
}
float area = 0.f;
int nr = intersectConvexConvex_(fp1, n, fp2, m, result, &area);
if( nr == 0 )
@@ -620,7 +620,7 @@ float cv::intersectConvexConvex( InputArray _p1, InputArray _p2, OutputArray _p1
_p12.release();
return 0.f;
}
if( pointPolygonTest(_InputArray(fp1, n), fp2[0], false) >= 0 )
{
result = fp2;
@@ -638,7 +638,7 @@ float cv::intersectConvexConvex( InputArray _p1, InputArray _p2, OutputArray _p1
}
area = (float)contourArea(_InputArray(result, nr), false);
}
if( _p12.needed() )
{
Mat temp(nr, 1, CV_32FC2, result);
@@ -662,7 +662,7 @@ static void testConvConv()
100, 100,
0, 100,
};
static const int Q1[] =
{
100, 80,
@@ -670,7 +670,7 @@ static void testConvConv()
50, 50,
100, 50
};
static const int P2[] =
{
0, 0,
@@ -679,7 +679,7 @@ static void testConvConv()
100, 200,
0, 100
};
static const int Q2[] =
{
100, 100,
@@ -687,7 +687,7 @@ static void testConvConv()
300, 200,
100, 200
};
static const int P3[] =
{
0, 0,
@@ -695,7 +695,7 @@ static void testConvConv()
100, 100,
0, 100
};
static const int Q3[] =
{
50, 50,
@@ -703,7 +703,7 @@ static void testConvConv()
150, 150,
50, 150
};
static const int P4[] =
{
0, 160,
@@ -717,7 +717,7 @@ static void testConvConv()
70, 320,
30, 290
};
static const int Q4[] =
{
160, -30,
@@ -726,12 +726,12 @@ static void testConvConv()
0, 220,
30, 100
};
static const void* PQs[] =
{
P1, Q1, P2, Q2, P3, Q3, P4, Q4
};
static const int lens[] =
{
CV_DIM(P1), CV_DIM(Q1),
@@ -739,36 +739,36 @@ static void testConvConv()
CV_DIM(P3), CV_DIM(Q3),
CV_DIM(P4), CV_DIM(Q4)
};
Mat img(800, 800, CV_8UC3);
for( int i = 0; i < CV_DIM(PQs)/2; i++ )
{
Mat Pm = Mat(lens[i*2]/2, 1, CV_32SC2, (void*)PQs[i*2]) + Scalar(100, 100);
Mat Qm = Mat(lens[i*2+1]/2, 1, CV_32SC2, (void*)PQs[i*2+1]) + Scalar(100, 100);
Point* P = Pm.ptr<Point>();
Point* Q = Qm.ptr<Point>();
flip(Pm, Pm, 0);
flip(Qm, Qm, 0);
Mat Rm;
intersectConvexConvex(Pm, Qm, Rm);
std::cout << Rm << std::endl << std::endl;
img = Scalar::all(0);
polylines(img, Pm, true, Scalar(0,255,0), 1, CV_AA, 0);
polylines(img, Qm, true, Scalar(0,0,255), 1, CV_AA, 0);
Mat temp;
Rm.convertTo(temp, CV_32S, 256);
polylines(img, temp, true, Scalar(128, 255, 255), 3, CV_AA, 8);
namedWindow("test", 1);
imshow("test", img);
waitKey();
}
}
*/
/* End of file. */
modules/imgproc/src/grabcut.cpp
+3 -3
View File
@@ -119,7 +119,7 @@ double GMM::operator()( int ci, const Vec3d color ) const
double res = 0;
if( coefs[ci] > 0 )
{
CV_Assert( covDeterms[ci] > std::numeric_limits<double>::epsilon() );
CV_Assert( covDeterms[ci] > std::numeric_limits<double>::epsilon() );
Vec3d diff = color;
double* m = mean + 3*ci;
diff[0] -= m[0]; diff[1] -= m[1]; diff[2] -= m[2];
@@ -138,7 +138,7 @@ int GMM::whichComponent( const Vec3d color ) const
for( int ci = 0; ci < componentsCount; ci++ )
{
double p = (*this)( ci, color );
double p = (*this)( ci, color );
if( p > max )
{
k = ci;
@@ -406,7 +406,7 @@ static void assignGMMsComponents( const Mat& img, const Mat& mask, const GMM& bg
for( p.x = 0; p.x < img.cols; p.x++ )
{
Vec3d color = img.at<Vec3b>(p);
compIdxs.at<int>(p) = mask.at<uchar>(p) == GC_BGD || mask.at<uchar>(p) == GC_PR_BGD ?
compIdxs.at<int>(p) = mask.at<uchar>(p) == GC_BGD || mask.at<uchar>(p) == GC_PR_BGD ?
bgdGMM.whichComponent(color) : fgdGMM.whichComponent(color);
}
}
modules/imgproc/src/imgwarp.cpp
+73 -73
View File
@@ -251,12 +251,12 @@ public:
ify(_ify)
{
}
virtual void operator() (const Range& range) const
{
Size ssize = src.size(), dsize = dst.size();
int y, x, pix_size = (int)src.elemSize();
for( y = range.start; y < range.end; y++ )
{
uchar* D = dst.data + dst.step*y;
@@ -327,7 +327,7 @@ public:
}
}
}
private:
const Mat src;
Mat dst;
@@ -354,7 +354,7 @@ resizeNN( const Mat& src, Mat& dst, double fx, double fy )
int sx = cvFloor(x*ifx);
x_ofs[x] = std::min(sx, ssize.width-1)*pix_size;
}
Range range(0, dsize.height);
resizeNNInvoker invoker(src, dst, x_ofs, pix_size4, ify);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
@@ -1132,7 +1132,7 @@ public:
typedef typename HResize::value_type T;
typedef typename HResize::buf_type WT;
typedef typename HResize::alpha_type AT;
resizeGeneric_Invoker(const Mat& _src, Mat &_dst, const int *_xofs, const int *_yofs,
const AT* _alpha, const AT* __beta, const Size& _ssize, const Size &_dsize,
int _ksize, int _xmin, int _xmax) :
@@ -1141,13 +1141,13 @@ public:
ksize(_ksize), xmin(_xmin), xmax(_xmax)
{
}
virtual void operator() (const Range& range) const
{
int dy, cn = src.channels();
HResize hresize;
VResize vresize;
int bufstep = (int)alignSize(dsize.width, 16);
AutoBuffer<WT> _buffer(bufstep*ksize);
const T* srows[MAX_ESIZE]={0};
@@ -1159,9 +1159,9 @@ public:
prev_sy[k] = -1;
rows[k] = (WT*)_buffer + bufstep*k;
}
const AT* beta = _beta + ksize * range.start;
for( dy = range.start; dy < range.end; dy++, beta += ksize )
{
int sy0 = yofs[dy], k0=ksize, k1=0, ksize2 = ksize/2;
@@ -1190,7 +1190,7 @@ public:
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
}
}
private:
Mat src;
Mat dst;
@@ -1218,7 +1218,7 @@ static void resizeGeneric_( const Mat& src, Mat& dst,
xmin *= cn;
xmax *= cn;
// image resize is a separable operation. In case of not too strong
Range range(0, dsize.height);
resizeGeneric_Invoker<HResize, VResize> invoker(src, dst, xofs, yofs, (const AT*)_alpha, beta,
ssize, dsize, ksize, xmin, xmax);
@@ -1238,18 +1238,18 @@ struct ResizeAreaFastVec
{
ResizeAreaFastVec(int _scale_x, int _scale_y, int _cn, int _step/*, const int* _ofs*/) :
scale_x(_scale_x), scale_y(_scale_y), cn(_cn), step(_step)/*, ofs(_ofs)*/
{
fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
{
fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
}
int operator() (const T* S, T* D, int w) const
{
if( !fast_mode )
return 0;
const T* nextS = (const T*)((const uchar*)S + step);
int dx = 0;
if (cn == 1)
for( ; dx < w; ++dx )
{
@@ -1276,10 +1276,10 @@ struct ResizeAreaFastVec
D[dx+3] = (T)((S[index+3] + S[index+7] + nextS[index+3] + nextS[index+7] + 2) >> 2);
}
}
return dx;
}
private:
int scale_x, scale_y;
int cn;
@@ -1298,7 +1298,7 @@ public:
scale_y(_scale_y), ofs(_ofs), xofs(_xofs)
{
}
virtual void operator() (const Range& range) const
{
Size ssize = src.size(), dsize = dst.size();
@@ -1309,15 +1309,15 @@ public:
dsize.width *= cn;
ssize.width *= cn;
int dy, dx, k = 0;
VecOp vop(scale_x, scale_y, src.channels(), (int)src.step/*, area_ofs*/);
for( dy = range.start; dy < range.end; dy++ )
{
T* D = (T*)(dst.data + dst.step*dy);
int sy0 = dy*scale_y;
int w = sy0 + scale_y <= ssize.height ? dwidth1 : 0;
if( sy0 >= ssize.height )
{
for( dx = 0; dx < dsize.width; dx++ )
@@ -1366,7 +1366,7 @@ public:
}
}
}
private:
Mat src;
Mat dst;
@@ -1379,7 +1379,7 @@ static void resizeAreaFast_( const Mat& src, Mat& dst, const int* ofs, const int
int scale_x, int scale_y )
{
Range range(0, dst.rows);
resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
resizeAreaFast_Invoker<T, WT, VecOp> invoker(src, dst, scale_x,
scale_y, ofs, xofs);
parallel_for_(range, invoker, dst.total()/(double)(1<<16));
}
@@ -1395,16 +1395,16 @@ class resizeArea_Invoker :
public ParallelLoopBody
{
public:
resizeArea_Invoker(const Mat& _src, Mat& _dst, const DecimateAlpha* _xofs,
int _xofs_count, double _scale_y_, const int* _cur_dy_ofs,
resizeArea_Invoker(const Mat& _src, Mat& _dst, const DecimateAlpha* _xofs,
int _xofs_count, double _scale_y_, const int* _cur_dy_ofs,
const std::vector<std::pair<int, int> >& _bands) :
ParallelLoopBody(), src(_src), dst(_dst), xofs(_xofs),
ParallelLoopBody(), src(_src), dst(_dst), xofs(_xofs),
xofs_count(_xofs_count), scale_y_(_scale_y_),
cur_dy_ofs(_cur_dy_ofs), bands(_bands)
{
}
void resize_single_band(const Range& range) const
void resize_single_band(const Range& range) const
{
Size ssize = src.size(), dsize = dst.size();
int cn = src.channels();
@@ -1413,11 +1413,11 @@ public:
WT *buf = _buffer, *sum = buf + dsize.width;
int k = 0, sy = 0, dx = 0, cur_dy = 0;
WT scale_y = (WT)scale_y_;
CV_Assert( cn <= 4 );
for( dx = 0; dx < dsize.width; dx++ )
buf[dx] = sum[dx] = 0;
cur_dy = cur_dy_ofs[range.start];
for (sy = range.start; sy < range.end; sy++)
{
@@ -1463,7 +1463,7 @@ public:
t1 = buf[dxn+3] + S[sxn+3]*alpha;
buf[dxn+2] = t0; buf[dxn+3] = t1;
}
if( (cur_dy + 1)*scale_y <= sy + 1 || sy == ssize.height - 1 )
{
WT beta = std::max(sy + 1 - (cur_dy+1)*scale_y, (WT)0);
@@ -1481,7 +1481,7 @@ public:
}
else
for( dx = 0; dx < dsize.width; dx++ )
{
{
D[dx] = saturate_cast<T>((sum[dx] + buf[dx]* beta1)/ min(scale_y, src.rows - cur_dy*scale_y)); //
sum[dx] = buf[dx]*beta;
buf[dx] = 0;
@@ -1505,7 +1505,7 @@ public:
}
}
}
virtual void operator() (const Range& range) const
{
for (int i = range.start; i < range.end; ++i)
@@ -1514,7 +1514,7 @@ public:
resize_single_band(band_range);
}
}
private:
Mat src;
Mat dst;
@@ -1533,11 +1533,11 @@ static void resizeArea_( const Mat& src, Mat& dst, const DecimateAlpha* xofs, in
int *cur_dy_ofs = _yofs;
int cur_dy = 0, index = 0;
std::vector<std::pair<int, int> > bands;
for (int sy = 0; sy < ssize.height; sy++)
{
cur_dy_ofs[sy] = cur_dy;
if ((cur_dy + 1) * scale_y_ <= sy + 1 || sy == ssize.height - 1 )
{
WT beta = (WT)std::max(sy + 1 - (cur_dy + 1) * scale_y_, 0.);
@@ -1569,7 +1569,7 @@ typedef void (*ResizeAreaFastFunc)( const Mat& src, Mat& dst,
int scale_x, int scale_y );
typedef void (*ResizeAreaFunc)( const Mat& src, Mat& dst,
const DecimateAlpha* xofs, int xofs_count,
const DecimateAlpha* xofs, int xofs_count,
double scale_y_);
}
@@ -1667,7 +1667,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
static ResizeAreaFastFunc areafast_tab[] =
{
resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar> >,
resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar> >,
0,
resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort> >,
resizeAreaFast_<short, float, ResizeAreaFastVec<short> >,
@@ -1679,7 +1679,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
static ResizeAreaFunc area_tab[] =
{
resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
resizeArea_<uchar, float>, 0, resizeArea_<ushort, float>,
resizeArea_<short, float>, 0, resizeArea_<float, float>,
resizeArea_<double, double>, 0
};
@@ -1718,15 +1718,15 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
resizeNN( src, dst, inv_scale_x, inv_scale_y );
return;
}
{
int iscale_x = saturate_cast<int>(scale_x);
int iscale_y = saturate_cast<int>(scale_y);
bool is_area_fast = std::abs(scale_x - iscale_x) < DBL_EPSILON &&
std::abs(scale_y - iscale_y) < DBL_EPSILON;
// in case of scale_x && scale_y is equal to 2
// in case of scale_x && scale_y is equal to 2
// INTER_AREA (fast) also is equal to INTER_LINEAR
if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
{
@@ -1801,7 +1801,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
xofs[k++].alpha = (float)(min(fsx2 - sx2, 1.) / min(scale_x, src.cols - fsx1));
}
}
func( src, dst, xofs, k, scale_y);
return;
}
@@ -2684,15 +2684,15 @@ class RemapInvoker :
public ParallelLoopBody
{
public:
RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
RemapInvoker(const Mat& _src, Mat& _dst, const Mat *_m1,
const Mat *_m2, int _interpolation, int _borderType, const Scalar &_borderValue,
int _planar_input, RemapNNFunc _nnfunc, RemapFunc _ifunc, const void *_ctab) :
ParallelLoopBody(), src(&_src), dst(&_dst), m1(_m1), m2(_m2),
interpolation(_interpolation), borderType(_borderType), borderValue(_borderValue),
interpolation(_interpolation), borderType(_borderType), borderValue(_borderValue),
planar_input(_planar_input), nnfunc(_nnfunc), ifunc(_ifunc), ctab(_ctab)
{
}
{
}
virtual void operator() (const Range& range) const
{
int x, y, x1, y1;
@@ -2866,7 +2866,7 @@ public:
}
}
}
private:
const Mat* src;
Mat* dst;
@@ -2972,7 +2972,7 @@ void cv::remap( InputArray _src, OutputArray _dst,
planar_input = map1.channels() == 1;
}
RemapInvoker invoker(src, dst, m1, m2, interpolation,
RemapInvoker invoker(src, dst, m1, m2, interpolation,
borderType, borderValue, planar_input, nnfunc, ifunc,
ctab);
parallel_for_(Range(0, dst.rows), invoker, dst.total()/(double)(1<<16));
@@ -3117,33 +3117,33 @@ void cv::convertMaps( InputArray _map1, InputArray _map2,
}
}
namespace cv
{
class warpAffineInvoker :
class warpAffineInvoker :
public ParallelLoopBody
{
public:
warpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
warpAffineInvoker(const Mat &_src, Mat &_dst, int _interpolation, int _borderType,
const Scalar &_borderValue, int *_adelta, int *_bdelta, double *_M) :
ParallelLoopBody(), src(_src), dst(_dst), interpolation(_interpolation),
borderType(_borderType), borderValue(_borderValue), adelta(_adelta), bdelta(_bdelta),
M(_M)
{
}
virtual void operator() (const Range& range) const
{
const int BLOCK_SZ = 64;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
const int AB_BITS = MAX(10, (int)INTER_BITS);
const int AB_SCALE = 1 << AB_BITS;
const int AB_SCALE = 1 << AB_BITS;
int round_delta = interpolation == INTER_NEAREST ? AB_SCALE/2 : AB_SCALE/INTER_TAB_SIZE/2, x, y, x1, y1;
#if CV_SSE2
bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
#endif
int bh0 = std::min(BLOCK_SZ/2, dst.rows);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, dst.cols);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, dst.rows);
@@ -3232,7 +3232,7 @@ public:
}
}
}
private:
Mat src;
Mat dst;
@@ -3243,8 +3243,8 @@ private:
};
}
void cv::warpAffine( InputArray _src, OutputArray _dst,
InputArray _M0, Size dsize,
int flags, int borderType, const Scalar& borderValue )
@@ -3308,41 +3308,41 @@ class warpPerspectiveInvoker :
public ParallelLoopBody
{
public:
warpPerspectiveInvoker(const Mat &_src, Mat &_dst, double *_M, int _interpolation,
int _borderType, const Scalar &_borderValue) :
ParallelLoopBody(), src(_src), dst(_dst), M(_M), interpolation(_interpolation),
borderType(_borderType), borderValue(_borderValue)
{
}
virtual void operator() (const Range& range) const
{
const int BLOCK_SZ = 32;
short XY[BLOCK_SZ*BLOCK_SZ*2], A[BLOCK_SZ*BLOCK_SZ];
int x, y, x1, y1, width = dst.cols, height = dst.rows;
int bh0 = std::min(BLOCK_SZ/2, height);
int bw0 = std::min(BLOCK_SZ*BLOCK_SZ/bh0, width);
bh0 = std::min(BLOCK_SZ*BLOCK_SZ/bw0, height);
for( y = range.start; y < range.end; y += bh0 )
{
for( x = 0; x < width; x += bw0 )
{
int bw = std::min( bw0, width - x);
int bh = std::min( bh0, range.end - y); // height
Mat _XY(bh, bw, CV_16SC2, XY), matA;
Mat dpart(dst, Rect(x, y, bw, bh));
for( y1 = 0; y1 < bh; y1++ )
{
short* xy = XY + y1*bw*2;
double X0 = M[0]*x + M[1]*(y + y1) + M[2];
double Y0 = M[3]*x + M[4]*(y + y1) + M[5];
double W0 = M[6]*x + M[7]*(y + y1) + M[8];
if( interpolation == INTER_NEAREST )
for( x1 = 0; x1 < bw; x1++ )
{
@@ -3352,7 +3352,7 @@ public:
double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3]*x1)*W));
int X = saturate_cast<int>(fX);
int Y = saturate_cast<int>(fY);
xy[x1*2] = saturate_cast<short>(X);
xy[x1*2+1] = saturate_cast<short>(Y);
}
@@ -3367,7 +3367,7 @@ public:
double fY = std::max((double)INT_MIN, std::min((double)INT_MAX, (Y0 + M[3]*x1)*W));
int X = saturate_cast<int>(fX);
int Y = saturate_cast<int>(fY);
xy[x1*2] = saturate_cast<short>(X >> INTER_BITS);
xy[x1*2+1] = saturate_cast<short>(Y >> INTER_BITS);
alpha[x1] = (short)((Y & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE +
@@ -3375,7 +3375,7 @@ public:
}
}
}
if( interpolation == INTER_NEAREST )
remap( src, dpart, _XY, Mat(), interpolation, borderType, borderValue );
else
@@ -3386,7 +3386,7 @@ public:
}
}
}
private:
Mat src;
Mat dst;
@@ -3394,7 +3394,7 @@ private:
int interpolation, borderType;
Scalar borderValue;
};
}
void cv::warpPerspective( InputArray _src, OutputArray _dst, InputArray _M0,
modules/imgproc/src/linefit.cpp
+2 -2
View File
@@ -394,7 +394,7 @@ static CvStatus icvFitLine2D( CvPoint2D32f * points, int count, int dist,
int first = 1;
for( i = 0; i < count; i++ )
w[i] = 0.f;
for( i = 0; i < MIN(count,10); )
{
j = cvRandInt(&rng) % count;
@@ -542,7 +542,7 @@ icvFitLine3D( CvPoint3D32f * points, int count, int dist,
int first = 1;
for( i = 0; i < count; i++ )
w[i] = 0.f;
for( i = 0; i < MIN(count,10); )
{
j = cvRandInt(&rng) % count;
modules/imgproc/src/matchcontours.cpp
+1 -1
View File
@@ -51,7 +51,7 @@
// method - method for the matching calculation
// (now CV_IPPI_CONTOURS_MATCH_I1, CV_CONTOURS_MATCH_I2 or
// CV_CONTOURS_MATCH_I3 only )
// rezult - output calculated measure
// rezult - output calculated measure
//
//F*/
CV_IMPL double
modules/imgproc/src/morph.cpp
+19 -19
View File
@@ -91,7 +91,7 @@ struct MorphNoVec
{
int operator()(uchar**, int, uchar*, int) const { return 0; }
};
#if CV_SSE2
template<class VecUpdate> struct MorphRowIVec
@@ -103,7 +103,7 @@ template<class VecUpdate> struct MorphRowIVec
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
cn *= ESZ;
int i, k, _ksize = ksize*cn;
width = (width & -4)*cn;
@@ -145,7 +145,7 @@ template<class VecUpdate> struct MorphRowFVec
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
int i, k, _ksize = ksize*cn;
width = (width & -4)*cn;
VecUpdate updateOp;
@@ -177,7 +177,7 @@ template<class VecUpdate> struct MorphColumnIVec
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
int i = 0, k, _ksize = ksize;
width *= ESZ;
VecUpdate updateOp;
@@ -281,7 +281,7 @@ template<class VecUpdate> struct MorphColumnFVec
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
int i = 0, k, _ksize = ksize;
VecUpdate updateOp;
@@ -410,7 +410,7 @@ template<class VecUpdate> struct MorphIVec
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
int i, k;
width *= ESZ;
VecUpdate updateOp;
@@ -457,7 +457,7 @@ template<class VecUpdate> struct MorphFVec
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
const float** src = (const float**)_src;
float* dst = (float*)_dst;
int i, k;
@@ -707,8 +707,8 @@ template<class Op, class VecOp> struct MorphColumnFilter : public BaseColumnFilt
for( ; _ksize > 1 && count > 1; count -= 2, D += dststep*2, src += 2 )
{
i = i0;
#if CV_ENABLE_UNROLLED
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[1] + i;
@@ -748,8 +748,8 @@ template<class Op, class VecOp> struct MorphColumnFilter : public BaseColumnFilt
for( ; count > 0; count--, D += dststep, src++ )
{
i = i0;
#if CV_ENABLE_UNROLLED
i = i0;
#if CV_ENABLE_UNROLLED
for( ; i <= width - 4; i += 4 )
{
const T* sptr = src[0] + i;
@@ -889,7 +889,7 @@ cv::Ptr<cv::BaseRowFilter> cv::getMorphologyRowFilter(int op, int type, int ksiz
if( depth == CV_64F )
return Ptr<BaseRowFilter>(new MorphRowFilter<MaxOp<double>,
DilateRowVec64f>(ksize, anchor));
}
}
CV_Error_( CV_StsNotImplemented, ("Unsupported data type (=%d)", type));
return Ptr<BaseRowFilter>(0);
@@ -1149,7 +1149,7 @@ static void morphOp( int op, InputArray _src, OutputArray _dst,
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if( iterations == 0 || kernel.rows*kernel.cols == 1 )
{
src.copyTo(dst);
@@ -1219,15 +1219,15 @@ void cv::morphologyEx( InputArray _src, OutputArray _dst, int op,
Mat src = _src.getMat(), temp;
_dst.create(src.size(), src.type());
Mat dst = _dst.getMat();
switch( op )
{
case MORPH_ERODE:
erode( src, dst, kernel, anchor, iterations, borderType, borderValue );
break;
break;
case MORPH_DILATE:
dilate( src, dst, kernel, anchor, iterations, borderType, borderValue );
break;
break;
case MORPH_OPEN:
erode( src, dst, kernel, anchor, iterations, borderType, borderValue );
dilate( dst, dst, kernel, anchor, iterations, borderType, borderValue );
@@ -1355,14 +1355,14 @@ cvMorphologyEx( const void* srcarr, void* dstarr, void*,
IplConvKernel* temp_element = NULL;
if (!element)
{
temp_element = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
temp_element = cvCreateStructuringElementEx(3, 3, 1, 1, CV_SHAPE_RECT);
} else {
temp_element = element;
temp_element = element;
}
convertConvKernel( temp_element, kernel, anchor );
if (!element)
{
cvReleaseStructuringElement(&temp_element);
cvReleaseStructuringElement(&temp_element);
}
cv::morphologyEx( src, dst, op, kernel, anchor, iterations, cv::BORDER_REPLICATE );
}
modules/imgproc/src/precomp.hpp
+1 -1
View File
@@ -43,7 +43,7 @@
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#ifdef HAVE_CVCONFIG_H
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif
modules/imgproc/src/pyramids.cpp
+6 -6
View File
@@ -72,7 +72,7 @@ struct PyrDownVec_32s8u
{
if( !checkHardwareSupport(CV_CPU_SSE2) )
return 0;
int x = 0;
const int *row0 = src[0], *row1 = src[1], *row2 = src[2], *row3 = src[3], *row4 = src[4];
__m128i delta = _mm_set1_epi16(128);
@@ -139,7 +139,7 @@ struct PyrDownVec_32f
{
if( !checkHardwareSupport(CV_CPU_SSE) )
return 0;
int x = 0;
const float *row0 = src[0], *row1 = src[1], *row2 = src[2], *row3 = src[3], *row4 = src[4];
__m128 _4 = _mm_set1_ps(4.f), _scale = _mm_set1_ps(1.f/256);
@@ -217,7 +217,7 @@ pyrDown_( const Mat& _src, Mat& _dst, int borderType )
tabR[x*cn + k] = sx1 + k;
}
}
ssize.width *= cn;
dsize.width *= cn;
width0 *= cn;
@@ -400,7 +400,7 @@ pyrUp_( const Mat& _src, Mat& _dst, int)
typedef void (*PyrFunc)(const Mat&, Mat&, int);
}
void cv::pyrDown( InputArray _src, OutputArray _dst, const Size& _dsz, int borderType )
{
Mat src = _src.getMat();
@@ -492,11 +492,11 @@ cvReleasePyramid( CvMat*** _pyramid, int extra_layers )
{
if( !_pyramid )
CV_Error( CV_StsNullPtr, "" );
if( *_pyramid )
for( int i = 0; i <= extra_layers; i++ )
cvReleaseMat( &(*_pyramid)[i] );
cvFree( _pyramid );
}
modules/imgproc/src/samplers.cpp
+1 -1
View File
@@ -50,7 +50,7 @@ cvSampleLine( const void* img, CvPoint pt1, CvPoint pt2,
void* _buffer, int connectivity )
{
int count = -1;
int i, coi = 0, pix_size;
CvMat stub, *mat = cvGetMat( img, &stub, &coi );
CvLineIterator iterator;
modules/imgproc/src/segmentation.cpp
+19 -19
View File
@@ -64,7 +64,7 @@ static CvWSNode*
icvAllocWSNodes( CvMemStorage* storage )
{
CvWSNode* n = 0;
int i, count = (storage->block_size - sizeof(CvMemBlock))/sizeof(*n) - 1;
n = (CvWSNode*)cvMemStorageAlloc( storage, count*sizeof(*n) );
@@ -83,7 +83,7 @@ cvWatershed( const CvArr* srcarr, CvArr* dstarr )
const int WSHED = -1;
const int NQ = 256;
cv::Ptr<CvMemStorage> storage;
CvMat sstub, *src;
CvMat dstub, *dst;
CvSize size;
@@ -149,7 +149,7 @@ cvWatershed( const CvArr* srcarr, CvArr* dstarr )
if( CV_MAT_TYPE(dst->type) != CV_32SC1 )
CV_Error( CV_StsUnsupportedFormat,
"Only 32-bit, 1-channel output images are supported" );
if( !CV_ARE_SIZES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedSizes, "The input and output images must have the same size" );
@@ -231,7 +231,7 @@ cvWatershed( const CvArr* srcarr, CvArr* dstarr )
int lab = 0, t;
int* m;
uchar* ptr;
if( q[active_queue].first == 0 )
{
for( i = active_queue+1; i < NQ; i++ )
@@ -316,13 +316,13 @@ void cv::watershed( InputArray _src, InputOutputArray markers )
\****************************************************************************************/
CV_IMPL void
cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
double sp0, double sr, int max_level,
CvTermCriteria termcrit )
{
const int cn = 3;
const int MAX_LEVELS = 8;
if( (unsigned)max_level > (unsigned)MAX_LEVELS )
CV_Error( CV_StsOutOfRange, "The number of pyramid levels is too large or negative" );
@@ -343,7 +343,7 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
if( src0.type() != CV_8UC3 )
CV_Error( CV_StsUnsupportedFormat, "Only 8-bit, 3-channel images are supported" );
if( src0.type() != dst0.type() )
CV_Error( CV_StsUnmatchedFormats, "The input and output images must have the same type" );
@@ -423,9 +423,9 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
for( i = 0; i < size.height; i++, sptr += sstep - size.width*3,
dptr += dstep - size.width*3,
mask += mstep )
{
{
for( j = 0; j < size.width; j++, sptr += 3, dptr += 3 )
{
{
int x0 = j, y0 = i, x1, y1, iter;
int c0, c1, c2;
@@ -449,46 +449,46 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
miny = cvRound(y0 - sp); miny = MAX(miny, 0);
maxx = cvRound(x0 + sp); maxx = MIN(maxx, size.width-1);
maxy = cvRound(y0 + sp); maxy = MIN(maxy, size.height-1);
ptr = sptr + (miny - i)*sstep + (minx - j)*3;
ptr = sptr + (miny - i)*sstep + (minx - j)*3;
for( y = miny; y <= maxy; y++, ptr += sstep - (maxx-minx+1)*3 )
{
int row_count = 0;
x = minx;
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; x + 3 <= maxx; x += 4, ptr += 12 )
{
int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
{
{
s0 += t0; s1 += t1; s2 += t2;
sx += x; row_count++;
}
t0 = ptr[3], t1 = ptr[4], t2 = ptr[5];
if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
{
{
s0 += t0; s1 += t1; s2 += t2;
sx += x+1; row_count++;
}
t0 = ptr[6], t1 = ptr[7], t2 = ptr[8];
if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
{
{
s0 += t0; s1 += t1; s2 += t2;
sx += x+2; row_count++;
}
t0 = ptr[9], t1 = ptr[10], t2 = ptr[11];
if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
{
{
s0 += t0; s1 += t1; s2 += t2;
sx += x+3; row_count++;
}
}
#endif
for( ; x <= maxx; x++, ptr += 3 )
{
{
int t0 = ptr[0], t1 = ptr[1], t2 = ptr[2];
if( tab[t0-c0+255] + tab[t1-c1+255] + tab[t2-c2+255] <= isr2 )
{
{
s0 += t0; s1 += t1; s2 += t2;
sx += x; row_count++;
}
@@ -510,7 +510,7 @@ cvPyrMeanShiftFiltering( const CvArr* srcarr, CvArr* dstarr,
stop_flag = (x0 == x1 && y0 == y1) || abs(x1-x0) + abs(y1-y0) +
tab[s0 - c0 + 255] + tab[s1 - c1 + 255] +
tab[s2 - c2 + 255] <= termcrit.epsilon;
x0 = x1; y0 = y1;
c0 = s0; c1 = s1; c2 = s2;
@@ -531,7 +531,7 @@ void cv::pyrMeanShiftFiltering( InputArray _src, OutputArray _dst,
TermCriteria termcrit )
{
Mat src = _src.getMat();
if( src.empty() )
return;
modules/imgproc/src/shapedescr.cpp
+80 -80
View File
@@ -1064,47 +1064,47 @@ cvBoundingRect( CvArr* array, int update )
if( xmin >= size.width )
xmin = ymin = 0;
}
else if( ptseq->total )
{
int is_float = CV_SEQ_ELTYPE(ptseq) == CV_32FC2;
cvStartReadSeq( ptseq, &reader, 0 );
CvPoint pt;
CV_READ_SEQ_ELEM( pt, reader );
#if CV_SSE4_2
if(cv::checkHardwareSupport(CV_CPU_SSE4_2))
{
if( !is_float )
{
}
else if( ptseq->total )
{
int is_float = CV_SEQ_ELTYPE(ptseq) == CV_32FC2;
cvStartReadSeq( ptseq, &reader, 0 );
CvPoint pt;
CV_READ_SEQ_ELEM( pt, reader );
#if CV_SSE4_2
if(cv::checkHardwareSupport(CV_CPU_SSE4_2))
{
if( !is_float )
{
__m128i minval, maxval;
minval = maxval = _mm_loadl_epi64((const __m128i*)(&pt)); //min[0]=pt.x, min[1]=pt.y
for( i = 1; i < ptseq->total; i++)
{
__m128i ptXY = _mm_loadl_epi64((const __m128i*)(reader.ptr));
minval = maxval = _mm_loadl_epi64((const __m128i*)(&pt)); //min[0]=pt.x, min[1]=pt.y
for( i = 1; i < ptseq->total; i++)
{
__m128i ptXY = _mm_loadl_epi64((const __m128i*)(reader.ptr));
CV_NEXT_SEQ_ELEM(sizeof(pt), reader);
minval = _mm_min_epi32(ptXY, minval);
maxval = _mm_max_epi32(ptXY, maxval);
}
minval = _mm_min_epi32(ptXY, minval);
maxval = _mm_max_epi32(ptXY, maxval);
}
xmin = _mm_cvtsi128_si32(minval);
ymin = _mm_cvtsi128_si32(_mm_srli_si128(minval, 4));
xmax = _mm_cvtsi128_si32(maxval);
ymax = _mm_cvtsi128_si32(_mm_srli_si128(maxval, 4));
}
else
{
}
else
{
__m128 minvalf, maxvalf, z = _mm_setzero_ps(), ptXY = _mm_setzero_ps();
minvalf = maxvalf = _mm_loadl_pi(z, (const __m64*)(&pt));
minvalf = maxvalf = _mm_loadl_pi(z, (const __m64*)(&pt));
for( i = 1; i < ptseq->total; i++ )
{
ptXY = _mm_loadl_pi(ptXY, (const __m64*)reader.ptr);
for( i = 1; i < ptseq->total; i++ )
{
ptXY = _mm_loadl_pi(ptXY, (const __m64*)reader.ptr);
CV_NEXT_SEQ_ELEM(sizeof(pt), reader);
minvalf = _mm_min_ps(minvalf, ptXY);
maxvalf = _mm_max_ps(maxvalf, ptXY);
}
minvalf = _mm_min_ps(minvalf, ptXY);
maxvalf = _mm_max_ps(maxvalf, ptXY);
}
float xyminf[2], xymaxf[2];
_mm_storel_pi((__m64*)xyminf, minvalf);
_mm_storel_pi((__m64*)xymaxf, maxvalf);
@@ -1113,72 +1113,72 @@ cvBoundingRect( CvArr* array, int update )
xmax = cvFloor(xymaxf[0]);
ymax = cvFloor(xymaxf[1]);
}
}
}
else
#endif
{
if( !is_float )
{
xmin = xmax = pt.x;
ymin = ymax = pt.y;
{
if( !is_float )
{
xmin = xmax = pt.x;
ymin = ymax = pt.y;
for( i = 1; i < ptseq->total; i++ )
{
CV_READ_SEQ_ELEM( pt, reader );
for( i = 1; i < ptseq->total; i++ )
{
CV_READ_SEQ_ELEM( pt, reader );
if( xmin > pt.x )
xmin = pt.x;
if( xmin > pt.x )
xmin = pt.x;
if( xmax < pt.x )
xmax = pt.x;
if( xmax < pt.x )
xmax = pt.x;
if( ymin > pt.y )
ymin = pt.y;
if( ymin > pt.y )
ymin = pt.y;
if( ymax < pt.y )
ymax = pt.y;
}
}
else
{
Cv32suf v;
// init values
xmin = xmax = CV_TOGGLE_FLT(pt.x);
ymin = ymax = CV_TOGGLE_FLT(pt.y);
if( ymax < pt.y )
ymax = pt.y;
}
}
else
{
Cv32suf v;
// init values
xmin = xmax = CV_TOGGLE_FLT(pt.x);
ymin = ymax = CV_TOGGLE_FLT(pt.y);
for( i = 1; i < ptseq->total; i++ )
{
CV_READ_SEQ_ELEM( pt, reader );
pt.x = CV_TOGGLE_FLT(pt.x);
pt.y = CV_TOGGLE_FLT(pt.y);
for( i = 1; i < ptseq->total; i++ )
{
CV_READ_SEQ_ELEM( pt, reader );
pt.x = CV_TOGGLE_FLT(pt.x);
pt.y = CV_TOGGLE_FLT(pt.y);
if( xmin > pt.x )
xmin = pt.x;
if( xmin > pt.x )
xmin = pt.x;
if( xmax < pt.x )
xmax = pt.x;
if( xmax < pt.x )
xmax = pt.x;
if( ymin > pt.y )
ymin = pt.y;
if( ymin > pt.y )
ymin = pt.y;
if( ymax < pt.y )
ymax = pt.y;
}
if( ymax < pt.y )
ymax = pt.y;
}
v.i = CV_TOGGLE_FLT(xmin); xmin = cvFloor(v.f);
v.i = CV_TOGGLE_FLT(ymin); ymin = cvFloor(v.f);
// because right and bottom sides of the bounding rectangle are not inclusive
// (note +1 in width and height calculation below), cvFloor is used here instead of cvCeil
v.i = CV_TOGGLE_FLT(xmax); xmax = cvFloor(v.f);
v.i = CV_TOGGLE_FLT(ymax); ymax = cvFloor(v.f);
}
}
v.i = CV_TOGGLE_FLT(xmin); xmin = cvFloor(v.f);
v.i = CV_TOGGLE_FLT(ymin); ymin = cvFloor(v.f);
// because right and bottom sides of the bounding rectangle are not inclusive
// (note +1 in width and height calculation below), cvFloor is used here instead of cvCeil
v.i = CV_TOGGLE_FLT(xmax); xmax = cvFloor(v.f);
v.i = CV_TOGGLE_FLT(ymax); ymax = cvFloor(v.f);
}
}
rect.x = xmin;
rect.y = ymin;
rect.width = xmax - xmin + 1;
rect.height = ymax - ymin + 1;
}
if( update )
}
if( update )
((CvContour*)ptseq)->rect = rect;
return rect;
}
modules/imgproc/src/smooth.cpp
+180 -180
View File
@@ -215,10 +215,10 @@ template<> struct ColumnSum<int, uchar> : public BaseColumnFilter
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
if( width != (int)sum.size() )
{
@@ -229,22 +229,22 @@ template<> struct ColumnSum<int, uchar> : public BaseColumnFilter
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_add_epi32(_sum, _sp));
}
}
#endif
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_add_epi32(_sum, _sp));
}
}
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
@@ -262,33 +262,33 @@ template<> struct ColumnSum<int, uchar> : public BaseColumnFilter
uchar* D = (uchar*)dst;
if( haveScale )
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
_mm_loadu_si128((const __m128i*)(Sp+i+4)));
__m128i _s0T = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
__m128i _s0T1 = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s01)));
_s0T = _mm_packs_epi32(_s0T, _s0T1);
__m128i _s0T = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
__m128i _s0T1 = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s01)));
_mm_storel_epi64((__m128i*)(D+i), _mm_packus_epi16(_s0T, _s0T));
_s0T = _mm_packs_epi32(_s0T, _s0T1);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
_mm_storel_epi64((__m128i*)(D+i), _mm_packus_epi16(_s0T, _s0T));
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
@@ -298,29 +298,29 @@ template<> struct ColumnSum<int, uchar> : public BaseColumnFilter
}
else
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
_mm_loadu_si128((const __m128i*)(Sp+i+4)));
__m128i _s0T = _mm_packs_epi32(_s0, _s01);
_mm_storel_epi64((__m128i*)(D+i), _mm_packus_epi16(_s0T, _s0T));
__m128i _s0T = _mm_packs_epi32(_s0, _s01);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
_mm_storel_epi64((__m128i*)(D+i), _mm_packus_epi16(_s0T, _s0T));
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
for( ; i < width; i++ )
{
@@ -357,9 +357,9 @@ template<> struct ColumnSum<int, short> : public BaseColumnFilter
bool haveScale = scale != 1;
double _scale = scale;
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
if( width != (int)sum.size() )
{
@@ -369,22 +369,22 @@ template<> struct ColumnSum<int, short> : public BaseColumnFilter
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_add_epi32(_sum, _sp));
}
}
#endif
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_add_epi32(_sum, _sp));
}
}
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
@@ -402,31 +402,31 @@ template<> struct ColumnSum<int, short> : public BaseColumnFilter
short* D = (short*)dst;
if( haveScale )
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
_mm_loadu_si128((const __m128i*)(Sp+i+4)));
__m128i _s0T = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
__m128i _s0T1 = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s01)));
_mm_storeu_si128((__m128i*)(D+i), _mm_packs_epi32(_s0T, _s0T1));
__m128i _s0T = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
__m128i _s0T1 = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s01)));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4), _mm_sub_epi32(_s01,_sm1));
}
}
#endif
_mm_storeu_si128((__m128i*)(D+i), _mm_packs_epi32(_s0T, _s0T1));
_mm_storeu_si128((__m128i*)(SUM+i),_mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4), _mm_sub_epi32(_s01,_sm1));
}
}
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
@@ -436,28 +436,28 @@ template<> struct ColumnSum<int, short> : public BaseColumnFilter
}
else
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-8; i+=8 )
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-8; i+=8 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _sm1 = _mm_loadu_si128((const __m128i*)(Sm+i+4));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
__m128i _s01 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i+4)),
_mm_loadu_si128((const __m128i*)(Sp+i+4)));
_mm_storeu_si128((__m128i*)(D+i), _mm_packs_epi32(_s0, _s01));
_mm_storeu_si128((__m128i*)(D+i), _mm_packs_epi32(_s0, _s01));
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
_mm_storeu_si128((__m128i*)(SUM+i+4),_mm_sub_epi32(_s01,_sm1));
}
}
#endif
for( ; i < width; i++ )
{
@@ -494,9 +494,9 @@ template<> struct ColumnSum<int, ushort> : public BaseColumnFilter
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
if( width != (int)sum.size() )
{
@@ -506,22 +506,22 @@ template<> struct ColumnSum<int, ushort> : public BaseColumnFilter
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i), _mm_add_epi32(_sum, _sp));
}
}
#endif
i = 0;
#if CV_SSE2
if(haveSSE2)
{
for( ; i < width-4; i+=4 )
{
__m128i _sum = _mm_loadu_si128((const __m128i*)(SUM+i));
__m128i _sp = _mm_loadu_si128((const __m128i*)(Sp+i));
_mm_storeu_si128((__m128i*)(SUM+i), _mm_add_epi32(_sum, _sp));
}
}
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
@@ -539,30 +539,30 @@ template<> struct ColumnSum<int, ushort> : public BaseColumnFilter
ushort* D = (ushort*)dst;
if( haveScale )
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
const __m128i delta0 = _mm_set1_epi32(0x8000);
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128 scale4 = _mm_set1_ps((float)_scale);
const __m128i delta0 = _mm_set1_epi32(0x8000);
const __m128i delta1 = _mm_set1_epi32(0x80008000);
for( ; i < width-4; i+=4)
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
for( ; i < width-4; i+=4)
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _res = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
__m128i _res = _mm_cvtps_epi32(_mm_mul_ps(scale4, _mm_cvtepi32_ps(_s0)));
_res = _mm_sub_epi32(_res, delta0);
_res = _mm_add_epi16(_mm_packs_epi32(_res, _res), delta1);
_mm_storel_epi64((__m128i*)(D+i), _res);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
}
}
#endif
_mm_storel_epi64((__m128i*)(D+i), _res);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
}
}
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
@@ -572,27 +572,27 @@ template<> struct ColumnSum<int, ushort> : public BaseColumnFilter
}
else
{
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128i delta0 = _mm_set1_epi32(0x8000);
i = 0;
#if CV_SSE2
if(haveSSE2)
{
const __m128i delta0 = _mm_set1_epi32(0x8000);
const __m128i delta1 = _mm_set1_epi32(0x80008000);
for( ; i < width-4; i+=4 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
for( ; i < width-4; i+=4 )
{
__m128i _sm = _mm_loadu_si128((const __m128i*)(Sm+i));
__m128i _s0 = _mm_add_epi32(_mm_loadu_si128((const __m128i*)(SUM+i)),
_mm_loadu_si128((const __m128i*)(Sp+i)));
__m128i _res = _mm_sub_epi32(_s0, delta0);
__m128i _res = _mm_sub_epi32(_s0, delta0);
_res = _mm_add_epi16(_mm_packs_epi32(_res, _res), delta1);
_mm_storel_epi64((__m128i*)(D+i), _res);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
}
}
#endif
_mm_storel_epi64((__m128i*)(D+i), _res);
_mm_storeu_si128((__m128i*)(SUM+i), _mm_sub_epi32(_s0,_sm));
}
}
#endif
for( ; i < width; i++ )
{
@@ -1712,7 +1712,7 @@ public:
maxk(_maxk), space_ofs(_space_ofs), space_weight(_space_weight), color_weight(_color_weight)
{
}
virtual void operator() (const Range& range) const
{
int i, j, cn = dest->channels(), k;
@@ -1723,12 +1723,12 @@ public:
static const int CV_DECL_ALIGNED(16) bufSignMask[] = { 0x80000000, 0x80000000, 0x80000000, 0x80000000 };
bool haveSSE3 = checkHardwareSupport(CV_CPU_SSE3);
#endif
for( i = range.start; i < range.end; i++ )
{
const uchar* sptr = temp->ptr(i+radius) + radius*cn;
uchar* dptr = dest->ptr(i);
if( cn == 1 )
{
for( j = 0; j < size.width; j++ )
@@ -1746,7 +1746,7 @@ public:
{
__m128 _valF = _mm_set_ps(sptr[j + space_ofs[k+3]], sptr[j + space_ofs[k+2]],
sptr[j + space_ofs[k+1]], sptr[j + space_ofs[k]]);
__m128 _val = _mm_andnot_ps(_signMask, _mm_sub_ps(_valF, _val0));
_mm_store_si128((__m128i*)buf, _mm_cvtps_epi32(_val));
@@ -1791,7 +1791,7 @@ public:
const __m128 _g0 = _mm_set1_ps(static_cast<float>(g0));
const __m128 _r0 = _mm_set1_ps(static_cast<float>(r0));
const __m128 _signMask = _mm_load_ps((const float*)bufSignMask);
for( ; k <= maxk - 4; k += 4 )
{
const uchar* sptr_k = sptr + j + space_ofs[k];
@@ -1851,7 +1851,7 @@ public:
}
}
}
private:
const Mat *temp;
Mat *dest;
@@ -1868,41 +1868,41 @@ bilateralFilter_8u( const Mat& src, Mat& dst, int d,
int cn = src.channels();
int i, j, maxk, radius;
Size size = src.size();
CV_Assert( (src.type() == CV_8UC1 || src.type() == CV_8UC3) &&
src.type() == dst.type() && src.size() == dst.size() &&
src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
if( d <= 0 )
radius = cvRound(sigma_space*1.5);
else
radius = d/2;
radius = MAX(radius, 1);
d = radius*2 + 1;
Mat temp;
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
vector<float> _color_weight(cn*256);
vector<float> _space_weight(d*d);
vector<int> _space_ofs(d*d);
float* color_weight = &_color_weight[0];
float* space_weight = &_space_weight[0];
int* space_ofs = &_space_ofs[0];
// initialize color-related bilateral filter coefficients
for( i = 0; i < 256*cn; i++ )
color_weight[i] = (float)std::exp(i*i*gauss_color_coeff);
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
{
@@ -1917,7 +1917,7 @@ bilateralFilter_8u( const Mat& src, Mat& dst, int d,
space_ofs[maxk++] = (int)(i*temp.step + j*cn);
}
}
BilateralFilter_8u_Invoker body(dst, temp, radius, maxk, space_ofs, space_weight, color_weight);
parallel_for_(Range(0, size.height), body, dst.total()/(double)(1<<16));
}
@@ -1964,7 +1964,7 @@ public:
const __m128 _val0 = _mm_set1_ps(sptr[j]);
const __m128 _scale_index = _mm_set1_ps(scale_index);
const __m128 _signMask = _mm_load_ps((const float*)bufSignMask);
for( ; k <= maxk - 4 ; k += 4 )
{
__m128 _sw = _mm_loadu_ps(space_weight + k);
@@ -1980,7 +1980,7 @@ public:
expLUT[idxBuf[1]], expLUT[idxBuf[0]]);
__m128 _explut1 = _mm_set_ps(expLUT[idxBuf[3]+1], expLUT[idxBuf[2]+1],
expLUT[idxBuf[1]+1], expLUT[idxBuf[0]+1]);
__m128 _w = _mm_mul_ps(_sw, _mm_add_ps(_explut, _mm_mul_ps(_alpha, _mm_sub_ps(_explut1, _explut))));
_val = _mm_mul_ps(_w, _val);
@@ -2023,7 +2023,7 @@ public:
const __m128 _r0 = _mm_set1_ps(r0);
const __m128 _scale_index = _mm_set1_ps(scale_index);
const __m128 _signMask = _mm_load_ps((const float*)bufSignMask);
for( ; k <= maxk-4; k += 4 )
{
__m128 _sw = _mm_loadu_ps(space_weight + k);
@@ -2049,7 +2049,7 @@ public:
__m128 _explut = _mm_set_ps(expLUT[idxBuf[3]], expLUT[idxBuf[2]], expLUT[idxBuf[1]], expLUT[idxBuf[0]]);
__m128 _explut1 = _mm_set_ps(expLUT[idxBuf[3]+1], expLUT[idxBuf[2]+1], expLUT[idxBuf[1]+1], expLUT[idxBuf[0]+1]);
__m128 _w = _mm_mul_ps(_sw, _mm_add_ps(_explut, _mm_mul_ps(_alpha, _mm_sub_ps(_explut1, _explut))));
_b = _mm_mul_ps(_b, _w);
@@ -2070,7 +2070,7 @@ public:
}
#endif
for(; k < maxk; k++ )
{
const float* sptr_k = sptr + j + space_ofs[k];
@@ -2099,7 +2099,7 @@ private:
Mat *dest;
float scale_index, *space_weight, *expLUT;
};
static void
bilateralFilter_32f( const Mat& src, Mat& dst, int d,
@@ -2176,7 +2176,7 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
}
// initialize space-related bilateral filter coefficients
for( i = -radius, maxk = 0; i <= radius; i++ )
for( i = -radius, maxk = 0; i <= radius; i++ )
for( j = -radius; j <= radius; j++ )
{
double r = std::sqrt((double)i*i + (double)j*j);
modules/imgproc/src/subdivision2d.cpp
+108 -108
View File
@@ -42,7 +42,7 @@
namespace cv
{
int Subdiv2D::nextEdge(int edge) const
{
CV_DbgAssert((size_t)(edge >> 2) < qedges.size());
@@ -114,7 +114,7 @@ Subdiv2D::Subdiv2D(Rect rect)
freeQEdge = 0;
freePoint = 0;
recentEdge = 0;
initDelaunay(rect);
}
@@ -132,7 +132,7 @@ Subdiv2D::QuadEdge::QuadEdge(int edgeidx)
next[1] = edgeidx+3;
next[2] = edgeidx+2;
next[3] = edgeidx+1;
pt[0] = pt[1] = pt[2] = pt[3] = 0;
}
@@ -187,10 +187,10 @@ void Subdiv2D::setEdgePoints(int edge, int orgPt, int dstPt)
int Subdiv2D::connectEdges( int edgeA, int edgeB )
{
int edge = newEdge();
splice(edge, getEdge(edgeA, NEXT_AROUND_LEFT));
splice(symEdge(edge), edgeB);
setEdgePoints(edge, edgeDst(edgeA), edgeOrg(edgeB));
return edge;
}
@@ -200,12 +200,12 @@ void Subdiv2D::swapEdges( int edge )
int sedge = symEdge(edge);
int a = getEdge(edge, PREV_AROUND_ORG);
int b = getEdge(sedge, PREV_AROUND_ORG);
splice(edge, a);
splice(sedge, b);
setEdgePoints(edge, edgeDst(a), edgeDst(b));
splice(edge, getEdge(a, NEXT_AROUND_LEFT));
splice(sedge, getEdge(b, NEXT_AROUND_LEFT));
}
@@ -213,15 +213,15 @@ void Subdiv2D::swapEdges( int edge )
static double triangleArea( Point2f a, Point2f b, Point2f c )
{
return ((double)b.x - a.x) * ((double)c.y - a.y) - ((double)b.y - a.y) * ((double)c.x - a.x);
}
}
int Subdiv2D::isRightOf(Point2f pt, int edge) const
{
Point2f org, dst;
edgeOrg(edge, &org);
edgeDst(edge, &dst);
double cw_area = triangleArea( pt, dst, org );
return (cw_area > 0) - (cw_area < 0);
}
@@ -244,7 +244,7 @@ void Subdiv2D::deleteEdge(int edge)
splice( edge, getEdge(edge, PREV_AROUND_ORG) );
int sedge = symEdge(edge);
splice(sedge, getEdge(sedge, PREV_AROUND_ORG) );
edge >>= 2;
qedges[edge].next[0] = 0;
qedges[edge].next[1] = freeQEdge;
@@ -261,7 +261,7 @@ int Subdiv2D::newPoint(Point2f pt, bool isvirtual, int firstEdge)
int vidx = freePoint;
freePoint = vtx[vidx].firstEdge;
vtx[vidx] = Vertex(pt, isvirtual, firstEdge);
return vidx;
}
@@ -276,35 +276,35 @@ void Subdiv2D::deletePoint(int vidx)
int Subdiv2D::locate(Point2f pt, int& _edge, int& _vertex)
{
int vertex = 0;
int i, maxEdges = (int)(qedges.size() * 4);
if( qedges.size() < (size_t)4 )
CV_Error( CV_StsError, "Subdivision is empty" );
if( pt.x < topLeft.x || pt.y < topLeft.y || pt.x >= bottomRight.x || pt.y >= bottomRight.y )
CV_Error( CV_StsOutOfRange, "" );
int edge = recentEdge;
CV_Assert(edge > 0);
int location = PTLOC_ERROR;
int right_of_curr = isRightOf(pt, edge);
if( right_of_curr > 0 )
{
edge = symEdge(edge);
right_of_curr = -right_of_curr;
}
for( i = 0; i < maxEdges; i++ )
{
int onext_edge = nextEdge( edge );
int dprev_edge = getEdge( edge, PREV_AROUND_DST );
int right_of_onext = isRightOf( pt, onext_edge );
int right_of_dprev = isRightOf( pt, dprev_edge );
if( right_of_dprev > 0 )
{
if( right_of_onext > 0 || (right_of_onext == 0 && right_of_curr == 0) )
@@ -345,22 +345,22 @@ int Subdiv2D::locate(Point2f pt, int& _edge, int& _vertex)
}
}
}
recentEdge = edge;
if( location == PTLOC_INSIDE )
{
Point2f org_pt, dst_pt;
edgeOrg(edge, &org_pt);
edgeDst(edge, &dst_pt);
double t1 = fabs( pt.x - org_pt.x );
t1 += fabs( pt.y - org_pt.y );
double t2 = fabs( pt.x - dst_pt.x );
t2 += fabs( pt.y - dst_pt.y );
double t3 = fabs( org_pt.x - dst_pt.x );
t3 += fabs( org_pt.y - dst_pt.y );
if( t1 < FLT_EPSILON )
{
location = PTLOC_VERTEX;
@@ -380,16 +380,16 @@ int Subdiv2D::locate(Point2f pt, int& _edge, int& _vertex)
vertex = 0;
}
}
if( location == PTLOC_ERROR )
{
edge = 0;
vertex = 0;
}
_edge = edge;
_vertex = vertex;
return location;
}
@@ -402,7 +402,7 @@ isPtInCircle3( Point2f pt, Point2f a, Point2f b, Point2f c)
val -= ((double)b.x * b.x + (double)b.y * b.y) * triangleArea( a, c, pt );
val += ((double)c.x * c.x + (double)c.y * c.y) * triangleArea( a, b, pt );
val -= ((double)pt.x * pt.x + (double)pt.y * pt.y) * triangleArea( a, b, c );
return val > eps ? 1 : val < -eps ? -1 : 0;
}
@@ -411,16 +411,16 @@ int Subdiv2D::insert(Point2f pt)
{
int curr_point = 0, curr_edge = 0, deleted_edge = 0;
int location = locate( pt, curr_edge, curr_point );
if( location == PTLOC_ERROR )
CV_Error( CV_StsBadSize, "" );
if( location == PTLOC_OUTSIDE_RECT )
CV_Error( CV_StsOutOfRange, "" );
if( location == PTLOC_VERTEX )
return curr_point;
if( location == PTLOC_ON_EDGE )
{
deleted_edge = curr_edge;
@@ -431,36 +431,36 @@ int Subdiv2D::insert(Point2f pt)
;
else
CV_Error_(CV_StsError, ("Subdiv2D::locate returned invalid location = %d", location) );
assert( curr_edge != 0 );
validGeometry = false;
curr_point = newPoint(pt, false);
int base_edge = newEdge();
int first_point = edgeOrg(curr_edge);
setEdgePoints(base_edge, first_point, curr_point);
splice(base_edge, curr_edge);
do
{
base_edge = connectEdges( curr_edge, symEdge(base_edge) );
curr_edge = getEdge(base_edge, PREV_AROUND_ORG);
}
while( edgeDst(curr_edge) != first_point );
curr_edge = getEdge( base_edge, PREV_AROUND_ORG );
int i, max_edges = (int)(qedges.size()*4);
for( i = 0; i < max_edges; i++ )
{
int temp_dst = 0, curr_org = 0, curr_dst = 0;
int temp_edge = getEdge( curr_edge, PREV_AROUND_ORG );
temp_dst = edgeDst( temp_edge );
curr_org = edgeOrg( curr_edge );
curr_dst = edgeDst( curr_edge );
if( isRightOf( vtx[temp_dst].pt, curr_edge ) > 0 &&
isPtInCircle3( vtx[curr_org].pt, vtx[temp_dst].pt,
vtx[curr_dst].pt, vtx[curr_point].pt ) < 0 )
@@ -473,7 +473,7 @@ int Subdiv2D::insert(Point2f pt)
else
curr_edge = getEdge( nextEdge( curr_edge ), PREV_AROUND_LEFT );
}
return curr_point;
}
@@ -488,42 +488,42 @@ void Subdiv2D::initDelaunay( Rect rect )
float big_coord = 3.f * MAX( rect.width, rect.height );
float rx = (float)rect.x;
float ry = (float)rect.y;
vtx.clear();
qedges.clear();
recentEdge = 0;
validGeometry = false;
topLeft = Point2f( rx, ry );
bottomRight = Point2f( rx + rect.width, ry + rect.height );
Point2f ppA( rx + big_coord, ry );
Point2f ppB( rx, ry + big_coord );
Point2f ppC( rx - big_coord, ry - big_coord );
vtx.push_back(Vertex());
qedges.push_back(QuadEdge());
freeQEdge = 0;
freePoint = 0;
int pA = newPoint(ppA, false);
int pB = newPoint(ppB, false);
int pC = newPoint(ppC, false);
int edge_AB = newEdge();
int edge_BC = newEdge();
int edge_CA = newEdge();
setEdgePoints( edge_AB, pA, pB );
setEdgePoints( edge_BC, pB, pC );
setEdgePoints( edge_CA, pC, pA );
splice( edge_AB, symEdge( edge_CA ));
splice( edge_BC, symEdge( edge_AB ));
splice( edge_CA, symEdge( edge_BC ));
recentEdge = edge_AB;
}
@@ -531,17 +531,17 @@ void Subdiv2D::initDelaunay( Rect rect )
void Subdiv2D::clearVoronoi()
{
size_t i, total = qedges.size();
for( i = 0; i < total; i++ )
qedges[i].pt[1] = qedges[i].pt[3] = 0;
total = vtx.size();
for( i = 0; i < total; i++ )
{
if( vtx[i].isvirtual() )
deletePoint((int)i);
}
validGeometry = false;
}
@@ -551,20 +551,20 @@ static Point2f computeVoronoiPoint(Point2f org0, Point2f dst0, Point2f org1, Poi
double a0 = dst0.x - org0.x;
double b0 = dst0.y - org0.y;
double c0 = -0.5*(a0 * (dst0.x + org0.x) + b0 * (dst0.y + org0.y));
double a1 = dst1.x - org1.x;
double b1 = dst1.y - org1.y;
double c1 = -0.5*(a1 * (dst1.x + org1.x) + b1 * (dst1.y + org1.y));
double det = a0 * b1 - a1 * b0;
if( det != 0 )
{
det = 1. / det;
return Point2f((float) ((b0 * c1 - b1 * c0) * det),
(float) ((a1 * c0 - a0 * c1) * det));
}
return Point2f(FLT_MAX, FLT_MAX);
}
@@ -574,33 +574,33 @@ void Subdiv2D::calcVoronoi()
// check if it is already calculated
if( validGeometry )
return;
clearVoronoi();
int i, total = (int)qedges.size();
// loop through all quad-edges, except for the first 3 (#1, #2, #3 - 0 is reserved for "NULL" pointer)
for( i = 4; i < total; i++ )
{
QuadEdge& quadedge = qedges[i];
if( quadedge.isfree() )
continue;
int edge0 = (int)(i*4);
Point2f org0, dst0, org1, dst1;
if( !quadedge.pt[3] )
{
int edge1 = getEdge( edge0, NEXT_AROUND_LEFT );
int edge2 = getEdge( edge1, NEXT_AROUND_LEFT );
edgeOrg(edge0, &org0);
edgeDst(edge0, &dst0);
edgeOrg(edge1, &org1);
edgeDst(edge1, &dst1);
Point2f virt_point = computeVoronoiPoint(org0, dst0, org1, dst1);
if( fabs( virt_point.x ) < FLT_MAX * 0.5 &&
fabs( virt_point.y ) < FLT_MAX * 0.5 )
{
@@ -608,28 +608,28 @@ void Subdiv2D::calcVoronoi()
qedges[edge2 >> 2].pt[3 - (edge2 & 2)] = newPoint(virt_point, true);
}
}
if( !quadedge.pt[1] )
{
int edge1 = getEdge( edge0, NEXT_AROUND_RIGHT );
int edge2 = getEdge( edge1, NEXT_AROUND_RIGHT );
edgeOrg(edge0, &org0);
edgeDst(edge0, &dst0);
edgeOrg(edge1, &org1);
edgeDst(edge1, &dst1);
Point2f virt_point = computeVoronoiPoint(org0, dst0, org1, dst1);
if( fabs( virt_point.x ) < FLT_MAX * 0.5 &&
fabs( virt_point.y ) < FLT_MAX * 0.5 )
{
quadedge.pt[1] = qedges[edge1 >> 2].pt[1 + (edge1 & 2)] =
quadedge.pt[1] = qedges[edge1 >> 2].pt[1 + (edge1 & 2)] =
qedges[edge2 >> 2].pt[1 + (edge2 & 2)] = newPoint(virt_point, true);
}
}
}
validGeometry = true;
}
@@ -646,70 +646,70 @@ int Subdiv2D::findNearest(Point2f pt, Point2f* nearestPt)
{
if( !validGeometry )
calcVoronoi();
int vertex = 0, edge = 0;
int loc = locate( pt, edge, vertex );
if( loc != PTLOC_ON_EDGE && loc != PTLOC_INSIDE )
return vertex;
vertex = 0;
Point2f start;
edgeOrg(edge, &start);
Point2f diff = pt - start;
edge = rotateEdge(edge, 1);
int i, total = (int)vtx.size();
for( i = 0; i < total; i++ )
{
Point2f t;
for(;;)
{
CV_Assert( edgeDst(edge, &t) > 0 );
if( isRightOf2( t, start, diff ) >= 0 )
break;
edge = getEdge( edge, NEXT_AROUND_LEFT );
}
for(;;)
{
CV_Assert( edgeOrg( edge, &t ) > 0 );
if( isRightOf2( t, start, diff ) < 0 )
break;
edge = getEdge( edge, PREV_AROUND_LEFT );
}
Point2f tempDiff;
edgeDst(edge, &tempDiff);
edgeOrg(edge, &t);
tempDiff -= t;
if( isRightOf2( pt, t, tempDiff ) >= 0 )
{
vertex = edgeOrg(rotateEdge( edge, 3 ));
break;
}
edge = symEdge( edge );
}
if( nearestPt && vertex > 0 )
*nearestPt = vtx[vertex].pt;
return vertex;
}
void Subdiv2D::getEdgeList(vector<Vec4f>& edgeList) const
{
edgeList.clear();
for( size_t i = 4; i < qedges.size(); i++ )
{
if( qedges[i].isfree() )
@@ -728,7 +728,7 @@ void Subdiv2D::getTriangleList(vector<Vec6f>& triangleList) const
triangleList.clear();
int i, total = (int)(qedges.size()*4);
vector<bool> edgemask(total, false);
for( i = 4; i < total; i += 2 )
{
if( edgemask[i] )
@@ -754,23 +754,23 @@ void Subdiv2D::getVoronoiFacetList(const vector<int>& idx,
calcVoronoi();
facetList.clear();
facetCenters.clear();
vector<Point2f> buf;
size_t i, total;
if( idx.empty() )
i = 4, total = vtx.size();
else
i = 0, total = idx.size();
for( ; i < total; i++ )
{
int k = idx.empty() ? (int)i : idx[i];
if( vtx[k].isfree() || vtx[k].isvirtual() )
continue;
int edge = rotateEdge(vtx[k].firstEdge, 1), t = edge;
int edge = rotateEdge(vtx[k].firstEdge, 1), t = edge;
// gather points
buf.clear();
do
@@ -779,7 +779,7 @@ void Subdiv2D::getVoronoiFacetList(const vector<int>& idx,
t = getEdge( t, NEXT_AROUND_LEFT );
}
while( t != edge );
facetList.push_back(buf);
facetCenters.push_back(vtx[k].pt);
}
@@ -789,14 +789,14 @@ void Subdiv2D::getVoronoiFacetList(const vector<int>& idx,
void Subdiv2D::checkSubdiv() const
{
int i, j, total = (int)qedges.size();
for( i = 0; i < total; i++ )
{
const QuadEdge& qe = qedges[i];
if( qe.isfree() )
continue;
for( j = 0; j < 4; j++ )
{
int e = (int)(i*4 + j);
@@ -804,13 +804,13 @@ void Subdiv2D::checkSubdiv() const
int o_prev = getEdge(e, PREV_AROUND_ORG );
int d_prev = getEdge(e, PREV_AROUND_DST );
int d_next = getEdge(e, NEXT_AROUND_DST );
// check points
CV_Assert( edgeOrg(e) == edgeOrg(o_next));
CV_Assert( edgeOrg(e) == edgeOrg(o_prev));
CV_Assert( edgeDst(e) == edgeDst(d_next));
CV_Assert( edgeDst(e) == edgeDst(d_prev));
if( j % 2 == 0 )
{
CV_Assert( edgeDst(o_next) == edgeOrg(d_prev));
@@ -820,8 +820,8 @@ void Subdiv2D::checkSubdiv() const
}
}
}
}
}
}
/* End of file. */
modules/imgproc/src/tables.cpp
+1 -1
View File
@@ -158,7 +158,7 @@ const float icv8x32fSqrTab[] =
61504.f, 62001.f, 62500.f, 63001.f, 63504.f, 64009.f, 64516.f, 65025.f
};
const uchar icvSaturate8u_cv[] =
const uchar icvSaturate8u_cv[] =
{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
modules/imgproc/src/templmatch.cpp
+22 -22
View File
@@ -56,26 +56,26 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
int depth = img.depth(), cn = img.channels();
int tdepth = templ.depth(), tcn = templ.channels();
int cdepth = CV_MAT_DEPTH(ctype), ccn = CV_MAT_CN(ctype);
CV_Assert( img.dims <= 2 && templ.dims <= 2 && corr.dims <= 2 );
if( depth != tdepth && tdepth != std::max(CV_32F, depth) )
{
_templ.convertTo(templ, std::max(CV_32F, depth));
tdepth = templ.depth();
}
CV_Assert( depth == tdepth || tdepth == CV_32F);
CV_Assert( corrsize.height <= img.rows + templ.rows - 1 &&
corrsize.width <= img.cols + templ.cols - 1 );
CV_Assert( ccn == 1 || delta == 0 );
corr.create(corrsize, ctype);
int maxDepth = depth > CV_8S ? CV_64F : std::max(std::max(CV_32F, tdepth), cdepth);
Size blocksize, dftsize;
blocksize.width = cvRound(templ.cols*blockScale);
blocksize.width = std::max( blocksize.width, minBlockSize - templ.cols + 1 );
blocksize.width = std::min( blocksize.width, corr.cols );
@@ -109,7 +109,7 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
bufSize = std::max( bufSize, blocksize.width*blocksize.height*CV_ELEM_SIZE(cdepth));
buf.resize(bufSize);
// compute DFT of each template plane
for( k = 0; k < tcn; k++ )
{
@@ -139,11 +139,11 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
int tileCountX = (corr.cols + blocksize.width - 1)/blocksize.width;
int tileCountY = (corr.rows + blocksize.height - 1)/blocksize.height;
int tileCount = tileCountX * tileCountY;
Size wholeSize = img.size();
Point roiofs(0,0);
Mat img0 = img;
if( !(borderType & BORDER_ISOLATED) )
{
img.locateROI(wholeSize, roiofs);
@@ -151,13 +151,13 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
roiofs.x, wholeSize.width-img.cols-roiofs.x);
}
borderType |= BORDER_ISOLATED;
// calculate correlation by blocks
for( i = 0; i < tileCount; i++ )
{
int x = (i%tileCountX)*blocksize.width;
int y = (i/tileCountX)*blocksize.height;
Size bsz(std::min(blocksize.width, corr.cols - x),
std::min(blocksize.height, corr.rows - y));
Size dsz(bsz.width + templ.cols - 1, bsz.height + templ.rows - 1);
@@ -169,12 +169,12 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
Mat dst(dftImg, Rect(0, 0, dsz.width, dsz.height));
Mat dst1(dftImg, Rect(x1-x0, y1-y0, x2-x1, y2-y1));
Mat cdst(corr, Rect(x, y, bsz.width, bsz.height));
for( k = 0; k < cn; k++ )
{
Mat src = src0;
dftImg = Scalar::all(0);
if( cn > 1 )
{
src = depth == maxDepth ? dst1 : Mat(y2-y1, x2-x1, depth, &buf[0]);
@@ -206,7 +206,7 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
src = plane;
}
int pairs[] = {0, k};
mixChannels(&src, 1, &cdst, 1, pairs, 1);
mixChannels(&src, 1, &cdst, 1, pairs, 1);
}
else
{
@@ -234,7 +234,7 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method )
{
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
int numType = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
bool isNormed = method == CV_TM_CCORR_NORMED ||
@@ -244,14 +244,14 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
Mat img = _img.getMat(), templ = _templ.getMat();
if( img.rows < templ.rows || img.cols < templ.cols )
std::swap(img, templ);
CV_Assert( (img.depth() == CV_8U || img.depth() == CV_32F) &&
img.type() == templ.type() );
Size corrSize(img.cols - templ.cols + 1, img.rows - templ.rows + 1);
_result.create(corrSize, CV_32F);
Mat result = _result.getMat();
int cn = img.channels();
crossCorr( img, templ, result, result.size(), result.type(), Point(0,0), 0, 0);
@@ -264,7 +264,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
Scalar templMean, templSdv;
double *q0 = 0, *q1 = 0, *q2 = 0, *q3 = 0;
double templNorm = 0, templSum2 = 0;
if( method == CV_TM_CCOEFF )
{
integral(img, sum, CV_64F);
@@ -283,7 +283,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
result = Scalar::all(1);
return;
}
templSum2 = templNorm +
CV_SQR(templMean[0]) + CV_SQR(templMean[1]) +
CV_SQR(templMean[2]) + CV_SQR(templMean[3]);
@@ -293,7 +293,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
templMean = Scalar::all(0);
templNorm = templSum2;
}
templSum2 /= invArea;
templNorm = sqrt(templNorm);
templNorm /= sqrt(invArea); // care of accuracy here
@@ -313,7 +313,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
int sqstep = sqsum.data ? (int)(sqsum.step / sizeof(double)) : 0;
int i, j, k;
for( i = 0; i < result.rows; i++ )
{
float* rrow = (float*)(result.data + i*result.step);
@@ -324,7 +324,7 @@ void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result,
{
double num = rrow[j], t;
double wndMean2 = 0, wndSum2 = 0;
if( numType == 1 )
{
for( k = 0; k < cn; k++ )
modules/imgproc/src/thresh.cpp
+1 -1
View File
@@ -781,7 +781,7 @@ double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double m
;
else
CV_Error( CV_StsUnsupportedFormat, "" );
parallel_for_(Range(0, dst.rows),
ThresholdRunner(src, dst, thresh, maxval, type),
dst.total()/(double)(1<<16));
modules/imgproc/src/utils.cpp
+21 -21
View File
@@ -48,9 +48,9 @@ CV_IMPL CvSeq* cvPointSeqFromMat( int seq_kind, const CvArr* arr,
int eltype;
CvMat* mat = (CvMat*)arr;
if( !CV_IS_MAT( mat ))
CV_Error( CV_StsBadArg, "Input array is not a valid matrix" );
CV_Error( CV_StsBadArg, "Input array is not a valid matrix" );
eltype = CV_MAT_TYPE( mat->type );
if( eltype != CV_32SC2 && eltype != CV_32FC2 )
@@ -93,14 +93,14 @@ static void copyMakeBorder_8u( const uchar* src, size_t srcstep, Size srcroi,
int* tab = _tab;
int right = dstroi.width - srcroi.width - left;
int bottom = dstroi.height - srcroi.height - top;
for( i = 0; i < left; i++ )
{
j = borderInterpolate(i - left, srcroi.width, borderType)*cn;
for( k = 0; k < cn; k++ )
tab[i*cn + k] = j + k;
}
for( i = 0; i < right; i++ )
{
j = borderInterpolate(srcroi.width + i, srcroi.width, borderType)*cn;
@@ -112,14 +112,14 @@ static void copyMakeBorder_8u( const uchar* src, size_t srcstep, Size srcroi,
dstroi.width *= cn;
left *= cn;
right *= cn;
uchar* dstInner = dst + dststep*top + left*elemSize;
for( i = 0; i < srcroi.height; i++, dstInner += dststep, src += srcstep )
{
if( dstInner != src )
memcpy(dstInner, src, srcroi.width*elemSize);
if( intMode )
{
const int* isrc = (int*)src;
@@ -137,16 +137,16 @@ static void copyMakeBorder_8u( const uchar* src, size_t srcstep, Size srcroi,
dstInner[j + srcroi.width] = src[tab[j + left]];
}
}
dstroi.width *= elemSize;
dst += dststep*top;
for( i = 0; i < top; i++ )
{
j = borderInterpolate(i - top, srcroi.height, borderType);
memcpy(dst + (i - top)*dststep, dst + j*dststep, dstroi.width);
}
for( i = 0; i < bottom; i++ )
{
j = borderInterpolate(i + srcroi.height, srcroi.height, borderType);
@@ -164,20 +164,20 @@ static void copyMakeConstBorder_8u( const uchar* src, size_t srcstep, Size srcro
uchar* constBuf = _constBuf;
int right = dstroi.width - srcroi.width - left;
int bottom = dstroi.height - srcroi.height - top;
for( i = 0; i < dstroi.width; i++ )
{
for( j = 0; j < cn; j++ )
constBuf[i*cn + j] = value[j];
}
srcroi.width *= cn;
dstroi.width *= cn;
left *= cn;
right *= cn;
uchar* dstInner = dst + dststep*top + left;
for( i = 0; i < srcroi.height; i++, dstInner += dststep, src += srcstep )
{
if( dstInner != src )
@@ -185,24 +185,24 @@ static void copyMakeConstBorder_8u( const uchar* src, size_t srcstep, Size srcro
memcpy( dstInner - left, constBuf, left );
memcpy( dstInner + srcroi.width, constBuf, right );
}
dst += dststep*top;
for( i = 0; i < top; i++ )
memcpy(dst + (i - top)*dststep, constBuf, dstroi.width);
for( i = 0; i < bottom; i++ )
memcpy(dst + (i + srcroi.height)*dststep, constBuf, dstroi.width);
}
}
void cv::copyMakeBorder( InputArray _src, OutputArray _dst, int top, int bottom,
int left, int right, int borderType, const Scalar& value )
{
Mat src = _src.getMat();
CV_Assert( top >= 0 && bottom >= 0 && left >= 0 && right >= 0 );
if( src.isSubmatrix() && (borderType & BORDER_ISOLATED) == 0 )
{
Size wholeSize;
@@ -228,9 +228,9 @@ void cv::copyMakeBorder( InputArray _src, OutputArray _dst, int top, int bottom,
src.copyTo(dst);
return;
}
borderType &= ~BORDER_ISOLATED;
if( borderType != BORDER_CONSTANT )
copyMakeBorder_8u( src.data, src.step, src.size(),
dst.data, dst.step, dst.size(),
@@ -268,7 +268,7 @@ cvCopyMakeBorder( const CvArr* srcarr, CvArr* dstarr, CvPoint offset,
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
int left = offset.x, right = dst.cols - src.cols - left;
int top = offset.y, bottom = dst.rows - src.rows - top;
CV_Assert( dst.type() == src.type() );
cv::copyMakeBorder( src, dst, top, bottom, left, right, borderType, value );
}
modules/imgproc/test/test_approxpoly.cpp
+19 -19
View File
@@ -49,7 +49,7 @@ using namespace std;
// TODO!!!:
// check_slice (and/or check) seem(s) to be broken, or this is a bug in function
// (or its inability to handle possible self-intersections in the generated contours).
//
//
// At least, if // return TotalErrors;
// is uncommented in check_slice, the test fails easily.
// So, now (and it looks like since 0.9.6)
@@ -177,7 +177,7 @@ int CV_ApproxPolyTest::check_slice( CvPoint StartPt, CvPoint EndPt,
double sin_a = 0;
double cos_a = 0;
double d = 0;
double dist;
double dist;
///////////
int j, TotalErrors = 0;
@@ -193,7 +193,7 @@ int CV_ApproxPolyTest::check_slice( CvPoint StartPt, CvPoint EndPt,
dx = (double)StartPt.x - (double)EndPt.x;
dy = (double)StartPt.y - (double)EndPt.y;
if( ( dx == 0 ) && ( dy == 0 ) ) flag = false;
else
{
@@ -270,7 +270,7 @@ int CV_ApproxPolyTest::check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps )
{
TotalErrors++;
return TotalErrors;
} //if( !flag )
} //if( !flag )
} // for( int i = 0 ; i < DstSeq->total ; i++ )
@@ -283,7 +283,7 @@ int CV_ApproxPolyTest::check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps )
void CV_ApproxPolyTest::run( int /*start_from*/ )
{
int code = cvtest::TS::OK;
CvMemStorage* storage = 0;
CvMemStorage* storage = 0;
////////////// Variables ////////////////
int IntervalsCount = 10;
///////////
@@ -296,42 +296,42 @@ void CV_ApproxPolyTest::run( int /*start_from*/ )
for( int i = 0; i < 30; i++ )
{
CvMemStoragePos pos;
ts->update_context( this, i, false );
///////////////////// init contour /////////
dDiam = 0;
while( sqrt(dDiam) / IntervalsCount == 0 )
{
if( storage != 0 )
cvReleaseMemStorage(&storage);
if( storage != 0 )
cvReleaseMemStorage(&storage);
storage = cvCreateMemStorage( 0 );
if( get_contour( 0, &SrcSeq, &iDiam, storage ) )
dDiam = (float)iDiam;
}
dDiam = (float)sqrt( dDiam );
storage = SrcSeq->storage;
////////////////// test /////////////
EpsStep = dDiam / IntervalsCount ;
for( Eps = EpsStep ; Eps < dDiam ; Eps += EpsStep )
{
cvSaveMemStoragePos( storage, &pos );
cvSaveMemStoragePos( storage, &pos );
////////// call function ////////////
DstSeq = cvApproxPoly( SrcSeq, SrcSeq->header_size, storage,
DstSeq = cvApproxPoly( SrcSeq, SrcSeq->header_size, storage,
CV_POLY_APPROX_DP, Eps );
if( DstSeq == NULL )
if( DstSeq == NULL )
{
ts->printf( cvtest::TS::LOG,
"cvApproxPoly returned NULL for contour #%d, espilon = %g\n", i, Eps );
code = cvtest::TS::FAIL_INVALID_OUTPUT;
goto _exit_;
} // if( DstSeq == NULL )
code = check( SrcSeq, DstSeq, Eps );
if( code != 0 )
{
@@ -340,10 +340,10 @@ void CV_ApproxPolyTest::run( int /*start_from*/ )
code = cvtest::TS::FAIL_BAD_ACCURACY;
goto _exit_;
}
cvRestoreMemStoragePos( storage, &pos );
} // for( Eps = EpsStep ; Eps <= Diam ; Eps += EpsStep )
///////////// free memory ///////////////////
cvReleaseMemStorage(&storage);
} // for( int i = 0; NULL != ( Cont = Contours[i] ) ; i++ )
modules/imgproc/test/test_bilateral_filter.cpp
+23 -23
View File
@@ -44,16 +44,16 @@
using namespace cv;
namespace cvtest
{
class CV_BilateralFilterTest :
namespace cvtest
{
class CV_BilateralFilterTest :
public cvtest::BaseTest
{
public:
enum
enum
{
MAX_WIDTH = 1920, MIN_WIDTH = 1,
MAX_HEIGHT = 1080, MIN_HEIGHT = 1
MAX_HEIGHT = 1080, MIN_HEIGHT = 1
};
CV_BilateralFilterTest();
@@ -63,22 +63,22 @@ namespace cvtest
virtual void run_func();
virtual int prepare_test_case(int test_case_index);
virtual int validate_test_results(int test_case_index);
private:
void reference_bilateral_filter(const Mat& src, Mat& dst, int d, double sigma_color,
double sigma_space, int borderType = BORDER_DEFAULT);
int getRandInt(RNG& rng, int min_value, int max_value) const;
double _sigma_color;
double _sigma_space;
Mat _src;
Mat _parallel_dst;
int _d;
};
CV_BilateralFilterTest::CV_BilateralFilterTest() :
CV_BilateralFilterTest::CV_BilateralFilterTest() :
cvtest::BaseTest(), _src(), _parallel_dst(), _d()
{
test_case_count = 1000;
@@ -94,7 +94,7 @@ namespace cvtest
return cvRound(exp((double)rand_value));
}
void CV_BilateralFilterTest::reference_bilateral_filter(const Mat &src, Mat &dst, int d,
void CV_BilateralFilterTest::reference_bilateral_filter(const Mat &src, Mat &dst, int d,
double sigma_color, double sigma_space, int borderType)
{
int cn = src.channels();
@@ -237,22 +237,22 @@ namespace cvtest
RNG& rng = ts->get_rng();
Size size(getRandInt(rng, MIN_WIDTH, MAX_WIDTH), getRandInt(rng, MIN_HEIGHT, MAX_HEIGHT));
int type = types[rng(sizeof(types) / sizeof(types[0]))];
_d = rng.uniform(0., 1.) > 0.5 ? 5 : 3;
_d = rng.uniform(0., 1.) > 0.5 ? 5 : 3;
_src.create(size, type);
rng.fill(_src, RNG::UNIFORM, 0, 256);
_sigma_color = _sigma_space = 1.;
return 1;
}
int CV_BilateralFilterTest::validate_test_results(int test_case_index)
{
static const double eps = 1;
Mat reference_dst, reference_src;
if (_src.depth() == CV_32F)
reference_bilateral_filter(_src, reference_dst, _d, _sigma_color, _sigma_space);
@@ -263,7 +263,7 @@ namespace cvtest
reference_bilateral_filter(reference_src, reference_dst, _d, _sigma_color, _sigma_space);
reference_dst.convertTo(reference_dst, type);
}
double e = norm(reference_dst, _parallel_dst);
if (e > eps)
{
@@ -272,7 +272,7 @@ namespace cvtest
}
else
ts->set_failed_test_info(cvtest::TS::OK);
return BaseTest::validate_test_results(test_case_index);
}
@@ -282,9 +282,9 @@ namespace cvtest
}
TEST(Imgproc_BilateralFilter, accuracy)
{
CV_BilateralFilterTest test;
test.safe_run();
{
CV_BilateralFilterTest test;
test.safe_run();
}
} // end of namespace cvtest
modules/imgproc/test/test_boundingrect.cpp
+144 -144
View File
@@ -1,144 +1,144 @@
/*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) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// 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 <time.h>
#define IMGPROC_BOUNDINGRECT_ERROR_DIFF 1
#define MESSAGE_ERROR_DIFF "Bounding rectangle found by boundingRect function is incorrect."
using namespace cv;
using namespace std;
class CV_BoundingRectTest: public cvtest::ArrayTest
{
public:
CV_BoundingRectTest();
~CV_BoundingRectTest();
protected:
void run (int);
private:
template <typename T> void generate_src_points(vector <Point_<T> >& src, int n);
template <typename T> cv::Rect get_bounding_rect(const vector <Point_<T> > src);
template <typename T> bool checking_function_work(vector <Point_<T> >& src, int type);
};
CV_BoundingRectTest::CV_BoundingRectTest() {}
CV_BoundingRectTest::~CV_BoundingRectTest() {}
template <typename T> void CV_BoundingRectTest::generate_src_points(vector <Point_<T> >& src, int n)
{
src.clear();
for (int i = 0; i < n; ++i)
src.push_back(Point_<T>(cv::randu<T>(), cv::randu<T>()));
}
template <typename T> cv::Rect CV_BoundingRectTest::get_bounding_rect(const vector <Point_<T> > src)
{
int n = (int)src.size();
T min_w = std::numeric_limits<T>::max(), max_w = std::numeric_limits<T>::min();
T min_h = min_w, max_h = max_w;
for (int i = 0; i < n; ++i)
{
min_w = std::min<T>(src.at(i).x, min_w);
max_w = std::max<T>(src.at(i).x, max_w);
min_h = std::min<T>(src.at(i).y, min_h);
max_h = std::max<T>(src.at(i).y, max_h);
}
return Rect((int)min_w, (int)min_h, (int)max_w-(int)min_w + 1, (int)max_h-(int)min_h + 1);
}
template <typename T> bool CV_BoundingRectTest::checking_function_work(vector <Point_<T> >& src, int type)
{
const int MAX_COUNT_OF_POINTS = 1000;
const int N = 10000;
for (int k = 0; k < N; ++k)
{
RNG& rng = ts->get_rng();
int n = rng.next()%MAX_COUNT_OF_POINTS + 1;
generate_src_points <T> (src, n);
cv::Rect right = get_bounding_rect <T> (src);
cv::Rect rect[2] = { boundingRect(src), boundingRect(Mat(src)) };
for (int i = 0; i < 2; ++i) if (rect[i] != right)
{
cout << endl; cout << "Checking for the work of boundingRect function..." << endl;
cout << "Type of src points: ";
switch (type)
{
case 0: {cout << "INT"; break;}
case 1: {cout << "FLOAT"; break;}
default: break;
}
cout << endl;
cout << "Src points are stored as "; if (i == 0) cout << "VECTOR" << endl; else cout << "MAT" << endl;
cout << "Number of points: " << n << endl;
cout << "Right rect (x, y, w, h): [" << right.x << ", " << right.y << ", " << right.width << ", " << right.height << "]" << endl;
cout << "Result rect (x, y, w, h): [" << rect[i].x << ", " << rect[i].y << ", " << rect[i].width << ", " << rect[i].height << "]" << endl;
cout << endl;
CV_Error(IMGPROC_BOUNDINGRECT_ERROR_DIFF, MESSAGE_ERROR_DIFF);
return false;
}
}
return true;
}
void CV_BoundingRectTest::run(int)
{
vector <Point> src_veci; if (!checking_function_work(src_veci, 0)) return;
vector <Point2f> src_vecf; checking_function_work(src_vecf, 1);
}
TEST (Imgproc_BoundingRect, accuracy) { CV_BoundingRectTest test; test.safe_run(); }
/*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) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// 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 <time.h>
#define IMGPROC_BOUNDINGRECT_ERROR_DIFF 1
#define MESSAGE_ERROR_DIFF "Bounding rectangle found by boundingRect function is incorrect."
using namespace cv;
using namespace std;
class CV_BoundingRectTest: public cvtest::ArrayTest
{
public:
CV_BoundingRectTest();
~CV_BoundingRectTest();
protected:
void run (int);
private:
template <typename T> void generate_src_points(vector <Point_<T> >& src, int n);
template <typename T> cv::Rect get_bounding_rect(const vector <Point_<T> > src);
template <typename T> bool checking_function_work(vector <Point_<T> >& src, int type);
};
CV_BoundingRectTest::CV_BoundingRectTest() {}
CV_BoundingRectTest::~CV_BoundingRectTest() {}
template <typename T> void CV_BoundingRectTest::generate_src_points(vector <Point_<T> >& src, int n)
{
src.clear();
for (int i = 0; i < n; ++i)
src.push_back(Point_<T>(cv::randu<T>(), cv::randu<T>()));
}
template <typename T> cv::Rect CV_BoundingRectTest::get_bounding_rect(const vector <Point_<T> > src)
{
int n = (int)src.size();
T min_w = std::numeric_limits<T>::max(), max_w = std::numeric_limits<T>::min();
T min_h = min_w, max_h = max_w;
for (int i = 0; i < n; ++i)
{
min_w = std::min<T>(src.at(i).x, min_w);
max_w = std::max<T>(src.at(i).x, max_w);
min_h = std::min<T>(src.at(i).y, min_h);
max_h = std::max<T>(src.at(i).y, max_h);
}
return Rect((int)min_w, (int)min_h, (int)max_w-(int)min_w + 1, (int)max_h-(int)min_h + 1);
}
template <typename T> bool CV_BoundingRectTest::checking_function_work(vector <Point_<T> >& src, int type)
{
const int MAX_COUNT_OF_POINTS = 1000;
const int N = 10000;
for (int k = 0; k < N; ++k)
{
RNG& rng = ts->get_rng();
int n = rng.next()%MAX_COUNT_OF_POINTS + 1;
generate_src_points <T> (src, n);
cv::Rect right = get_bounding_rect <T> (src);
cv::Rect rect[2] = { boundingRect(src), boundingRect(Mat(src)) };
for (int i = 0; i < 2; ++i) if (rect[i] != right)
{
cout << endl; cout << "Checking for the work of boundingRect function..." << endl;
cout << "Type of src points: ";
switch (type)
{
case 0: {cout << "INT"; break;}
case 1: {cout << "FLOAT"; break;}
default: break;
}
cout << endl;
cout << "Src points are stored as "; if (i == 0) cout << "VECTOR" << endl; else cout << "MAT" << endl;
cout << "Number of points: " << n << endl;
cout << "Right rect (x, y, w, h): [" << right.x << ", " << right.y << ", " << right.width << ", " << right.height << "]" << endl;
cout << "Result rect (x, y, w, h): [" << rect[i].x << ", " << rect[i].y << ", " << rect[i].width << ", " << rect[i].height << "]" << endl;
cout << endl;
CV_Error(IMGPROC_BOUNDINGRECT_ERROR_DIFF, MESSAGE_ERROR_DIFF);
return false;
}
}
return true;
}
void CV_BoundingRectTest::run(int)
{
vector <Point> src_veci; if (!checking_function_work(src_veci, 0)) return;
vector <Point2f> src_vecf; checking_function_work(src_vecf, 1);
}
TEST (Imgproc_BoundingRect, accuracy) { CV_BoundingRectTest test; test.safe_run(); }
modules/imgproc/test/test_canny.cpp
+6 -6
View File
@@ -193,13 +193,13 @@ test_Canny( const Mat& src, Mat& dst,
{
for( x = 0; x < width; x++ )
{
float a = mag.at<float>(y, x), b = 0, c = 0;
int y1 = 0, y2 = 0, x1 = 0, x2 = 0;
if( a <= lowThreshold )
continue;
int dxval = dx.at<short>(y, x);
int dyval = dy.at<short>(y, x);
@@ -259,18 +259,18 @@ int CV_CannyTest::validate_test_results( int test_case_idx )
{
int code = cvtest::TS::OK, nz0;
prepare_to_validation(test_case_idx);
double err = cvtest::norm(test_mat[OUTPUT][0], test_mat[REF_OUTPUT][0], CV_L1);
if( err == 0 )
return code;
if( err != cvRound(err) || cvRound(err)%255 != 0 )
{
ts->printf( cvtest::TS::LOG, "Some of the pixels, produced by Canny, are not 0's or 255's; the difference is %g\n", err );
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
return code;
}
nz0 = cvRound(cvtest::norm(test_mat[REF_OUTPUT][0], CV_L1)/255);
err = (err/255/MAX(nz0,100))*100;
if( err > 1 )
@@ -278,7 +278,7 @@ int CV_CannyTest::validate_test_results( int test_case_idx )
ts->printf( cvtest::TS::LOG, "Too high percentage of non-matching edge pixels = %g%%\n", err);
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
}
return code;
}
modules/imgproc/test/test_color.cpp
+42 -42
View File
@@ -159,12 +159,12 @@ void CV_ColorCvtBaseTest::run_func()
{
CvArr* out0 = test_array[OUTPUT][0];
cv::Mat _out0 = cv::cvarrToMat(out0), _out1 = cv::cvarrToMat(test_array[OUTPUT][1]);
if(!test_cpp)
cvCvtColor( inplace ? out0 : test_array[INPUT][0], out0, fwd_code );
else
cv::cvtColor( cv::cvarrToMat(inplace ? out0 : test_array[INPUT][0]), _out0, fwd_code, _out0.channels());
if( inplace )
{
cvCopy( out0, test_array[OUTPUT][1] );
@@ -189,7 +189,7 @@ void CV_ColorCvtBaseTest::prepare_to_validation( int /*test_case_idx*/ )
{
uchar* h0 = test_mat[REF_OUTPUT][0].ptr(y);
uchar* h = test_mat[OUTPUT][0].ptr(y);
for( int x = 0; x < test_mat[REF_OUTPUT][0].cols; x++, h0 += 3, h += 3 )
{
if( abs(*h - *h0) >= hue_range-1 && (*h <= 1 || *h0 <= 1) )
@@ -1018,16 +1018,16 @@ void CV_ColorLabTest::convert_row_bgr2abc_32f_c3(const float* src_row, float* ds
float Lscale = depth == CV_8U ? 255.f/100.f : depth == CV_16U ? 65535.f/100.f : 1.f;
float ab_bias = depth == CV_8U ? 128.f : depth == CV_16U ? 32768.f : 0.f;
float M[9];
for (int j = 0; j < 9; j++ )
M[j] = (float)RGB2XYZ[j];
for (int x = 0; x < n*3; x += 3)
{
float R = src_row[x + 2];
float G = src_row[x + 1];
float B = src_row[x];
float X = (R * M[0] + G * M[1] + B * M[2]) / Xn;
float Y = R * M[3] + G * M[4] + B * M[5];
float Z = (R * M[6] + G * M[7] + B * M[8]) / Zn;
@@ -1035,7 +1035,7 @@ void CV_ColorLabTest::convert_row_bgr2abc_32f_c3(const float* src_row, float* ds
(7.787f * X + 16.f / 116.f);
float fZ = Z > 0.008856f ? pow(Z, _1_3f):
(7.787f * Z + 16.f / 116.f);
float L = 0.0f, fY = 0.0f;
if (Y > 0.008856f)
{
@@ -1047,10 +1047,10 @@ void CV_ColorLabTest::convert_row_bgr2abc_32f_c3(const float* src_row, float* ds
fY = 7.787f * Y + 16.f / 116.f;
L = 903.3f * Y;
}
float a = 500.f * (fX - fY);
float b = 200.f * (fY - fZ);
dst_row[x] = L * Lscale;
dst_row[x + 1] = a + ab_bias;
dst_row[x + 2] = b + ab_bias;
@@ -1063,10 +1063,10 @@ void CV_ColorLabTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* d
float Lscale = depth == CV_8U ? 100.f/255.f : depth == CV_16U ? 100.f/65535.f : 1.f;
float ab_bias = depth == CV_8U ? 128.f : depth == CV_16U ? 32768.f : 0.f;
float M[9];
for(int j = 0; j < 9; j++ )
M[j] = (float)XYZ2RGB[j];
static const float lthresh = 903.3f * 0.008856f;
static const float thresh = 7.787f * 0.008856f + 16.0f / 116.0f;
for (int x = 0, end = n * 3; x < end; x += 3)
@@ -1074,7 +1074,7 @@ void CV_ColorLabTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* d
float L = src_row[x] * Lscale;
float a = src_row[x + 1] - ab_bias;
float b = src_row[x + 2] - ab_bias;
float FY = 0.0f, Y = 0.0f;
if (L <= lthresh)
{
@@ -1086,10 +1086,10 @@ void CV_ColorLabTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* d
FY = (L + 16.0f) / 116.0f;
Y = FY * FY * FY;
}
float FX = a / 500.0f + FY;
float FZ = FY - b / 200.0f;
float FXZ[] = { FX, FZ };
for (int k = 0; k < 2; ++k)
{
@@ -1100,11 +1100,11 @@ void CV_ColorLabTest::convert_row_abc2bgr_32f_c3( const float* src_row, float* d
}
float X = FXZ[0] * Xn;
float Z = FXZ[1] * Zn;
float R = M[0] * X + M[1] * Y + M[2] * Z;
float G = M[3] * X + M[4] * Y + M[5] * Z;
float B = M[6] * X + M[7] * Y + M[8] * Z;
dst_row[x] = B;
dst_row[x + 1] = G;
dst_row[x + 2] = R;
@@ -1589,10 +1589,10 @@ static void bayer2BGR_(const Mat& src, Mat& dst, int code)
int i, j, cols = src.cols - 2;
int bi = 0;
int step = (int)(src.step/sizeof(T));
if( code == CV_BayerRG2BGR || code == CV_BayerGR2BGR )
bi ^= 2;
for( i = 1; i < src.rows - 1; i++ )
{
const T* ptr = src.ptr<T>(i) + 1;
@@ -1604,7 +1604,7 @@ static void bayer2BGR_(const Mat& src, Mat& dst, int code)
dst_row[cols*3] = dst_row[cols*3+1] = dst_row[cols*3+2] = 0;
continue;
}
for( j = 0; j < cols; j++ )
{
int b, g, r;
@@ -1625,18 +1625,18 @@ static void bayer2BGR_(const Mat& src, Mat& dst, int code)
dst_row[j*3 + 1] = (T)g;
dst_row[j*3 + (bi^2)] = (T)r;
}
dst_row[-3] = dst_row[0];
dst_row[-2] = dst_row[1];
dst_row[-1] = dst_row[2];
dst_row[cols*3] = dst_row[cols*3-3];
dst_row[cols*3+1] = dst_row[cols*3-2];
dst_row[cols*3+2] = dst_row[cols*3-1];
code = save_code ^ 1;
bi ^= 2;
}
if( src.rows <= 2 )
{
memset( dst.ptr(), 0, (cols+2)*3*sizeof(T) );
@@ -1647,7 +1647,7 @@ static void bayer2BGR_(const Mat& src, Mat& dst, int code)
T* top_row = dst.ptr<T>();
T* bottom_row = dst.ptr<T>(dst.rows-1);
int dstep = (int)(dst.step/sizeof(T));
for( j = 0; j < (cols+2)*3; j++ )
{
top_row[j] = top_row[j + dstep];
@@ -1708,14 +1708,14 @@ TEST(Imgproc_ColorBayerVNG, regression)
cvtest::TS& ts = *cvtest::TS::ptr();
Mat given = imread(string(ts.get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
string goldfname = string(ts.get_data_path()) + "/cvtcolor/bayerVNG_gold.png";
string goldfname = string(ts.get_data_path()) + "/cvtcolor/bayerVNG_gold.png";
Mat gold = imread(goldfname, CV_LOAD_IMAGE_UNCHANGED);
Mat result;
CV_Assert(given.data != NULL);
cvtColor(given, result, CV_BayerBG2BGR_VNG, 3);
if (gold.empty())
imwrite(goldfname, result);
else
@@ -1750,7 +1750,7 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
ts.set_gtest_status();
return;
}
int type = -1;
for (int i = 0; i < 4; ++i)
{
@@ -1816,7 +1816,7 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
// calculating a dst image
cvtColor(bayer, dst, type);
// reading a reference image
full_path = parent_path + pattern[i] + image_name;
reference = imread(full_path, CV_LOAD_IMAGE_UNCHANGED);
@@ -1825,7 +1825,7 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
imwrite(full_path, dst);
continue;
}
if (reference.depth() != dst.depth() || reference.channels() != dst.channels() ||
reference.size() != dst.size())
{
@@ -1839,13 +1839,13 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
ts.printf(cvtest::TS::SUMMARY, "\nReference cols: %d\n"
"Actual cols: %d\n", reference.cols, dst.cols);
ts.set_gtest_status();
return;
}
Mat diff;
absdiff(reference, dst, diff);
int nonZero = countNonZero(diff.reshape(1) > 1);
if (nonZero != 0)
{
@@ -1872,7 +1872,7 @@ void GetTestMatrix(Mat& src)
float b = (1 + cos((szm - i) * (szm - j) * pi2 / (10 * float(szm)))) / 2;
float g = (1 + cos((szm - i) * j * pi2 / (10 * float(szm)))) / 2;
float r = (1 + sin(i * j * pi2 / (10 * float(szm)))) / 2;
// The following lines aren't necessary, but just to prove that
// the BGR values all lie in [0,1]...
if (b < 0) b = 0; else if (b > 1) b = 1;
@@ -1887,11 +1887,11 @@ void validate_result(const Mat& reference, const Mat& actual, const Mat& src = M
{
cvtest::TS* ts = cvtest::TS::ptr();
Size ssize = reference.size();
int cn = reference.channels();
ssize.width *= cn;
bool next = true;
for (int y = 0; y < ssize.height && next; ++y)
{
const float* rD = reference.ptr<float>(y);
@@ -1906,7 +1906,7 @@ void validate_result(const Mat& reference, const Mat& actual, const Mat& src = M
if (!src.empty())
ts->printf(cvtest::TS::SUMMARY, "Src value: %f\n", src.ptr<float>(y)[x]);
ts->printf(cvtest::TS::SUMMARY, "Size: (%d, %d)\n", reference.rows, reference.cols);
if (mode >= 0)
{
cv::Mat lab;
@@ -1914,7 +1914,7 @@ void validate_result(const Mat& reference, const Mat& actual, const Mat& src = M
std::cout << "lab: " << lab(cv::Rect(y, x / cn, 1, 1)) << std::endl;
}
std::cout << "src: " << src(cv::Rect(y, x / cn, 1, 1)) << std::endl;
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->set_gtest_status();
}
@@ -1928,11 +1928,11 @@ TEST(Imgproc_ColorLab_Full, accuracy)
Mat reference(src.size(), CV_32FC3);
Size ssize = src.size();
CV_Assert(ssize.width == ssize.height);
RNG& rng = cvtest::TS::ptr()->get_rng();
int blueInd = rng.uniform(0., 1.) > 0.5 ? 0 : 2;
bool srgb = rng.uniform(0., 1.) > 0.5;
// Convert test image to LAB
cv::Mat lab;
int forward_code = blueInd ? srgb ? CV_BGR2Lab : CV_LBGR2Lab : srgb ? CV_RGB2Lab : CV_LRGB2Lab;
@@ -1941,12 +1941,12 @@ TEST(Imgproc_ColorLab_Full, accuracy)
// Convert LAB image back to BGR(RGB)
cv::Mat recons;
cv::cvtColor(lab, recons, inverse_code);
validate_result(src, recons, src, forward_code);
// src *= 255.0f;
// recons *= 255.0f;
// imshow("Test", src);
// imshow("OpenCV", recons);
// waitKey();
modules/imgproc/test/test_cvtyuv.cpp
+484 -484
View File
@@ -1,484 +1,484 @@
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
#undef RGB
#undef YUV
typedef Vec3b YUV;
typedef Vec3b RGB;
int countOfDifferencies(const Mat& gold, const Mat& result, int maxAllowedDifference = 1)
{
Mat diff;
absdiff(gold, result, diff);
return countNonZero(diff.reshape(1) > maxAllowedDifference);
}
class YUVreader
{
public:
virtual ~YUVreader() {}
virtual YUV read(const Mat& yuv, int row, int col) = 0;
virtual int channels() = 0;
virtual Size size(Size imgSize) = 0;
virtual bool requiresEvenHeight() { return true; }
virtual bool requiresEvenWidth() { return true; }
static YUVreader* getReader(int code);
};
class RGBwriter
{
public:
virtual ~RGBwriter() {}
virtual void write(Mat& rgb, int row, int col, const RGB& val) = 0;
virtual int channels() = 0;
static RGBwriter* getWriter(int code);
};
class GRAYwriter
{
public:
virtual ~GRAYwriter() {}
virtual void write(Mat& gray, int row, int col, const uchar& val)
{
gray.at<uchar>(row, col) = val;
}
virtual int channels() { return 1; }
static GRAYwriter* getWriter(int code);
};
class RGB888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
rgb.at<Vec3b>(row, col) = val;
}
int channels() { return 3; }
};
class BGR888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec3b tmp(val[2], val[1], val[0]);
rgb.at<Vec3b>(row, col) = tmp;
}
int channels() { return 3; }
};
class RGBA8888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec4b tmp(val[0], val[1], val[2], 255);
rgb.at<Vec4b>(row, col) = tmp;
}
int channels() { return 4; }
};
class BGRA8888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec4b tmp(val[2], val[1], val[0], 255);
rgb.at<Vec4b>(row, col) = tmp;
}
int channels() { return 4; }
};
class YUV420Reader: public YUVreader
{
int channels() { return 1; }
Size size(Size imgSize) { return Size(imgSize.width, imgSize.height * 3 / 2); }
};
class YUV422Reader: public YUVreader
{
int channels() { return 2; }
Size size(Size imgSize) { return imgSize; }
bool requiresEvenHeight() { return false; }
};
class NV21Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2 + 1];
uchar v = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2];
return YUV(y, u, v);
}
};
struct NV12Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2];
uchar v = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2 + 1];
return YUV(y, u, v);
}
};
class YV12Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
int h = yuv.rows * 2 / 3;
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(h + (row/2 + h/2)/2)[col/2 + ((row/2 + h/2) % 2) * (yuv.cols/2)];
uchar v = yuv.ptr<uchar>(h + row/4)[col/2 + ((row/2) % 2) * (yuv.cols/2)];
return YUV(y, u, v);
}
};
class IYUVReader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
int h = yuv.rows * 2 / 3;
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(h + row/4)[col/2 + ((row/2) % 2) * (yuv.cols/2)];
uchar v = yuv.ptr<uchar>(h + (row/2 + h/2)/2)[col/2 + ((row/2 + h/2) % 2) * (yuv.cols/2)];
return YUV(y, u, v);
}
};
class UYVYReader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][1];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2][0];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][0];
return YUV(y, u, v);
}
};
class YUY2Reader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][0];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2][1];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][1];
return YUV(y, u, v);
}
};
class YVYUReader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][0];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][1];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2][1];
return YUV(y, u, v);
}
};
class YUV888Reader : public YUVreader
{
YUV read(const Mat& yuv, int row, int col)
{
return yuv.at<YUV>(row, col);
}
int channels() { return 3; }
Size size(Size imgSize) { return imgSize; }
bool requiresEvenHeight() { return false; }
bool requiresEvenWidth() { return false; }
};
class YUV2RGB_Converter
{
public:
RGB convert(YUV yuv)
{
int y = std::max(0, yuv[0] - 16);
int u = yuv[1] - 128;
int v = yuv[2] - 128;
uchar r = saturate_cast<uchar>(1.164f * y + 1.596f * v);
uchar g = saturate_cast<uchar>(1.164f * y - 0.813f * v - 0.391f * u);
uchar b = saturate_cast<uchar>(1.164f * y + 2.018f * u);
return RGB(r, g, b);
}
};
class YUV2GRAY_Converter
{
public:
uchar convert(YUV yuv)
{
return yuv[0];
}
};
YUVreader* YUVreader::getReader(int code)
{
switch(code)
{
case CV_YUV2RGB_NV12:
case CV_YUV2BGR_NV12:
case CV_YUV2RGBA_NV12:
case CV_YUV2BGRA_NV12:
return new NV12Reader();
case CV_YUV2RGB_NV21:
case CV_YUV2BGR_NV21:
case CV_YUV2RGBA_NV21:
case CV_YUV2BGRA_NV21:
return new NV21Reader();
case CV_YUV2RGB_YV12:
case CV_YUV2BGR_YV12:
case CV_YUV2RGBA_YV12:
case CV_YUV2BGRA_YV12:
return new YV12Reader();
case CV_YUV2RGB_IYUV:
case CV_YUV2BGR_IYUV:
case CV_YUV2RGBA_IYUV:
case CV_YUV2BGRA_IYUV:
return new IYUVReader();
case CV_YUV2RGB_UYVY:
case CV_YUV2BGR_UYVY:
case CV_YUV2RGBA_UYVY:
case CV_YUV2BGRA_UYVY:
return new UYVYReader();
//case CV_YUV2RGB_VYUY = 109,
//case CV_YUV2BGR_VYUY = 110,
//case CV_YUV2RGBA_VYUY = 113,
//case CV_YUV2BGRA_VYUY = 114,
// return ??
case CV_YUV2RGB_YUY2:
case CV_YUV2BGR_YUY2:
case CV_YUV2RGBA_YUY2:
case CV_YUV2BGRA_YUY2:
return new YUY2Reader();
case CV_YUV2RGB_YVYU:
case CV_YUV2BGR_YVYU:
case CV_YUV2RGBA_YVYU:
case CV_YUV2BGRA_YVYU:
return new YVYUReader();
case CV_YUV2GRAY_420:
return new NV21Reader();
case CV_YUV2GRAY_UYVY:
return new UYVYReader();
case CV_YUV2GRAY_YUY2:
return new YUY2Reader();
case CV_YUV2BGR:
case CV_YUV2RGB:
return new YUV888Reader();
default:
return 0;
}
}
RGBwriter* RGBwriter::getWriter(int code)
{
switch(code)
{
case CV_YUV2RGB_NV12:
case CV_YUV2RGB_NV21:
case CV_YUV2RGB_YV12:
case CV_YUV2RGB_IYUV:
case CV_YUV2RGB_UYVY:
//case CV_YUV2RGB_VYUY:
case CV_YUV2RGB_YUY2:
case CV_YUV2RGB_YVYU:
case CV_YUV2RGB:
return new RGB888Writer();
case CV_YUV2BGR_NV12:
case CV_YUV2BGR_NV21:
case CV_YUV2BGR_YV12:
case CV_YUV2BGR_IYUV:
case CV_YUV2BGR_UYVY:
//case CV_YUV2BGR_VYUY:
case CV_YUV2BGR_YUY2:
case CV_YUV2BGR_YVYU:
case CV_YUV2BGR:
return new BGR888Writer();
case CV_YUV2RGBA_NV12:
case CV_YUV2RGBA_NV21:
case CV_YUV2RGBA_YV12:
case CV_YUV2RGBA_IYUV:
case CV_YUV2RGBA_UYVY:
//case CV_YUV2RGBA_VYUY:
case CV_YUV2RGBA_YUY2:
case CV_YUV2RGBA_YVYU:
return new RGBA8888Writer();
case CV_YUV2BGRA_NV12:
case CV_YUV2BGRA_NV21:
case CV_YUV2BGRA_YV12:
case CV_YUV2BGRA_IYUV:
case CV_YUV2BGRA_UYVY:
//case CV_YUV2BGRA_VYUY:
case CV_YUV2BGRA_YUY2:
case CV_YUV2BGRA_YVYU:
return new BGRA8888Writer();
default:
return 0;
};
}
GRAYwriter* GRAYwriter::getWriter(int code)
{
switch(code)
{
case CV_YUV2GRAY_420:
case CV_YUV2GRAY_UYVY:
case CV_YUV2GRAY_YUY2:
return new GRAYwriter();
default:
return 0;
}
}
template<class convertor>
void referenceYUV2RGB(const Mat& yuv, Mat& rgb, YUVreader* yuvReader, RGBwriter* rgbWriter)
{
convertor cvt;
for(int row = 0; row < rgb.rows; ++row)
for(int col = 0; col < rgb.cols; ++col)
rgbWriter->write(rgb, row, col, cvt.convert(yuvReader->read(yuv, row, col)));
}
template<class convertor>
void referenceYUV2GRAY(const Mat& yuv, Mat& rgb, YUVreader* yuvReader, GRAYwriter* grayWriter)
{
convertor cvt;
for(int row = 0; row < rgb.rows; ++row)
for(int col = 0; col < rgb.cols; ++col)
grayWriter->write(rgb, row, col, cvt.convert(yuvReader->read(yuv, row, col)));
}
CV_ENUM(YUVCVTS, CV_YUV2RGB_NV12, CV_YUV2BGR_NV12, CV_YUV2RGB_NV21, CV_YUV2BGR_NV21,
CV_YUV2RGBA_NV12, CV_YUV2BGRA_NV12, CV_YUV2RGBA_NV21, CV_YUV2BGRA_NV21,
CV_YUV2RGB_YV12, CV_YUV2BGR_YV12, CV_YUV2RGB_IYUV, CV_YUV2BGR_IYUV,
CV_YUV2RGBA_YV12, CV_YUV2BGRA_YV12, CV_YUV2RGBA_IYUV, CV_YUV2BGRA_IYUV,
CV_YUV2RGB_UYVY, CV_YUV2BGR_UYVY, CV_YUV2RGBA_UYVY, CV_YUV2BGRA_UYVY,
CV_YUV2RGB_YUY2, CV_YUV2BGR_YUY2, CV_YUV2RGB_YVYU, CV_YUV2BGR_YVYU,
CV_YUV2RGBA_YUY2, CV_YUV2BGRA_YUY2, CV_YUV2RGBA_YVYU, CV_YUV2BGRA_YVYU,
CV_YUV2GRAY_420, CV_YUV2GRAY_UYVY, CV_YUV2GRAY_YUY2,
CV_YUV2BGR, CV_YUV2RGB);
typedef ::testing::TestWithParam<YUVCVTS> Imgproc_ColorYUV;
TEST_P(Imgproc_ColorYUV, accuracy)
{
int code = GetParam();
RNG& random = theRNG();
YUVreader* yuvReader = YUVreader::getReader(code);
RGBwriter* rgbWriter = RGBwriter::getWriter(code);
GRAYwriter* grayWriter = GRAYwriter::getWriter(code);
int dcn = (rgbWriter == 0) ? grayWriter->channels() : rgbWriter->channels();
for(int iter = 0; iter < 30; ++iter)
{
Size sz(random.uniform(1, 641), random.uniform(1, 481));
if(yuvReader->requiresEvenWidth()) sz.width += sz.width % 2;
if(yuvReader->requiresEvenHeight()) sz.height += sz.height % 2;
Size ysz = yuvReader->size(sz);
Mat src = Mat(ysz.height, ysz.width * yuvReader->channels(), CV_8UC1).reshape(yuvReader->channels());
Mat dst = Mat(sz.height, sz.width * dcn, CV_8UC1).reshape(dcn);
Mat gold(sz, CV_8UC(dcn));
random.fill(src, RNG::UNIFORM, 0, 256);
if(rgbWriter)
referenceYUV2RGB<YUV2RGB_Converter>(src, gold, yuvReader, rgbWriter);
else
referenceYUV2GRAY<YUV2GRAY_Converter>(src, gold, yuvReader, grayWriter);
cv::cvtColor(src, dst, code, -1);
EXPECT_EQ(0, countOfDifferencies(gold, dst));
}
}
TEST_P(Imgproc_ColorYUV, roi_accuracy)
{
int code = GetParam();
RNG& random = theRNG();
YUVreader* yuvReader = YUVreader::getReader(code);
RGBwriter* rgbWriter = RGBwriter::getWriter(code);
GRAYwriter* grayWriter = GRAYwriter::getWriter(code);
int dcn = (rgbWriter == 0) ? grayWriter->channels() : rgbWriter->channels();
for(int iter = 0; iter < 30; ++iter)
{
Size sz(random.uniform(1, 641), random.uniform(1, 481));
if(yuvReader->requiresEvenWidth()) sz.width += sz.width % 2;
if(yuvReader->requiresEvenHeight()) sz.height += sz.height % 2;
int roi_offset_top = random.uniform(0, 6);
int roi_offset_bottom = random.uniform(0, 6);
int roi_offset_left = random.uniform(0, 6);
int roi_offset_right = random.uniform(0, 6);
Size ysz = yuvReader->size(sz);
Mat src_full(ysz.height + roi_offset_top + roi_offset_bottom, ysz.width + roi_offset_left + roi_offset_right, CV_8UC(yuvReader->channels()));
Mat dst_full(sz.height + roi_offset_left + roi_offset_right, sz.width + roi_offset_top + roi_offset_bottom, CV_8UC(dcn), Scalar::all(0));
Mat gold_full(dst_full.size(), CV_8UC(dcn), Scalar::all(0));
random.fill(src_full, RNG::UNIFORM, 0, 256);
Mat src = src_full(Range(roi_offset_top, roi_offset_top + ysz.height), Range(roi_offset_left, roi_offset_left + ysz.width));
Mat dst = dst_full(Range(roi_offset_left, roi_offset_left + sz.height), Range(roi_offset_top, roi_offset_top + sz.width));
Mat gold = gold_full(Range(roi_offset_left, roi_offset_left + sz.height), Range(roi_offset_top, roi_offset_top + sz.width));
if(rgbWriter)
referenceYUV2RGB<YUV2RGB_Converter>(src, gold, yuvReader, rgbWriter);
else
referenceYUV2GRAY<YUV2GRAY_Converter>(src, gold, yuvReader, grayWriter);
cv::cvtColor(src, dst, code, -1);
EXPECT_EQ(0, countOfDifferencies(gold_full, dst_full));
}
}
INSTANTIATE_TEST_CASE_P(cvt420, Imgproc_ColorYUV,
::testing::Values((int)CV_YUV2RGB_NV12, (int)CV_YUV2BGR_NV12, (int)CV_YUV2RGB_NV21, (int)CV_YUV2BGR_NV21,
(int)CV_YUV2RGBA_NV12, (int)CV_YUV2BGRA_NV12, (int)CV_YUV2RGBA_NV21, (int)CV_YUV2BGRA_NV21,
(int)CV_YUV2RGB_YV12, (int)CV_YUV2BGR_YV12, (int)CV_YUV2RGB_IYUV, (int)CV_YUV2BGR_IYUV,
(int)CV_YUV2RGBA_YV12, (int)CV_YUV2BGRA_YV12, (int)CV_YUV2RGBA_IYUV, (int)CV_YUV2BGRA_IYUV,
(int)CV_YUV2GRAY_420));
INSTANTIATE_TEST_CASE_P(cvt422, Imgproc_ColorYUV,
::testing::Values((int)CV_YUV2RGB_UYVY, (int)CV_YUV2BGR_UYVY, (int)CV_YUV2RGBA_UYVY, (int)CV_YUV2BGRA_UYVY,
(int)CV_YUV2RGB_YUY2, (int)CV_YUV2BGR_YUY2, (int)CV_YUV2RGB_YVYU, (int)CV_YUV2BGR_YVYU,
(int)CV_YUV2RGBA_YUY2, (int)CV_YUV2BGRA_YUY2, (int)CV_YUV2RGBA_YVYU, (int)CV_YUV2BGRA_YVYU,
(int)CV_YUV2GRAY_UYVY, (int)CV_YUV2GRAY_YUY2));
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
#undef RGB
#undef YUV
typedef Vec3b YUV;
typedef Vec3b RGB;
int countOfDifferencies(const Mat& gold, const Mat& result, int maxAllowedDifference = 1)
{
Mat diff;
absdiff(gold, result, diff);
return countNonZero(diff.reshape(1) > maxAllowedDifference);
}
class YUVreader
{
public:
virtual ~YUVreader() {}
virtual YUV read(const Mat& yuv, int row, int col) = 0;
virtual int channels() = 0;
virtual Size size(Size imgSize) = 0;
virtual bool requiresEvenHeight() { return true; }
virtual bool requiresEvenWidth() { return true; }
static YUVreader* getReader(int code);
};
class RGBwriter
{
public:
virtual ~RGBwriter() {}
virtual void write(Mat& rgb, int row, int col, const RGB& val) = 0;
virtual int channels() = 0;
static RGBwriter* getWriter(int code);
};
class GRAYwriter
{
public:
virtual ~GRAYwriter() {}
virtual void write(Mat& gray, int row, int col, const uchar& val)
{
gray.at<uchar>(row, col) = val;
}
virtual int channels() { return 1; }
static GRAYwriter* getWriter(int code);
};
class RGB888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
rgb.at<Vec3b>(row, col) = val;
}
int channels() { return 3; }
};
class BGR888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec3b tmp(val[2], val[1], val[0]);
rgb.at<Vec3b>(row, col) = tmp;
}
int channels() { return 3; }
};
class RGBA8888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec4b tmp(val[0], val[1], val[2], 255);
rgb.at<Vec4b>(row, col) = tmp;
}
int channels() { return 4; }
};
class BGRA8888Writer : public RGBwriter
{
void write(Mat& rgb, int row, int col, const RGB& val)
{
Vec4b tmp(val[2], val[1], val[0], 255);
rgb.at<Vec4b>(row, col) = tmp;
}
int channels() { return 4; }
};
class YUV420Reader: public YUVreader
{
int channels() { return 1; }
Size size(Size imgSize) { return Size(imgSize.width, imgSize.height * 3 / 2); }
};
class YUV422Reader: public YUVreader
{
int channels() { return 2; }
Size size(Size imgSize) { return imgSize; }
bool requiresEvenHeight() { return false; }
};
class NV21Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2 + 1];
uchar v = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2];
return YUV(y, u, v);
}
};
struct NV12Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2];
uchar v = yuv.ptr<uchar>(yuv.rows * 2 / 3 + row/2)[(col/2)*2 + 1];
return YUV(y, u, v);
}
};
class YV12Reader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
int h = yuv.rows * 2 / 3;
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(h + (row/2 + h/2)/2)[col/2 + ((row/2 + h/2) % 2) * (yuv.cols/2)];
uchar v = yuv.ptr<uchar>(h + row/4)[col/2 + ((row/2) % 2) * (yuv.cols/2)];
return YUV(y, u, v);
}
};
class IYUVReader: public YUV420Reader
{
YUV read(const Mat& yuv, int row, int col)
{
int h = yuv.rows * 2 / 3;
uchar y = yuv.ptr<uchar>(row)[col];
uchar u = yuv.ptr<uchar>(h + row/4)[col/2 + ((row/2) % 2) * (yuv.cols/2)];
uchar v = yuv.ptr<uchar>(h + (row/2 + h/2)/2)[col/2 + ((row/2 + h/2) % 2) * (yuv.cols/2)];
return YUV(y, u, v);
}
};
class UYVYReader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][1];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2][0];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][0];
return YUV(y, u, v);
}
};
class YUY2Reader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][0];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2][1];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][1];
return YUV(y, u, v);
}
};
class YVYUReader: public YUV422Reader
{
YUV read(const Mat& yuv, int row, int col)
{
uchar y = yuv.ptr<Vec2b>(row)[col][0];
uchar u = yuv.ptr<Vec2b>(row)[(col/2)*2 + 1][1];
uchar v = yuv.ptr<Vec2b>(row)[(col/2)*2][1];
return YUV(y, u, v);
}
};
class YUV888Reader : public YUVreader
{
YUV read(const Mat& yuv, int row, int col)
{
return yuv.at<YUV>(row, col);
}
int channels() { return 3; }
Size size(Size imgSize) { return imgSize; }
bool requiresEvenHeight() { return false; }
bool requiresEvenWidth() { return false; }
};
class YUV2RGB_Converter
{
public:
RGB convert(YUV yuv)
{
int y = std::max(0, yuv[0] - 16);
int u = yuv[1] - 128;
int v = yuv[2] - 128;
uchar r = saturate_cast<uchar>(1.164f * y + 1.596f * v);
uchar g = saturate_cast<uchar>(1.164f * y - 0.813f * v - 0.391f * u);
uchar b = saturate_cast<uchar>(1.164f * y + 2.018f * u);
return RGB(r, g, b);
}
};
class YUV2GRAY_Converter
{
public:
uchar convert(YUV yuv)
{
return yuv[0];
}
};
YUVreader* YUVreader::getReader(int code)
{
switch(code)
{
case CV_YUV2RGB_NV12:
case CV_YUV2BGR_NV12:
case CV_YUV2RGBA_NV12:
case CV_YUV2BGRA_NV12:
return new NV12Reader();
case CV_YUV2RGB_NV21:
case CV_YUV2BGR_NV21:
case CV_YUV2RGBA_NV21:
case CV_YUV2BGRA_NV21:
return new NV21Reader();
case CV_YUV2RGB_YV12:
case CV_YUV2BGR_YV12:
case CV_YUV2RGBA_YV12:
case CV_YUV2BGRA_YV12:
return new YV12Reader();
case CV_YUV2RGB_IYUV:
case CV_YUV2BGR_IYUV:
case CV_YUV2RGBA_IYUV:
case CV_YUV2BGRA_IYUV:
return new IYUVReader();
case CV_YUV2RGB_UYVY:
case CV_YUV2BGR_UYVY:
case CV_YUV2RGBA_UYVY:
case CV_YUV2BGRA_UYVY:
return new UYVYReader();
//case CV_YUV2RGB_VYUY = 109,
//case CV_YUV2BGR_VYUY = 110,
//case CV_YUV2RGBA_VYUY = 113,
//case CV_YUV2BGRA_VYUY = 114,
// return ??
case CV_YUV2RGB_YUY2:
case CV_YUV2BGR_YUY2:
case CV_YUV2RGBA_YUY2:
case CV_YUV2BGRA_YUY2:
return new YUY2Reader();
case CV_YUV2RGB_YVYU:
case CV_YUV2BGR_YVYU:
case CV_YUV2RGBA_YVYU:
case CV_YUV2BGRA_YVYU:
return new YVYUReader();
case CV_YUV2GRAY_420:
return new NV21Reader();
case CV_YUV2GRAY_UYVY:
return new UYVYReader();
case CV_YUV2GRAY_YUY2:
return new YUY2Reader();
case CV_YUV2BGR:
case CV_YUV2RGB:
return new YUV888Reader();
default:
return 0;
}
}
RGBwriter* RGBwriter::getWriter(int code)
{
switch(code)
{
case CV_YUV2RGB_NV12:
case CV_YUV2RGB_NV21:
case CV_YUV2RGB_YV12:
case CV_YUV2RGB_IYUV:
case CV_YUV2RGB_UYVY:
//case CV_YUV2RGB_VYUY:
case CV_YUV2RGB_YUY2:
case CV_YUV2RGB_YVYU:
case CV_YUV2RGB:
return new RGB888Writer();
case CV_YUV2BGR_NV12:
case CV_YUV2BGR_NV21:
case CV_YUV2BGR_YV12:
case CV_YUV2BGR_IYUV:
case CV_YUV2BGR_UYVY:
//case CV_YUV2BGR_VYUY:
case CV_YUV2BGR_YUY2:
case CV_YUV2BGR_YVYU:
case CV_YUV2BGR:
return new BGR888Writer();
case CV_YUV2RGBA_NV12:
case CV_YUV2RGBA_NV21:
case CV_YUV2RGBA_YV12:
case CV_YUV2RGBA_IYUV:
case CV_YUV2RGBA_UYVY:
//case CV_YUV2RGBA_VYUY:
case CV_YUV2RGBA_YUY2:
case CV_YUV2RGBA_YVYU:
return new RGBA8888Writer();
case CV_YUV2BGRA_NV12:
case CV_YUV2BGRA_NV21:
case CV_YUV2BGRA_YV12:
case CV_YUV2BGRA_IYUV:
case CV_YUV2BGRA_UYVY:
//case CV_YUV2BGRA_VYUY:
case CV_YUV2BGRA_YUY2:
case CV_YUV2BGRA_YVYU:
return new BGRA8888Writer();
default:
return 0;
};
}
GRAYwriter* GRAYwriter::getWriter(int code)
{
switch(code)
{
case CV_YUV2GRAY_420:
case CV_YUV2GRAY_UYVY:
case CV_YUV2GRAY_YUY2:
return new GRAYwriter();
default:
return 0;
}
}
template<class convertor>
void referenceYUV2RGB(const Mat& yuv, Mat& rgb, YUVreader* yuvReader, RGBwriter* rgbWriter)
{
convertor cvt;
for(int row = 0; row < rgb.rows; ++row)
for(int col = 0; col < rgb.cols; ++col)
rgbWriter->write(rgb, row, col, cvt.convert(yuvReader->read(yuv, row, col)));
}
template<class convertor>
void referenceYUV2GRAY(const Mat& yuv, Mat& rgb, YUVreader* yuvReader, GRAYwriter* grayWriter)
{
convertor cvt;
for(int row = 0; row < rgb.rows; ++row)
for(int col = 0; col < rgb.cols; ++col)
grayWriter->write(rgb, row, col, cvt.convert(yuvReader->read(yuv, row, col)));
}
CV_ENUM(YUVCVTS, CV_YUV2RGB_NV12, CV_YUV2BGR_NV12, CV_YUV2RGB_NV21, CV_YUV2BGR_NV21,
CV_YUV2RGBA_NV12, CV_YUV2BGRA_NV12, CV_YUV2RGBA_NV21, CV_YUV2BGRA_NV21,
CV_YUV2RGB_YV12, CV_YUV2BGR_YV12, CV_YUV2RGB_IYUV, CV_YUV2BGR_IYUV,
CV_YUV2RGBA_YV12, CV_YUV2BGRA_YV12, CV_YUV2RGBA_IYUV, CV_YUV2BGRA_IYUV,
CV_YUV2RGB_UYVY, CV_YUV2BGR_UYVY, CV_YUV2RGBA_UYVY, CV_YUV2BGRA_UYVY,
CV_YUV2RGB_YUY2, CV_YUV2BGR_YUY2, CV_YUV2RGB_YVYU, CV_YUV2BGR_YVYU,
CV_YUV2RGBA_YUY2, CV_YUV2BGRA_YUY2, CV_YUV2RGBA_YVYU, CV_YUV2BGRA_YVYU,
CV_YUV2GRAY_420, CV_YUV2GRAY_UYVY, CV_YUV2GRAY_YUY2,
CV_YUV2BGR, CV_YUV2RGB);
typedef ::testing::TestWithParam<YUVCVTS> Imgproc_ColorYUV;
TEST_P(Imgproc_ColorYUV, accuracy)
{
int code = GetParam();
RNG& random = theRNG();
YUVreader* yuvReader = YUVreader::getReader(code);
RGBwriter* rgbWriter = RGBwriter::getWriter(code);
GRAYwriter* grayWriter = GRAYwriter::getWriter(code);
int dcn = (rgbWriter == 0) ? grayWriter->channels() : rgbWriter->channels();
for(int iter = 0; iter < 30; ++iter)
{
Size sz(random.uniform(1, 641), random.uniform(1, 481));
if(yuvReader->requiresEvenWidth()) sz.width += sz.width % 2;
if(yuvReader->requiresEvenHeight()) sz.height += sz.height % 2;
Size ysz = yuvReader->size(sz);
Mat src = Mat(ysz.height, ysz.width * yuvReader->channels(), CV_8UC1).reshape(yuvReader->channels());
Mat dst = Mat(sz.height, sz.width * dcn, CV_8UC1).reshape(dcn);
Mat gold(sz, CV_8UC(dcn));
random.fill(src, RNG::UNIFORM, 0, 256);
if(rgbWriter)
referenceYUV2RGB<YUV2RGB_Converter>(src, gold, yuvReader, rgbWriter);
else
referenceYUV2GRAY<YUV2GRAY_Converter>(src, gold, yuvReader, grayWriter);
cv::cvtColor(src, dst, code, -1);
EXPECT_EQ(0, countOfDifferencies(gold, dst));
}
}
TEST_P(Imgproc_ColorYUV, roi_accuracy)
{
int code = GetParam();
RNG& random = theRNG();
YUVreader* yuvReader = YUVreader::getReader(code);
RGBwriter* rgbWriter = RGBwriter::getWriter(code);
GRAYwriter* grayWriter = GRAYwriter::getWriter(code);
int dcn = (rgbWriter == 0) ? grayWriter->channels() : rgbWriter->channels();
for(int iter = 0; iter < 30; ++iter)
{
Size sz(random.uniform(1, 641), random.uniform(1, 481));
if(yuvReader->requiresEvenWidth()) sz.width += sz.width % 2;
if(yuvReader->requiresEvenHeight()) sz.height += sz.height % 2;
int roi_offset_top = random.uniform(0, 6);
int roi_offset_bottom = random.uniform(0, 6);
int roi_offset_left = random.uniform(0, 6);
int roi_offset_right = random.uniform(0, 6);
Size ysz = yuvReader->size(sz);
Mat src_full(ysz.height + roi_offset_top + roi_offset_bottom, ysz.width + roi_offset_left + roi_offset_right, CV_8UC(yuvReader->channels()));
Mat dst_full(sz.height + roi_offset_left + roi_offset_right, sz.width + roi_offset_top + roi_offset_bottom, CV_8UC(dcn), Scalar::all(0));
Mat gold_full(dst_full.size(), CV_8UC(dcn), Scalar::all(0));
random.fill(src_full, RNG::UNIFORM, 0, 256);
Mat src = src_full(Range(roi_offset_top, roi_offset_top + ysz.height), Range(roi_offset_left, roi_offset_left + ysz.width));
Mat dst = dst_full(Range(roi_offset_left, roi_offset_left + sz.height), Range(roi_offset_top, roi_offset_top + sz.width));
Mat gold = gold_full(Range(roi_offset_left, roi_offset_left + sz.height), Range(roi_offset_top, roi_offset_top + sz.width));
if(rgbWriter)
referenceYUV2RGB<YUV2RGB_Converter>(src, gold, yuvReader, rgbWriter);
else
referenceYUV2GRAY<YUV2GRAY_Converter>(src, gold, yuvReader, grayWriter);
cv::cvtColor(src, dst, code, -1);
EXPECT_EQ(0, countOfDifferencies(gold_full, dst_full));
}
}
INSTANTIATE_TEST_CASE_P(cvt420, Imgproc_ColorYUV,
::testing::Values((int)CV_YUV2RGB_NV12, (int)CV_YUV2BGR_NV12, (int)CV_YUV2RGB_NV21, (int)CV_YUV2BGR_NV21,
(int)CV_YUV2RGBA_NV12, (int)CV_YUV2BGRA_NV12, (int)CV_YUV2RGBA_NV21, (int)CV_YUV2BGRA_NV21,
(int)CV_YUV2RGB_YV12, (int)CV_YUV2BGR_YV12, (int)CV_YUV2RGB_IYUV, (int)CV_YUV2BGR_IYUV,
(int)CV_YUV2RGBA_YV12, (int)CV_YUV2BGRA_YV12, (int)CV_YUV2RGBA_IYUV, (int)CV_YUV2BGRA_IYUV,
(int)CV_YUV2GRAY_420));
INSTANTIATE_TEST_CASE_P(cvt422, Imgproc_ColorYUV,
::testing::Values((int)CV_YUV2RGB_UYVY, (int)CV_YUV2BGR_UYVY, (int)CV_YUV2RGBA_UYVY, (int)CV_YUV2BGRA_UYVY,
(int)CV_YUV2RGB_YUY2, (int)CV_YUV2BGR_YUY2, (int)CV_YUV2RGB_YVYU, (int)CV_YUV2BGR_YVYU,
(int)CV_YUV2RGBA_YUY2, (int)CV_YUV2BGRA_YUY2, (int)CV_YUV2RGBA_YVYU, (int)CV_YUV2BGRA_YVYU,
(int)CV_YUV2GRAY_UYVY, (int)CV_YUV2GRAY_YUY2));
modules/imgproc/test/test_distancetransform.cpp
+4 -4
View File
@@ -57,7 +57,7 @@ protected:
void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high );
int prepare_test_case( int test_case_idx );
int mask_size;
int dist_type;
int fill_labels;
@@ -86,7 +86,7 @@ void CV_DisTransTest::get_test_array_types_and_sizes( int test_case_idx,
types[INPUT][0] = CV_8UC1;
types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_32FC1;
types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_32SC1;
if( cvtest::randInt(rng) & 1 )
{
mask_size = 3;
@@ -239,7 +239,7 @@ cvTsDistTransform( const CvMat* _src, CvMat* _dst, int dist_type,
for( j = 0; j < mask_size/2; j++ )
tmp[-j-1] = tmp[j + width] = init_val;
for( j = 0; j < width; j++ )
{
if( s[j] == 0 )
@@ -287,7 +287,7 @@ cvTsDistTransform( const CvMat* _src, CvMat* _dst, int dist_type,
void CV_DisTransTest::prepare_to_validation( int /*test_case_idx*/ )
{
CvMat _input = test_mat[INPUT][0], _output = test_mat[REF_OUTPUT][0];
cvTsDistTransform( &_input, &_output, dist_type, mask_size, mask, 0 );
}
modules/imgproc/test/test_emd.cpp
+2 -2
View File
@@ -65,7 +65,7 @@ void CV_EMDTest::run( int )
const double success_error_level = 1e-6;
#define M 10000
double emd0 = 2460./210;
static float cost[] =
static float cost[] =
{
16, 16, 13, 22, 17,
14, 14, 13, 19, 15,
@@ -77,7 +77,7 @@ void CV_EMDTest::run( int )
Mat _w1(4, 1, CV_32F, w1);
Mat _w2(5, 1, CV_32F, w2);
Mat _cost(_w1.rows, _w2.rows, CV_32F, cost);
float emd = EMD( _w1, _w2, -1, _cost );
if( fabs( emd - emd0 ) > success_error_level*emd0 )
{
modules/imgproc/test/test_filter.cpp
+19 -19
View File
@@ -1123,15 +1123,15 @@ void CV_PyramidDownTest::prepare_to_validation( int /*test_case_idx*/ )
cvtest::filter2D(src, temp, src.depth(),
kernel, Point(kernel.cols/2, kernel.rows/2),
0, BORDER_REFLECT_101);
size_t elem_size = temp.elemSize();
size_t ncols = dst.cols*elem_size;
for( int i = 0; i < dst.rows; i++ )
{
const uchar* src_row = temp.ptr(i*2);
uchar* dst_row = dst.ptr(i);
for( size_t j = 0; j < ncols; j += elem_size )
{
for( size_t k = 0; k < elem_size; k++ )
@@ -1169,15 +1169,15 @@ void CV_PyramidUpTest::prepare_to_validation( int /*test_case_idx*/ )
{
Mat& src = test_mat[INPUT][0], &dst = test_mat[REF_OUTPUT][0];
Mat temp(dst.size(), dst.type());
size_t elem_size = src.elemSize();
size_t ncols = src.cols*elem_size;
for( int i = 0; i < src.rows; i++ )
{
const uchar* src_row = src.ptr(i);
uchar* dst_row = temp.ptr(i*2);
if( i*2 + 1 < temp.rows )
memset( temp.ptr(i*2+1), 0, temp.cols*elem_size );
for( size_t j = 0; j < ncols; j += elem_size )
@@ -1189,7 +1189,7 @@ void CV_PyramidUpTest::prepare_to_validation( int /*test_case_idx*/ )
}
}
}
cvtest::filter2D(temp, dst, dst.depth(),
kernel, Point(kernel.cols/2, kernel.rows/2),
0, BORDER_REFLECT_101);
@@ -1521,7 +1521,7 @@ void CV_PreCornerDetectTest::prepare_to_validation( int /*test_case_idx*/ )
double kernel_scale = type != ftype ? 1./255 : 1.;
Mat dx, dy, d2x, d2y, dxy, kernel;
kernel = cvtest::calcSobelKernel2D(1, 0, aperture_size);
cvtest::filter2D(src, dx, ftype, kernel*kernel_scale, anchor, 0, BORDER_REPLICATE);
kernel = cvtest::calcSobelKernel2D(2, 0, aperture_size);
@@ -1660,13 +1660,13 @@ void CV_IntegralTest::run_func()
static void test_integral( const Mat& img, Mat* sum, Mat* sqsum, Mat* tilted )
{
CV_Assert( img.depth() == CV_32F );
sum->create(img.rows+1, img.cols+1, CV_64F);
if( sqsum )
sqsum->create(img.rows+1, img.cols+1, CV_64F);
if( tilted )
tilted->create(img.rows+1, img.cols+1, CV_64F);
const float* data = img.ptr<float>();
double* sdata = sum->ptr<double>();
double* sqdata = sqsum ? sqsum->ptr<double>() : 0;
@@ -1740,20 +1740,20 @@ void CV_IntegralTest::prepare_to_validation( int /*test_case_idx*/ )
psqsum2 = sqsum0 ? *sqsum0 : Mat();
ptsum2 = tsum0 ? *tsum0 : Mat();
}
for( int i = 0; i < cn; i++ )
{
if( cn > 1 )
cvtest::extract(src, plane, i);
plane.convertTo(srcf, CV_32F);
test_integral( srcf, &psum, sqsum0 ? &psqsum : 0, tsum0 ? &ptsum : 0 );
psum.convertTo(psum2, sum0->depth());
if( sqsum0 )
psqsum.convertTo(psqsum2, sqsum0->depth());
if( tsum0 )
ptsum.convertTo(ptsum2, tsum0->depth());
if( cn > 1 )
{
cvtest::insert(psum2, *sum0, i);
@@ -1790,11 +1790,11 @@ class CV_FilterSupportedFormatsTest : public cvtest::BaseTest
{
public:
CV_FilterSupportedFormatsTest() {}
~CV_FilterSupportedFormatsTest() {}
~CV_FilterSupportedFormatsTest() {}
protected:
void run(int)
{
const int depths[][2] =
const int depths[][2] =
{
{CV_8U, CV_8U},
{CV_8U, CV_16U},
@@ -1811,7 +1811,7 @@ protected:
{CV_64F, CV_64F},
{-1, -1}
};
int i = 0;
volatile int fidx = -1;
try
@@ -1830,10 +1830,10 @@ protected:
symkernelX += kernelX;
flip(kernelY, symkernelY, 0);
symkernelY += kernelY;
Mat elem_ellipse = getStructuringElement(MORPH_ELLIPSE, Size(7, 7));
Mat elem_rect = getStructuringElement(MORPH_RECT, Size(7, 7));
for( i = 0; depths[i][0] >= 0; i++ )
{
int sdepth = depths[i][0];
@@ -1879,7 +1879,7 @@ protected:
fidx == 7 ? "blur" :
fidx == 8 || fidx == 9 ? "morphologyEx" :
"unknown???");
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
}
}
modules/imgproc/test/test_imgwarp.cpp
+8 -8
View File
@@ -1498,12 +1498,12 @@ TEST(Imgproc_resize_area, regression)
ASSERT_EQ(actual.type(), expected.type());
ASSERT_EQ(actual.size(), expected.size());
Mat diff;
absdiff(actual, expected, diff);
Mat one_channel_diff = diff; //.reshape(1);
float elem_diff = 1.0f;
Size dsize = actual.size();
bool next = true;
@@ -1511,25 +1511,25 @@ TEST(Imgproc_resize_area, regression)
{
ushort* eD = expected.ptr<ushort>(dy);
ushort* aD = actual.ptr<ushort>(dy);
for (int dx = 0; dx < dsize.width && next; ++dx)
if (fabs(static_cast<float>(aD[dx] - eD[dx])) > elem_diff)
{
cvtest::TS::ptr()->printf(cvtest::TS::SUMMARY, "Inf norm: %f\n", static_cast<float>(norm(actual, expected, NORM_INF)));
cvtest::TS::ptr()->printf(cvtest::TS::SUMMARY, "Error in : (%d, %d)\n", dx, dy);
const int radius = 3;
int rmin = MAX(dy - radius, 0), rmax = MIN(dy + radius, dsize.height);
int cmin = MAX(dx - radius, 0), cmax = MIN(dx + radius, dsize.width);
std::cout << "Abs diff:" << std::endl << diff << std::endl;
std::cout << "actual result:\n" << actual(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
std::cout << "expected result:\n" << expected(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
next = false;
}
}
ASSERT_EQ(norm(one_channel_diff, cv::NORM_INF), 0);
}
modules/imgproc/test/test_imgwarp_strict.cpp
+93 -93
View File
@@ -58,7 +58,7 @@ namespace internal
cvtest::TS::ptr()->printf(cvtest::TS::SUMMARY, buffer);
va_end(args);
}
#define PRINT_TO_LOG __wrap_printf_func
}
@@ -78,7 +78,7 @@ public:
CV_ImageWarpBaseTest();
virtual ~CV_ImageWarpBaseTest();
virtual void run(int);
protected:
virtual void generate_test_data();
@@ -89,7 +89,7 @@ protected:
virtual void prepare_test_data_for_reference_func();
Size randSize(RNG& rng) const;
const char* interpolation_to_string(int inter_type) const;
int interpolation;
@@ -150,7 +150,7 @@ void CV_ImageWarpBaseTest::generate_test_data()
int cn = rng.uniform(1, 4);
while (cn == 2)
cn = rng.uniform(1, 4);
src.create(ssize, CV_MAKE_TYPE(depth, cn));
// generating the src matrix
@@ -170,10 +170,10 @@ void CV_ImageWarpBaseTest::generate_test_data()
for (x = cell_size; x < src.cols; x += cell_size)
line(src, Point2i(x, 0), Point2i(x, src.rows), Scalar::all(0), 1);
}
// generating an interpolation type
interpolation = rng.uniform(0, CV_INTER_LANCZOS4 + 1);
// generating the dst matrix structure
double scale_x, scale_y;
if (interpolation == INTER_AREA)
@@ -196,16 +196,16 @@ void CV_ImageWarpBaseTest::generate_test_data()
scale_y = rng.uniform(0.4, 4.0);
}
CV_Assert(scale_x > 0.0f && scale_y > 0.0f);
dsize.width = saturate_cast<int>((ssize.width + scale_x - 1) / scale_x);
dsize.height = saturate_cast<int>((ssize.height + scale_y - 1) / scale_y);
dst = Mat::zeros(dsize, src.type());
reference_dst = Mat::zeros(dst.size(), CV_MAKE_TYPE(CV_32F, dst.channels()));
scale_x = src.cols / static_cast<double>(dst.cols);
scale_y = src.rows / static_cast<double>(dst.rows);
if (interpolation == INTER_AREA && (scale_x < 1.0 || scale_y < 1.0))
interpolation = INTER_LINEAR;
}
@@ -231,7 +231,7 @@ void CV_ImageWarpBaseTest::validate_results() const
{
Mat _dst;
dst.convertTo(_dst, reference_dst.depth());
Size dsize = dst.size(), ssize = src.size();
int cn = _dst.channels();
dsize.width *= cn;
@@ -244,12 +244,12 @@ void CV_ImageWarpBaseTest::validate_results() const
t = 1.0f;
else if (interpolation == INTER_AREA)
t = 2.0f;
for (int dy = 0; dy < dsize.height; ++dy)
{
const float* rD = reference_dst.ptr<float>(dy);
const float* D = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
if (fabs(rD[dx] - D[dx]) > t &&
// fabs(rD[dx] - D[dx]) < 250.0f &&
@@ -260,7 +260,7 @@ void CV_ImageWarpBaseTest::validate_results() const
PRINT_TO_LOG("Tuple (rD, D): (%f, %f)\n", rD[dx], D[dx]);
PRINT_TO_LOG("Dsize: (%d, %d)\n", dsize.width / cn, dsize.height);
PRINT_TO_LOG("Ssize: (%d, %d)\n", src.cols, src.rows);
double scale_x = static_cast<double>(ssize.width) / dsize.width;
double scale_y = static_cast<double>(ssize.height) / dsize.height;
bool area_fast = interpolation == INTER_AREA &&
@@ -271,37 +271,37 @@ void CV_ImageWarpBaseTest::validate_results() const
scale_y = cvRound(scale_y);
scale_x = cvRound(scale_x);
}
PRINT_TO_LOG("Interpolation: %s\n", interpolation_to_string(area_fast ? INTER_LANCZOS4 + 1 : interpolation));
PRINT_TO_LOG("Scale (x, y): (%lf, %lf)\n", scale_x, scale_y);
PRINT_TO_LOG("Elemsize: %d\n", src.elemSize1());
PRINT_TO_LOG("Channels: %d\n", cn);
#ifdef SHOW_IMAGE
const std::string w1("OpenCV impl (run func)"), w2("Reference func"), w3("Src image"), w4("Diff");
namedWindow(w1, CV_WINDOW_KEEPRATIO);
namedWindow(w2, CV_WINDOW_KEEPRATIO);
namedWindow(w3, CV_WINDOW_KEEPRATIO);
namedWindow(w4, CV_WINDOW_KEEPRATIO);
Mat diff;
absdiff(reference_dst, _dst, diff);
imshow(w1, dst);
imshow(w2, reference_dst);
imshow(w3, src);
imshow(w4, diff);
waitKey();
#endif
const int radius = 3;
int rmin = MAX(dy - radius, 0), rmax = MIN(dy + radius, dsize.height);
int cmin = MAX(dx / cn - radius, 0), cmax = MIN(dx / cn + radius, dsize.width);
std::cout << "opencv result:\n" << dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
std::cout << "reference result:\n" << reference_dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl;
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
@@ -334,7 +334,7 @@ protected:
virtual void run_func();
virtual void run_reference_func();
private:
double scale_x;
double scale_y;
@@ -343,7 +343,7 @@ private:
void resize_generic();
void resize_area();
double getWeight(double a, double b, int x);
typedef std::vector<std::pair<int, double> > dim;
void generate_buffer(double scale, dim& _dim);
void resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim);
@@ -366,23 +366,23 @@ namespace internal
coeffs[0] = 1.f - x;
coeffs[1] = x;
}
void interpolateCubic(float x, float* coeffs)
{
const float A = -0.75f;
coeffs[0] = ((A*(x + 1) - 5*A)*(x + 1) + 8*A)*(x + 1) - 4*A;
coeffs[1] = ((A + 2)*x - (A + 3))*x*x + 1;
coeffs[2] = ((A + 2)*(1 - x) - (A + 3))*(1 - x)*(1 - x) + 1;
coeffs[3] = 1.f - coeffs[0] - coeffs[1] - coeffs[2];
}
void interpolateLanczos4(float x, float* coeffs)
{
static const double s45 = 0.70710678118654752440084436210485;
static const double cs[][2]=
{{1, 0}, {-s45, -s45}, {0, 1}, {s45, -s45}, {-1, 0}, {s45, s45}, {0, -1}, {-s45, s45}};
if( x < FLT_EPSILON )
{
for( int i = 0; i < 8; i++ )
@@ -390,7 +390,7 @@ namespace internal
coeffs[3] = 1;
return;
}
float sum = 0;
double y0=-(x+3)*CV_PI*0.25, s0 = sin(y0), c0=cos(y0);
for(int i = 0; i < 8; i++ )
@@ -399,12 +399,12 @@ namespace internal
coeffs[i] = (float)((cs[i][0]*s0 + cs[i][1]*c0)/(y*y));
sum += coeffs[i];
}
sum = 1.f/sum;
for(int i = 0; i < 8; i++ )
coeffs[i] *= sum;
}
typedef void (*interpolate_method)(float x, float* coeffs);
interpolate_method inter_array[] = { &interpolateLinear, &interpolateCubic, &interpolateLanczos4 };
}
@@ -412,10 +412,10 @@ namespace internal
void CV_Resize_Test::generate_test_data()
{
CV_ImageWarpBaseTest::generate_test_data();
scale_x = src.cols / static_cast<double>(dst.cols);
scale_y = src.rows / static_cast<double>(dst.rows);
area_fast = interpolation == INTER_AREA &&
fabs(scale_x - cvRound(scale_x)) < FLT_EPSILON &&
fabs(scale_y - cvRound(scale_y)) < FLT_EPSILON;
@@ -434,7 +434,7 @@ void CV_Resize_Test::run_func()
void CV_Resize_Test::run_reference_func()
{
CV_ImageWarpBaseTest::prepare_test_data_for_reference_func();
if (interpolation == INTER_AREA)
resize_area();
else
@@ -451,28 +451,28 @@ double CV_Resize_Test::getWeight(double a, double b, int x)
void CV_Resize_Test::resize_area()
{
Size ssize = src.size(), dsize = reference_dst.size();
CV_Assert(ssize.area() > 0 && dsize.area() > 0);
CV_Assert(ssize.area() > 0 && dsize.area() > 0);
int cn = src.channels();
CV_Assert(scale_x >= 1.0 && scale_y >= 1.0);
CV_Assert(scale_x >= 1.0 && scale_y >= 1.0);
double fsy0 = 0, fsy1 = scale_y;
for (int dy = 0; dy < dsize.height; ++dy)
{
float* yD = reference_dst.ptr<float>(dy);
int isy0 = cvFloor(fsy0), isy1 = std::min(cvFloor(fsy1), ssize.height - 1);
CV_Assert(isy1 <= ssize.height && isy0 < ssize.height);
double fsx0 = 0, fsx1 = scale_x;
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + cn * dx;
int isx0 = cvFloor(fsx0), isx1 = std::min(ssize.width - 1, cvFloor(fsx1));
CV_Assert(isx1 <= ssize.width);
CV_Assert(isx0 < ssize.width);
// for each pixel of dst
for (int r = 0; r < cn; ++r)
{
@@ -490,7 +490,7 @@ void CV_Resize_Test::resize_area()
area += w;
}
}
CV_Assert(area != 0);
// norming pixel
xyD[r] = static_cast<float>(xyD[r] / area);
@@ -504,19 +504,19 @@ void CV_Resize_Test::resize_area()
// for interpolation type : INTER_LINEAR, INTER_LINEAR, INTER_CUBIC, INTER_LANCZOS4
void CV_Resize_Test::resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim)
{
Size dsize = _dst.size();
Size dsize = _dst.size();
int cn = _dst.channels();
float* yD = _dst.ptr<float>(dy);
if (interpolation == INTER_NEAREST)
{
const float* yS = _src.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
int isx = _dim[dx].first;
const float* xyS = yS + isx * cn;
float* xyD = yD + dx * cn;
const float* xyS = yS + isx * cn;
float* xyD = yD + dx * cn;
for (int r = 0; r < cn; ++r)
xyD[r] = xyS[r];
}
@@ -525,13 +525,13 @@ void CV_Resize_Test::resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _d
{
internal::interpolate_method inter_func = internal::inter_array[interpolation - (interpolation == INTER_LANCZOS4 ? 2 : 1)];
size_t elemsize = _src.elemSize();
int ofs = 0, ksize = 2;
if (interpolation == INTER_CUBIC)
ofs = 1, ksize = 4;
else if (interpolation == INTER_LANCZOS4)
ofs = 3, ksize = 8;
Mat _extended_src_row(1, _src.cols + ksize * 2, _src.type());
uchar* srow = _src.data + dy * _src.step;
memcpy(_extended_src_row.data + elemsize * ksize, srow, _src.step);
@@ -540,7 +540,7 @@ void CV_Resize_Test::resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _d
memcpy(_extended_src_row.data + k * elemsize, srow, elemsize);
memcpy(_extended_src_row.data + (ksize + k) * elemsize + _src.step, srow + _src.step - elemsize, elemsize);
}
for (int dx = 0; dx < dsize.width; ++dx)
{
int isx = _dim[dx].first;
@@ -569,7 +569,7 @@ void CV_Resize_Test::generate_buffer(double scale, dim& _dim)
{
size_t length = _dim.size();
for (size_t dx = 0; dx < length; ++dx)
{
{
double fsx = scale * (dx + 0.5) - 0.5;
int isx = cvFloor(fsx);
_dim[dx] = std::make_pair(isx, fsx - isx);
@@ -580,12 +580,12 @@ void CV_Resize_Test::resize_generic()
{
Size dsize = reference_dst.size(), ssize = src.size();
CV_Assert(dsize.area() > 0 && ssize.area() > 0);
dim dims[] = { dim(dsize.width), dim(dsize.height) };
if (interpolation == INTER_NEAREST)
{
for (int dx = 0; dx < dsize.width; ++dx)
dims[0][dx].first = std::min(cvFloor(dx * scale_x), ssize.width - 1);
dims[0][dx].first = std::min(cvFloor(dx * scale_x), ssize.width - 1);
for (int dy = 0; dy < dsize.height; ++dy)
dims[1][dy].first = std::min(cvFloor(dy * scale_y), ssize.height - 1);
}
@@ -594,14 +594,14 @@ void CV_Resize_Test::resize_generic()
generate_buffer(scale_x, dims[0]);
generate_buffer(scale_y, dims[1]);
}
Mat tmp(ssize.height, dsize.width, reference_dst.type());
for (int dy = 0; dy < tmp.rows; ++dy)
resize_1d(src, tmp, dy, dims[0]);
transpose(tmp, tmp);
transpose(reference_dst, reference_dst);
for (int dy = 0; dy < tmp.rows; ++dy)
resize_1d(tmp, reference_dst, dy, dims[1]);
transpose(reference_dst, reference_dst);
@@ -634,7 +634,7 @@ protected:
Scalar borderValue;
remap_func funcs[2];
private:
void remap_nearest(const Mat&, Mat&);
void remap_generic(const Mat&, Mat&);
@@ -671,7 +671,7 @@ void CV_Remap_Test::generate_test_data()
const int n = std::min(std::min(src.cols, src.rows) / 10 + 1, 2);
float _n = 0; //static_cast<float>(-n);
switch (mapx.type())
{
case CV_16SC2:
@@ -737,7 +737,7 @@ void CV_Remap_Test::generate_test_data()
}
}
break;
default:
assert(0);
break;
@@ -756,7 +756,7 @@ void CV_Remap_Test::convert_maps()
else if (interpolation != INTER_NEAREST)
if (mapy.type() != CV_16UC1)
mapy.clone().convertTo(mapy, CV_16UC1);
if (interpolation == INTER_NEAREST)
mapy = Mat();
CV_Assert(((interpolation == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16UC1 ||
@@ -803,7 +803,7 @@ void CV_Remap_Test::run_reference_func()
if (interpolation == INTER_AREA)
interpolation = INTER_LINEAR;
int index = interpolation == INTER_NEAREST ? 0 : 1;
(this->*funcs[index])(src, reference_dst);
}
@@ -821,7 +821,7 @@ void CV_Remap_Test::remap_nearest(const Mat& _src, Mat& _dst)
{
const short* yM = mapx.ptr<short>(dy);
float* yD = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + cn * dx;
@@ -858,7 +858,7 @@ void CV_Remap_Test::remap_nearest(const Mat& _src, Mat& _dst)
void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
{
CV_Assert(mapx.type() == CV_16SC2 && mapy.type() == CV_16UC1);
int ksize = 2;
if (interpolation == INTER_CUBIC)
ksize = 4;
@@ -867,7 +867,7 @@ void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
else if (interpolation != INTER_LINEAR)
assert(0);
int ofs = (ksize / 2) - 1;
CV_Assert(_src.depth() == CV_32F && _dst.type() == _src.type());
Size ssize = _src.size(), dsize = _dst.size();
int cn = _src.channels(), width1 = std::max(ssize.width - ksize + 1, 0),
@@ -882,7 +882,7 @@ void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
const ushort* yMy = mapy.ptr<ushort>(dy);
float* yD = _dst.ptr<float>(dy);
for (int dx = 0; dx < dsize.width; ++dx)
{
float* xyD = yD + dx * cn;
@@ -891,7 +891,7 @@ void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
inter_func((yMy[dx] & (INTER_TAB_SIZE - 1)) / static_cast<float>(INTER_TAB_SIZE), w);
inter_func(((yMy[dx] >> INTER_BITS) & (INTER_TAB_SIZE - 1)) / static_cast<float>(INTER_TAB_SIZE), w + ksize);
isx -= ofs;
isy -= ofs;
@@ -915,7 +915,7 @@ void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst)
else if (borderType != BORDER_TRANSPARENT)
{
int ar_x[8], ar_y[8];
for (int k = 0; k < ksize; k++)
{
ar_x[k] = borderInterpolate(isx + k, ssize.width, borderType) * cn;
@@ -1009,7 +1009,7 @@ void CV_WarpAffine_Test::generate_test_data()
M.convertTo(tmp, depth);
M = tmp;
}
// warp_matrix is inverse
if (rng.uniform(0., 1.) > 0)
interpolation |= CV_WARP_INVERSE_MAP;
@@ -1042,7 +1042,7 @@ void CV_WarpAffine_Test::warpAffine(const Mat& _src, Mat& _dst)
Mat tM;
M.convertTo(tM, CV_64F);
int inter = interpolation & INTER_MAX;
if (inter == INTER_AREA)
inter = INTER_LINEAR;
@@ -1052,35 +1052,35 @@ void CV_WarpAffine_Test::warpAffine(const Mat& _src, Mat& _dst)
mapy.create(dsize, CV_16SC1);
else
mapy = Mat();
if (!(interpolation & CV_WARP_INVERSE_MAP))
invertAffineTransform(tM.clone(), tM);
const int AB_BITS = MAX(10, (int)INTER_BITS);
const int AB_SCALE = 1 << AB_BITS;
const int AB_SCALE = 1 << AB_BITS;
int round_delta = (inter == INTER_NEAREST) ? AB_SCALE / 2 : (AB_SCALE / INTER_TAB_SIZE / 2);
const double* data_tM = tM.ptr<double>(0);
for (int dy = 0; dy < dsize.height; ++dy)
{
short* yM = mapx.ptr<short>(dy);
for (int dx = 0; dx < dsize.width; ++dx, yM += 2)
{
int v1 = saturate_cast<int>(saturate_cast<int>(data_tM[0] * dx * AB_SCALE) +
saturate_cast<int>((data_tM[1] * dy + data_tM[2]) * AB_SCALE) + round_delta),
v2 = saturate_cast<int>(saturate_cast<int>(data_tM[3] * dx * AB_SCALE) +
{
int v1 = saturate_cast<int>(saturate_cast<int>(data_tM[0] * dx * AB_SCALE) +
saturate_cast<int>((data_tM[1] * dy + data_tM[2]) * AB_SCALE) + round_delta),
v2 = saturate_cast<int>(saturate_cast<int>(data_tM[3] * dx * AB_SCALE) +
saturate_cast<int>((data_tM[4] * dy + data_tM[5]) * AB_SCALE) + round_delta);
v1 >>= AB_BITS - INTER_BITS;
v2 >>= AB_BITS - INTER_BITS;
yM[0] = saturate_cast<short>(v1 >> INTER_BITS);
yM[1] = saturate_cast<short>(v2 >> INTER_BITS);
if (inter != INTER_NEAREST)
mapy.ptr<short>(dy)[dx] = ((v2 & (INTER_TAB_SIZE - 1)) * INTER_TAB_SIZE + (v1 & (INTER_TAB_SIZE - 1)));
}
}
CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16SC1));
cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue);
}
@@ -1106,7 +1106,7 @@ protected:
private:
void warpPerspective(const Mat&, Mat&);
};
CV_WarpPerspective_Test::CV_WarpPerspective_Test() :
CV_WarpAffine_Test()
{
@@ -1156,24 +1156,24 @@ void CV_WarpPerspective_Test::warpPerspective(const Mat& _src, Mat& _dst)
CV_Assert(dsize.area() > 0);
CV_Assert(_src.type() == _dst.type());
if (M.depth() != CV_64F)
{
Mat tmp;
M.convertTo(tmp, CV_64F);
M = tmp;
}
if (M.depth() != CV_64F)
{
Mat tmp;
M.convertTo(tmp, CV_64F);
M = tmp;
}
if (!(interpolation & CV_WARP_INVERSE_MAP))
{
Mat tmp;
invert(M, tmp);
M = tmp;
}
int inter = interpolation & INTER_MAX;
if (inter == INTER_AREA)
inter = INTER_LINEAR;
mapx.create(dsize, CV_16SC2);
if (inter != INTER_NEAREST)
mapy.create(dsize, CV_16SC1);
@@ -1184,30 +1184,30 @@ void CV_WarpPerspective_Test::warpPerspective(const Mat& _src, Mat& _dst)
for (int dy = 0; dy < dsize.height; ++dy)
{
short* yMx = mapx.ptr<short>(dy);
for (int dx = 0; dx < dsize.width; ++dx, yMx += 2)
{
double den = tM[6] * dx + tM[7] * dy + tM[8];
den = den ? 1.0 / den : 0.0;
if (inter == INTER_NEAREST)
{
yMx[0] = saturate_cast<short>((tM[0] * dx + tM[1] * dy + tM[2]) * den);
yMx[1] = saturate_cast<short>((tM[3] * dx + tM[4] * dy + tM[5]) * den);
continue;
}
den *= INTER_TAB_SIZE;
int v0 = saturate_cast<int>((tM[0] * dx + tM[1] * dy + tM[2]) * den);
int v1 = saturate_cast<int>((tM[3] * dx + tM[4] * dy + tM[5]) * den);
yMx[0] = saturate_cast<short>(v0 >> INTER_BITS);
yMx[1] = saturate_cast<short>(v1 >> INTER_BITS);
mapy.ptr<short>(dy)[dx] = saturate_cast<short>((v1 & (INTER_TAB_SIZE - 1)) *
mapy.ptr<short>(dy)[dx] = saturate_cast<short>((v1 & (INTER_TAB_SIZE - 1)) *
INTER_TAB_SIZE + (v0 & (INTER_TAB_SIZE - 1)));
}
}
CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16SC1));
cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue);
}
modules/imgproc/test/test_moments.cpp
+11 -11
View File
@@ -50,7 +50,7 @@ public:
CV_MomentsTest();
protected:
enum { MOMENT_COUNT = 25 };
int prepare_test_case( int test_case_idx );
void prepare_to_validation( int /*test_case_idx*/ );
@@ -78,7 +78,7 @@ void CV_MomentsTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Sca
{
cvtest::ArrayTest::get_minmax_bounds( i, j, type, low, high );
int depth = CV_MAT_DEPTH(type);
if( depth == CV_16U )
{
low = Scalar::all(0);
@@ -167,7 +167,7 @@ void CV_MomentsTest::prepare_to_validation( int /*test_case_idx*/ )
int cn = src.channels();
int i, y, x, cols = src.cols;
double xc = 0., yc = 0.;
memset( &m, 0, sizeof(m));
for( y = 0; y < src.rows; y++ )
@@ -199,7 +199,7 @@ void CV_MomentsTest::prepare_to_validation( int /*test_case_idx*/ )
m.m01 += s0*y;
m.m02 += (s0*y)*y;
m.m03 += ((s0*y)*y)*y;
m.m10 += s1;
m.m11 += s1*y;
m.m12 += (s1*y)*y;
@@ -243,7 +243,7 @@ void CV_MomentsTest::prepare_to_validation( int /*test_case_idx*/ )
m.mu02 += s0*y1*y1;
m.mu03 += ((s0*y1)*y1)*y1;
m.mu11 += s1*y1;
m.mu12 += (s1*y1)*y1;
@@ -291,9 +291,9 @@ public:
CV_HuMomentsTest();
protected:
enum { MOMENT_COUNT = 18, HU_MOMENT_COUNT = 7 };
int prepare_test_case( int test_case_idx );
void prepare_to_validation( int /*test_case_idx*/ );
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
@@ -367,7 +367,7 @@ void CV_HuMomentsTest::prepare_to_validation( int /*test_case_idx*/ )
double nu20 = m->mu20 * s2;
double nu11 = m->mu11 * s2;
double nu02 = m->mu02 * s2;
double nu30 = m->mu30 * s3;
double nu21 = m->mu21 * s3;
double nu12 = m->mu12 * s3;
@@ -396,7 +396,7 @@ class CV_SmallContourMomentTest : public cvtest::BaseTest
{
public:
CV_SmallContourMomentTest() {}
~CV_SmallContourMomentTest() {}
~CV_SmallContourMomentTest() {}
protected:
void run(int)
{
@@ -407,10 +407,10 @@ protected:
points.push_back(Point(53, 53));
points.push_back(Point(46, 54));
points.push_back(Point(49, 51));
Moments m = moments(points, false);
double area = contourArea(points);
CV_Assert( m.m00 == 0 && m.m01 == 0 && m.m10 == 0 && area == 0 );
}
catch(...)
modules/imgproc/test/test_thresh.cpp
+2 -2
View File
@@ -127,7 +127,7 @@ static void test_threshold( const Mat& _src, Mat& _dst,
int width_n = _src.cols*cn, height = _src.rows;
int ithresh = cvFloor(thresh);
int imaxval, ithresh2;
if( depth == CV_8U )
{
ithresh2 = saturate_cast<uchar>(ithresh);
@@ -145,7 +145,7 @@ static void test_threshold( const Mat& _src, Mat& _dst,
}
assert( depth == CV_8U || depth == CV_16S || depth == CV_32F );
switch( thresh_type )
{
case CV_THRESH_BINARY: