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提交 66df8ef0 编写于 作者: V Vladislav Vinogradov
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added Filter Engine to gpu module. 

disabled gpu::sum, gpu::minMax, gpu:Canny until fix crash.
上级 7a3b0785
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Showing with 1127 addition and 401 deletion
modules/gpu/include/opencv2/gpu/gpu.hpp
浏览文件 @ 66df8ef0
......@@ -407,10 +407,12 @@ namespace cv
//! computes sum of array elements
//! supports CV_8UC1, CV_8UC4 types
//! disabled until fix crash
CV_EXPORTS Scalar sum(const GpuMat& m);
//! finds global minimum and maximum array elements and returns their values
//! supports only CV_8UC1 type
//! disabled until fix npp bug
CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal = 0);
//! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i))
......@@ -451,8 +453,10 @@ namespace cv
CV_EXPORTS void log(const GpuMat& a, GpuMat& b);
//! computes magnitude (magnitude(i)) of each (x(i), y(i)) vector
//! supports only CV_32FC1 type
CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
//! computes magnitude (magnitude(i)) of complex (x(i).re, x(i).im) vector
//! supports only CV_32FC2 type
CV_EXPORTS void magnitude(const GpuMat& x, GpuMat& magnitude);
////////////////////////////// Image processing //////////////////////////////
......@@ -517,34 +521,169 @@ namespace cv
//! supports only CV_32FC1 source type
CV_EXPORTS void integral(GpuMat& src, GpuMat& sum, GpuMat& sqsum);
//! applies Canny edge detector and produces the edge map
//! supprots only CV_8UC1 source type
//! disabled until fix crash
CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize = 3);
//////////////////////////////// Filter Engine ////////////////////////////////
/*!
The Base Class for 1D or Row-wise Filters
This is the base class for linear or non-linear filters that process 1D data.
In particular, such filters are used for the "horizontal" filtering parts in separable filters.
*/
class CV_EXPORTS BaseRowFilter_GPU
{
public:
BaseRowFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {}
virtual ~BaseRowFilter_GPU() {}
virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
int ksize, anchor;
};
/*!
The Base Class for Column-wise Filters
This is the base class for linear or non-linear filters that process columns of 2D arrays.
Such filters are used for the "vertical" filtering parts in separable filters.
*/
class CV_EXPORTS BaseColumnFilter_GPU
{
public:
BaseColumnFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {}
virtual ~BaseColumnFilter_GPU() {}
virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
int ksize, anchor;
};
/*!
The Base Class for Non-Separable 2D Filters.
This is the base class for linear or non-linear 2D filters.
*/
class CV_EXPORTS BaseFilter_GPU
{
public:
BaseFilter_GPU(const Size& ksize_, const Point& anchor_) : ksize(ksize_), anchor(anchor_) {}
virtual ~BaseFilter_GPU() {}
virtual void operator()(const GpuMat& src, GpuMat& dst) = 0;
Size ksize;
Point anchor;
};
/*!
The Base Class for Filter Engine.
The class can be used to apply an arbitrary filtering operation to an image.
It contains all the necessary intermediate buffers.
*/
class CV_EXPORTS FilterEngine_GPU
{
public:
virtual ~FilterEngine_GPU() {}
virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1)) = 0;
};
//! returns the non-separable filter engine with the specified filter
CV_EXPORTS Ptr<FilterEngine_GPU> createFilter2D_GPU(const Ptr<BaseFilter_GPU> filter2D);
//! returns the separable filter engine with the specified filters
CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableFilter_GPU(const Ptr<BaseRowFilter_GPU>& rowFilter,
const Ptr<BaseColumnFilter_GPU>& columnFilter);
//! returns horizontal 1D box filter
//! supports only CV_8UC1 source type and CV_32FC1 sum type
CV_EXPORTS Ptr<BaseRowFilter_GPU> getRowSumFilter_GPU(int srcType, int sumType, int ksize, int anchor = -1);
//! returns vertical 1D box filter
//! supports only CV_8UC1 sum type and CV_32FC1 dst type
CV_EXPORTS Ptr<BaseColumnFilter_GPU> getColumnSumFilter_GPU(int sumType, int dstType, int ksize, int anchor = -1);
//! returns 2D box filter
//! supports CV_8UC1 and CV_8UC4 source type, dst type must be the same as source type
CV_EXPORTS Ptr<BaseFilter_GPU> getBoxFilter_GPU(int srcType, int dstType, const Size& ksize, Point anchor = Point(-1, -1));
//! returns box filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createBoxFilter_GPU(int srcType, int dstType, const Size& ksize,
const Point& anchor = Point(-1,-1));
//! returns 2D morphological filter
//! only MORPH_ERODE and MORPH_DILATE are supported
//! supports CV_8UC1 and CV_8UC4 types
//! kernel must have CV_8UC1 type, one rows and cols == ksize.width * ksize.height
CV_EXPORTS Ptr<BaseFilter_GPU> getMorphologyFilter_GPU(int op, int type, const GpuMat& kernel, const Size& ksize,
Point anchor=Point(-1,-1));
//! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.
CV_EXPORTS Ptr<FilterEngine_GPU> createMorphologyFilter_GPU(int op, int type, const Mat& kernel,
const Point& anchor = Point(-1,-1), int iterations = 1);
//! returns 2D filter with the specified kernel
//! supports CV_8UC1 and CV_8UC4 types
//! kernel must have CV_8UC1 type, one rows and cols == ksize.width * ksize.height
CV_EXPORTS Ptr<BaseFilter_GPU> getLinearFilter_GPU(int srcType, int dstType, const GpuMat& kernel, const Size& ksize,
Point anchor = Point(-1, -1), int nDivisor = 1);
//! returns the non-separable linear filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createLinearFilter_GPU(int srcType, int dstType, const Mat& kernel,
const Point& anchor = Point(-1,-1));
//! returns the primitive row filter with the specified kernel
CV_EXPORTS Ptr<BaseRowFilter_GPU> getLinearRowFilter_GPU(int srcType, int bufType, const GpuMat& rowKernel,
int anchor = -1, int nDivisor = 1);
//! returns the primitive column filter with the specified kernel
CV_EXPORTS Ptr<BaseColumnFilter_GPU> getLinearColumnFilter_GPU(int bufType, int dstType, const GpuMat& columnKernel,
int anchor = -1, int nDivisor = 1);
//! returns the separable linear filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat& rowKernel,
const Mat& columnKernel, const Point& anchor = Point(-1,-1));
//! returns filter engine for the generalized Sobel operator
CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize);
//! returns the Gaussian filter engine
CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0);
//! smooths the image using the normalized box filter
//! supports CV_8UC1, CV_8UC4 types and kernel size 3, 5, 7
CV_EXPORTS void boxFilter(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1));
//! supports CV_8UC1, CV_8UC4 types
CV_EXPORTS void boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor = Point(-1,-1));
//! a synonym for normalized box filter
static inline void blur(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1)) { boxFilter(src, dst, ksize, anchor); }
static inline void blur(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1)) { boxFilter(src, dst, -1, ksize, anchor); }
//! erodes the image (applies the local minimum operator)
CV_EXPORTS void erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations);
CV_EXPORTS void erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
//! dilates the image (applies the local maximum operator)
CV_EXPORTS void dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor, int iterations);
CV_EXPORTS void dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
//! applies an advanced morphological operation to the image
CV_EXPORTS void morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor, int iterations);
CV_EXPORTS void morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1);
//! applies non-separable 2D linear filter to the image
CV_EXPORTS void filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor=Point(-1,-1));
//! 1D mask Window Sum for 8 bit images
CV_EXPORTS void sumWindowColumn(const GpuMat& src, GpuMat& dst, int ksize, int anchor = -1);
CV_EXPORTS void sumWindowRow(const GpuMat& src, GpuMat& dst, int ksize, int anchor = -1);
//! applies separable 2D linear filter to the image
CV_EXPORTS void sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY,
Point anchor = Point(-1,-1));
//! applies generalized Sobel operator to the image
CV_EXPORTS void Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1);
//! applies the vertical or horizontal Scharr operator to the image
CV_EXPORTS void Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, double scale = 1);
//! smooths the image using Gaussian filter.
CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double sigma1, double sigma2 = 0);
//! applies Canny edge detector and produces the edge map.
CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize = 3);
//! applies Laplacian operator to the image
//! supports only ksize = 1 and ksize = 3
CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1);
//////////////////////////////// Image Labeling ////////////////////////////////
......
modules/gpu/src/arithm.cpp
浏览文件 @ 66df8ef0
......@@ -387,6 +387,7 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
Scalar cv::gpu::sum(const GpuMat& src)
{
CV_Assert(!"disabled until fix crash");
CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC4);
NppiSize sz;
......@@ -420,6 +421,7 @@ Scalar cv::gpu::sum(const GpuMat& src)
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal)
{
CV_Assert(!"disabled until fix npp bug");
CV_Assert(src.type() == CV_8UC1);
NppiSize sz;
......
modules/gpu/src/filtering_npp.cpp
浏览文件 @ 66df8ef0
此差异已折叠。
modules/gpu/src/imgproc_gpu.cpp
浏览文件 @ 66df8ef0
......@@ -992,6 +992,7 @@ void cv::gpu::integral(GpuMat& src, GpuMat& sum, GpuMat& sqsum)
void cv::gpu::Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize)
{
CV_Assert(!"disabled until fix crash");
CV_Assert(image.type() == CV_8UC1);
GpuMat srcDx, srcDy;
......
tests/gpu/src/morf_filters.cpp → tests/gpu/src/filters.cpp
浏览文件 @ 66df8ef0
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuNppMorphogyTest : public CvTest
{
public:
CV_GpuNppMorphogyTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuNppMorphogyTest() {}
protected:
void run(int);
virtual int test(const Mat& img) = 0;
int test8UC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int test8UC4(const Mat& img)
{
cv::Mat img_C4;
cvtColor(img, img_C4, CV_BGR2BGRA);
return test(img_C4);
}
int CheckNorm(const Mat& m1, const Mat& m2)
{
double res = norm(m1, m2, NORM_INF);
if (res < std::numeric_limits<double>::epsilon())
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", res);
return CvTS::FAIL_GENERIC;
}
};
void CV_GpuNppMorphogyTest::run( int )
{
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
try
{
//run tests
int testResult = test8UC1(img);
if (testResult != CvTS::OK)
{
ts->set_failed_test_info(testResult);
return;
}
testResult = test8UC4(img);
if (testResult != CvTS::OK)
{
ts->set_failed_test_info(testResult);
return;
}
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(CvTS::OK);
}
////////////////////////////////////////////////////////////////////////////////
// Erode
class CV_GpuErodeTest : public CV_GpuNppMorphogyTest
{
public:
CV_GpuErodeTest() : CV_GpuNppMorphogyTest( "GPU-NppErode", "erode" ) {}
protected:
virtual int test(const Mat& img)
{
GpuMat kernel(Mat::ones(3, 3, CV_8U));
Point anchor(0, 0);
int iters = 1;
cv::Mat cpuRes, cpuRes1;
cv::erode(img, cpuRes, kernel, anchor, iters);
GpuMat gpuRes;
cv::gpu::erode(GpuMat(img), gpuRes, kernel, anchor, iters);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// Dilate
class CV_GpuDilateTest : public CV_GpuNppMorphogyTest
{
public:
CV_GpuDilateTest() : CV_GpuNppMorphogyTest( "GPU-NppDilate", "dilate" ) {}
protected:
virtual int test(const Mat& img)
{
GpuMat kernel(Mat::ones(3, 3, CV_8U));
Point anchor(0, 0);
int iters = 1;
cv::Mat cpuRes, cpuRes1;
cv::dilate(img, cpuRes, kernel, anchor, iters);
GpuMat gpuRes, gpuRes1;
cv::gpu::dilate(GpuMat(img), gpuRes, kernel, anchor, iters);
return CheckNorm(cpuRes, gpuRes);
}
};
////////////////////////////////////////////////////////////////////////////////
// Dilate
class CV_GpuMorphExTest : public CV_GpuNppMorphogyTest
{
public:
CV_GpuMorphExTest() : CV_GpuNppMorphogyTest( "GPU-NppMorphologyEx", "dmorphologyExilate" ) {}
protected:
virtual int test(const Mat& img)
{
static int ops[] = { MORPH_OPEN, CV_MOP_CLOSE, CV_MOP_GRADIENT, CV_MOP_TOPHAT, CV_MOP_BLACKHAT};
const char *names[] = { "MORPH_OPEN", "CV_MOP_CLOSE", "CV_MOP_GRADIENT", "CV_MOP_TOPHAT", "CV_MOP_BLACKHAT"};
int num = sizeof(ops)/sizeof(ops[0]);
GpuMat kernel(Mat::ones(3, 3, CV_8U));
Point anchor(0, 0);
int iters = 1;
for(int i = 0; i < num; ++i)
{
ts->printf(CvTS::LOG, "Tesing %s\n", names[i]);
cv::Mat cpuRes;
cv::morphologyEx(img, cpuRes, ops[i], kernel, anchor, iters);
GpuMat gpuRes;
cv::gpu::morphologyEx(GpuMat(img), gpuRes, ops[i], kernel, anchor, iters);
int res = CheckNorm(cpuRes, gpuRes);
if (CvTS::OK != res)
return res;
}
return CvTS::OK;
}
};
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
CV_GpuErodeTest CV_GpuErode_test;
CV_GpuDilateTest CV_GpuDilate_test;
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
#include <cmath>
#include <limits>
#include "gputest.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuNppFilterTest : public CvTest
{
public:
CV_GpuNppFilterTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
virtual ~CV_GpuNppFilterTest() {}
protected:
void run(int);
virtual int test(const Mat& img) = 0;
int test8UC1(const Mat& img)
{
cv::Mat img_C1;
cvtColor(img, img_C1, CV_BGR2GRAY);
return test(img_C1);
}
int test8UC4(const Mat& img)
{
cv::Mat img_C4;
cvtColor(img, img_C4, CV_BGR2BGRA);
return test(img_C4);
}
int CheckNorm(const Mat& m1, const Mat& m2, const Size& ksize)
{
Rect roi = Rect(ksize.width, ksize.height, m1.cols - 2 * ksize.width, m1.rows - 2 * ksize.height);
Mat m1ROI = m1(roi);
Mat m2ROI = m2(roi);
double res = norm(m1ROI, m2ROI, NORM_INF);
if (res <= 1)
return CvTS::OK;
ts->printf(CvTS::LOG, "\nNorm: %f\n", res);
return CvTS::FAIL_GENERIC;
}
};
void CV_GpuNppFilterTest::run( int )
{
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
if (img.empty())
{
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
return;
}
try
{
//run tests
int testResult = CvTS::OK;
if (test8UC1(img) != CvTS::OK)
testResult = CvTS::FAIL_GENERIC;
if (test8UC4(img) != CvTS::OK)
testResult = CvTS::FAIL_GENERIC;
ts->set_failed_test_info(testResult);
}
catch(const cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
ts->set_failed_test_info(CvTS::OK);
}
////////////////////////////////////////////////////////////////////////////////
// blur
struct CV_GpuNppImageBlurTest : public CV_GpuNppFilterTest
{
CV_GpuNppImageBlurTest() : CV_GpuNppFilterTest( "GPU-NppImageBlur", "blur" ) {}
int test(const Mat& img)
{
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
for (int j = 0; j < ksizes_num; ++j)
{
Size ksize(ksizes[i], ksizes[j]);
ts->printf(CvTS::LOG, "\nksize = (%dx%d)\n", ksizes[i], ksizes[j]);
Mat cpudst;
cv::blur(img, cpudst, ksize);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::blur(gpu1, gpudst, ksize);
if (CheckNorm(cpudst, gpudst, ksize) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Sobel
struct CV_GpuNppImageSobelTest : public CV_GpuNppFilterTest
{
CV_GpuNppImageSobelTest() : CV_GpuNppFilterTest( "GPU-NppImageSobel", "Sobel" ) {}
int test(const Mat& img)
{
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int dx = 1, dy = 0;
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::Sobel(img, cpudst, -1, dx, dy, ksizes[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::Sobel(gpu1, gpudst, -1, dx, dy, ksizes[i]);
if (CheckNorm(cpudst, gpudst, Size(ksizes[i], ksizes[i])) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Scharr
struct CV_GpuNppImageScharrTest : public CV_GpuNppFilterTest
{
CV_GpuNppImageScharrTest() : CV_GpuNppFilterTest( "GPU-NppImageScharr", "Scharr" ) {}
int test(const Mat& img)
{
int dx = 1, dy = 0;
Mat cpudst;
cv::Scharr(img, cpudst, -1, dx, dy);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::Scharr(gpu1, gpudst, -1, dx, dy);
return CheckNorm(cpudst, gpudst, Size(3, 3));
}
};
////////////////////////////////////////////////////////////////////////////////
// GaussianBlur
struct CV_GpuNppImageGaussianBlurTest : public CV_GpuNppFilterTest
{
CV_GpuNppImageGaussianBlurTest() : CV_GpuNppFilterTest( "GPU-NppImageGaussianBlur", "GaussianBlur" ) {}
int test(const Mat& img)
{
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
const double sigma1 = 3.0;
for (int i = 0; i < ksizes_num; ++i)
{
for (int j = 0; j < ksizes_num; ++j)
{
cv::Size ksize(ksizes[i], ksizes[j]);
ts->printf(CvTS::LOG, "\nksize = (%dx%d)\n", ksizes[i], ksizes[j]);
Mat cpudst;
cv::GaussianBlur(img, cpudst, ksize, sigma1);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::GaussianBlur(gpu1, gpudst, ksize, sigma1);
if (CheckNorm(cpudst, gpudst, ksize) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Laplacian
struct CV_GpuNppImageLaplacianTest : public CV_GpuNppFilterTest
{
CV_GpuNppImageLaplacianTest() : CV_GpuNppFilterTest( "GPU-NppImageLaplacian", "Laplacian" ) {}
int test(const Mat& img)
{
int ksizes[] = {1, 3};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::Laplacian(img, cpudst, -1, ksizes[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::Laplacian(gpu1, gpudst, -1, ksizes[i]);
if (CheckNorm(cpudst, gpudst, Size(3, 3)) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Erode
class CV_GpuErodeTest : public CV_GpuNppFilterTest
{
public:
CV_GpuErodeTest() : CV_GpuNppFilterTest( "GPU-NppErode", "erode" ) {}
protected:
virtual int test(const Mat& img)
{
Mat kernel(Mat::ones(3, 3, CV_8U));
cv::Mat cpuRes;
cv::erode(img, cpuRes, kernel);
GpuMat gpuRes;
cv::gpu::erode(GpuMat(img), gpuRes, kernel);
return CheckNorm(cpuRes, gpuRes, Size(3, 3));
}
};
////////////////////////////////////////////////////////////////////////////////
// Dilate
class CV_GpuDilateTest : public CV_GpuNppFilterTest
{
public:
CV_GpuDilateTest() : CV_GpuNppFilterTest( "GPU-NppDilate", "dilate" ) {}
protected:
virtual int test(const Mat& img)
{
Mat kernel(Mat::ones(3, 3, CV_8U));
cv::Mat cpuRes;
cv::dilate(img, cpuRes, kernel);
GpuMat gpuRes;
cv::gpu::dilate(GpuMat(img), gpuRes, kernel);
return CheckNorm(cpuRes, gpuRes, Size(3, 3));
}
};
////////////////////////////////////////////////////////////////////////////////
// MorphologyEx
class CV_GpuMorphExTest : public CV_GpuNppFilterTest
{
public:
CV_GpuMorphExTest() : CV_GpuNppFilterTest( "GPU-NppMorphologyEx", "morphologyEx" ) {}
protected:
virtual int test(const Mat& img)
{
static int ops[] = { MORPH_OPEN, CV_MOP_CLOSE, CV_MOP_GRADIENT, CV_MOP_TOPHAT, CV_MOP_BLACKHAT};
const char *names[] = { "MORPH_OPEN", "CV_MOP_CLOSE", "CV_MOP_GRADIENT", "CV_MOP_TOPHAT", "CV_MOP_BLACKHAT"};
int num = sizeof(ops)/sizeof(ops[0]);
GpuMat kernel(Mat::ones(3, 3, CV_8U));
int res = CvTS::OK;
for(int i = 0; i < num; ++i)
{
ts->printf(CvTS::LOG, "Tesing %s\n", names[i]);
cv::Mat cpuRes;
cv::morphologyEx(img, cpuRes, ops[i], kernel);
GpuMat gpuRes;
cv::gpu::morphologyEx(GpuMat(img), gpuRes, ops[i], kernel);
if (CvTS::OK != CheckNorm(cpuRes, gpuRes, Size(3, 3)))
res = CvTS::FAIL_GENERIC;
}
return res;
}
};
/////////////////////////////////////////////////////////////////////////////
/////////////////// tests registration /////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////
CV_GpuNppImageBlurTest CV_GpuNppImageBlur_test;
CV_GpuNppImageSobelTest CV_GpuNppImageSobel_test;
CV_GpuNppImageScharrTest CV_GpuNppImageScharr_test;
CV_GpuNppImageGaussianBlurTest CV_GpuNppImageGaussianBlur_test;
CV_GpuNppImageLaplacianTest CV_GpuNppImageLaplacian_test;
CV_GpuErodeTest CV_GpuErode_test;
CV_GpuDilateTest CV_GpuDilate_test;
CV_GpuMorphExTest CV_GpuMorphEx_test;
\ No newline at end of file
tests/gpu/src/gputest_main.cpp
浏览文件 @ 66df8ef0
......@@ -45,25 +45,27 @@ CvTS test_system;
const char* blacklist[] =
{
"GPU-NppImageSum", // crash
"GPU-MatOperatorAsyncCall", // crash
//"GPU-NppErode", // different border interpolation
//"GPU-NppMorphologyEx", // different border interpolation
"GPU-NppImageSum", // crash, probably npp bug
"GPU-NppImageMinNax", // npp bug - don't find min/max near right border
//"GPU-NppImageDivide", // different round mode
//"GPU-NppImageMeanStdDev", // different precision
//"GPU-NppImageMinNax", // npp bug - don't find min/max near right border
//"GPU-NppImageResize", // different precision in interpolation
//"GPU-NppImageWarpAffine", // different precision in interpolation
//"GPU-NppImageWarpPerspective", // different precision in interpolation
//"GPU-NppImageIntegral", // different precision
//"GPU-NppImageBlur", // different precision
//"GPU-NppImageExp", // different precision
//"GPU-NppImageLog", // different precision
//"GPU-NppImageMagnitude", // different precision
//"GPU-NppImageSumWindow", // different border interpolation
//"GPU-NppImageSobel", // ???
//"GPU-NppImageGaussianBlur", // different border interpolation
"GPU-NppImageCanny", // NPP_TEXTURE_BIND_ERROR
//"GPU-NppImageResize", // different precision
//"GPU-NppImageWarpAffine", // different precision
//"GPU-NppImageWarpPerspective", // different precision
//"GPU-NppImageIntegral", // different precision
//"GPU-NppImageSobel", // ???
//"GPU-NppImageScharr", // ???
//"GPU-NppImageGaussianBlur", // different precision
//"GPU-NppMorphologyEx", // different precision?
0
};
......
tests/gpu/src/imgproc_gpu.cpp
浏览文件 @ 66df8ef0
......@@ -413,167 +413,6 @@ struct CV_GpuNppImageIntegralTest : public CV_GpuImageProcTest
}
};
////////////////////////////////////////////////////////////////////////////////
// blur
struct CV_GpuNppImageBlurTest : public CV_GpuImageProcTest
{
CV_GpuNppImageBlurTest() : CV_GpuImageProcTest( "GPU-NppImageBlur", "blur" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::blur(img, cpudst, Size(ksizes[i], ksizes[i]));
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::blur(gpu1, gpudst, Size(ksizes[i], ksizes[i]));
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// sumWindow
struct CV_GpuNppImageSumWindowTest : public CV_GpuImageProcTest
{
CV_GpuNppImageSumWindowTest() : CV_GpuImageProcTest( "GPU-NppImageSumWindow", "sumWindow" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst(img.size(), CV_64FC1, Scalar());
cv::Ptr<cv::BaseRowFilter> ft = cv::getRowSumFilter(CV_8UC1, CV_64FC1, ksizes[i], 0);
for (int y = 0; y < img.rows; ++y)
(*ft)(img.ptr(y), cpudst.ptr(y), img.cols, 1);
cpudst.convertTo(cpudst, CV_32F);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::sumWindowRow(gpu1, gpudst, ksizes[i], 0);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Sobel
struct CV_GpuNppImageSobelTest : public CV_GpuImageProcTest
{
CV_GpuNppImageSobelTest() : CV_GpuImageProcTest( "GPU-NppImageSobel", "Sobel" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int dx = 1, dy = 0;
int test_res = CvTS::OK;
for (int i = 0; i < ksizes_num; ++i)
{
ts->printf(CvTS::LOG, "\nksize = %d\n", ksizes[i]);
Mat cpudst;
cv::Sobel(img, cpudst, -1, dx, dy, ksizes[i]);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::Sobel(gpu1, gpudst, -1, dx, dy, ksizes[i]);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// GaussianBlur
struct CV_GpuNppImageGaussianBlurTest : public CV_GpuImageProcTest
{
CV_GpuNppImageGaussianBlurTest() : CV_GpuImageProcTest( "GPU-NppImageGaussianBlur", "GaussianBlur" ) {}
int test(const Mat& img)
{
if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
{
ts->printf(CvTS::LOG, "\nUnsupported type\n");
return CvTS::OK;
}
int ksizes[] = {3, 5, 7};
int ksizes_num = sizeof(ksizes) / sizeof(int);
int test_res = CvTS::OK;
const double sigma1 = 3.0;
for (int i = 0; i < ksizes_num; ++i)
{
for (int j = 0; j < ksizes_num; ++j)
{
ts->printf(CvTS::LOG, "\nksize = (%dx%d)\n", ksizes[i], ksizes[j]);
Mat cpudst;
cv::GaussianBlur(img, cpudst, cv::Size(ksizes[i], ksizes[j]), sigma1);
GpuMat gpu1(img);
GpuMat gpudst;
cv::gpu::GaussianBlur(gpu1, gpudst, cv::Size(ksizes[i], ksizes[j]), sigma1);
if (CheckNorm(cpudst, gpudst) != CvTS::OK)
test_res = CvTS::FAIL_GENERIC;
}
}
return test_res;
}
};
////////////////////////////////////////////////////////////////////////////////
// Canny
struct CV_GpuNppImageCannyTest : public CV_GpuImageProcTest
......@@ -705,9 +544,5 @@ CV_GpuNppImageCopyMakeBorderTest CV_GpuNppImageCopyMakeBorder_test;
CV_GpuNppImageWarpAffineTest CV_GpuNppImageWarpAffine_test;
CV_GpuNppImageWarpPerspectiveTest CV_GpuNppImageWarpPerspective_test;
CV_GpuNppImageIntegralTest CV_GpuNppImageIntegral_test;
CV_GpuNppImageBlurTest CV_GpuNppImageBlur_test;
CV_GpuNppImageSumWindowTest CV_GpuNppImageSumWindow_test;
CV_GpuNppImageSobelTest CV_GpuNppImageSobel_test;
CV_GpuNppImageGaussianBlurTest CV_GpuNppImageGaussianBlur_test;
CV_GpuNppImageCannyTest CV_GpuNppImageCanny_test;
CV_GpuCvtColorTest CV_GpuCvtColor_test;
\ No newline at end of file
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