//
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Jia Haipeng, jiahaipeng95@gmail.com
// Zero Lin, Zero.Lin@amd.com
// Zhang Ying, zhangying913@gmail.com
+// Yao Wang, bitwangyaoyao@gmail.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//M*/
-#include "precomp.hpp"
+#include "test_precomp.hpp"
#ifdef HAVE_OPENCL
using namespace std;
-PARAM_TEST_CASE(FilterTestBase, MatType, bool)
+PARAM_TEST_CASE(FilterTestBase,
+ MatType,
+ cv::Size, // kernel size
+ cv::Size, // dx,dy
+ int // border type, or iteration
+ )
{
- int type;
- cv::Scalar val;
-
//src mat
cv::Mat mat1;
- cv::Mat mat2;
- cv::Mat mask;
cv::Mat dst;
- cv::Mat dst1; //bak, for two outputs
// set up roi
int roicols;
int roirows;
int src1x;
int src1y;
- int src2x;
- int src2y;
int dstx;
int dsty;
- int maskx;
- int masky;
//src mat with roi
cv::Mat mat1_roi;
- cv::Mat mat2_roi;
- cv::Mat mask_roi;
cv::Mat dst_roi;
- cv::Mat dst1_roi; //bak
- //std::vector<cv::ocl::Info> oclinfo;
+
//ocl dst mat for testing
cv::ocl::oclMat gdst_whole;
- cv::ocl::oclMat gdst1_whole; //bak
//ocl mat with roi
cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gmat2;
cv::ocl::oclMat gdst;
- cv::ocl::oclMat gdst1; //bak
- cv::ocl::oclMat gmask;
-
- virtual void SetUp()
- {
- type = GET_PARAM(0);
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- mat2 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
- dst1 = randomMat(rng, size, type, 5, 16, false);
- mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
-
- cv::threshold(mask, mask, 0.5, 255., CV_8UC1);
-
- val = cv::Scalar(rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0));
- }
void random_roi()
{
#ifdef RANDOMROI
//randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(1, mat1.cols);
- roirows = rng.uniform(1, mat1.rows);
+ roicols = rng.uniform(2, mat1.cols);
+ roirows = rng.uniform(2, mat1.rows);
src1x = rng.uniform(0, mat1.cols - roicols);
src1y = rng.uniform(0, mat1.rows - roirows);
- src2x = rng.uniform(0, mat2.cols - roicols);
- src2y = rng.uniform(0, mat2.rows - roirows);
dstx = rng.uniform(0, dst.cols - roicols);
dsty = rng.uniform(0, dst.rows - roirows);
- maskx = rng.uniform(0, mask.cols - roicols);
- masky = rng.uniform(0, mask.rows - roirows);
#else
roicols = mat1.cols;
roirows = mat1.rows;
src1x = 0;
src1y = 0;
- src2x = 0;
- src2y = 0;
dstx = 0;
dsty = 0;
- maskx = 0;
- masky = 0;
#endif
+
mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- mat2_roi = mat2(Rect(src2x, src2y, roicols, roirows));
- mask_roi = mask(Rect(maskx, masky, roicols, roirows));
dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
- dst1_roi = dst1(Rect(dstx, dsty, roicols, roirows));
gdst_whole = dst;
gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
- gdst1_whole = dst1;
- gdst1 = gdst1_whole(Rect(dstx, dsty, roicols, roirows));
-
gmat1 = mat1_roi;
- gmat2 = mat2_roi;
- gmask = mask_roi;
}
+ void Init(int mat_type)
+ {
+ cv::Size size(MWIDTH, MHEIGHT);
+ mat1 = randomMat(size, mat_type, 5, 16);
+ dst = randomMat(size, mat_type, 5, 16);
+ }
+
+ void Near(double threshold)
+ {
+ EXPECT_MAT_NEAR(dst, Mat(gdst_whole), threshold);
+ }
};
/////////////////////////////////////////////////////////////////////////////////////////////////
// blur
-
-PARAM_TEST_CASE(Blur, MatType, cv::Size, int)
+struct Blur : FilterTestBase
{
int type;
cv::Size ksize;
int bordertype;
- //src mat
- cv::Mat mat1;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int src1x;
- int src1y;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat1_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gdst;
-
virtual void SetUp()
{
type = GET_PARAM(0);
ksize = GET_PARAM(1);
- bordertype = GET_PARAM(2);
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
- //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
- //CV_Assert(devnums > 0);
- ////if you want to use undefault device, set it here
- ////setDevice(oclinfo[0]);
- }
-
- void random_roi()
- {
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat1.cols);
- roirows = rng.uniform(2, mat1.rows);
- src1x = rng.uniform(0, mat1.cols - roicols);
- src1y = rng.uniform(0, mat1.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat1.cols;
- roirows = mat1.rows;
- src1x = 0;
- src1y = 0;
- dstx = 0;
- dsty = 0;
-#endif
-
- mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
-
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
-
-
- gmat1 = mat1_roi;
+ bordertype = GET_PARAM(3);
+ Init(type);
}
-
};
-TEST_P(Blur, Mat)
+OCL_TEST_P(Blur, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
-
cv::blur(mat1_roi, dst_roi, ksize, Point(-1, -1), bordertype);
cv::ocl::blur(gmat1, gdst, ksize, Point(-1, -1), bordertype);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
- EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
+ Near(1.0);
}
-
}
-
/////////////////////////////////////////////////////////////////////////////////////////////////
//Laplacian
-
-PARAM_TEST_CASE(LaplacianTestBase, MatType, int)
+struct Laplacian : FilterTestBase
{
int type;
- int ksize;
-
- //src mat
- cv::Mat mat;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int srcx;
- int srcy;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat;
- cv::ocl::oclMat gdst;
+ cv::Size ksize;
virtual void SetUp()
{
type = GET_PARAM(0);
ksize = GET_PARAM(1);
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
-
- //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
- //CV_Assert(devnums > 0);
- ////if you want to use undefault device, set it here
- ////setDevice(oclinfo[0]);
- }
-
- void random_roi()
- {
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat.cols);
- roirows = rng.uniform(2, mat.rows);
- srcx = rng.uniform(0, mat.cols - roicols);
- srcy = rng.uniform(0, mat.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat.cols;
- roirows = mat.rows;
- srcx = 0;
- srcy = 0;
- dstx = 0;
- dsty = 0;
-#endif
-
- mat_roi = mat(Rect(srcx, srcy, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
-
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
-
- gmat = mat_roi;
+ Init(type);
}
};
-struct Laplacian : LaplacianTestBase {};
-
-TEST_P(Laplacian, Accuracy)
+OCL_TEST_P(Laplacian, Accuracy)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
-
- cv::Laplacian(mat_roi, dst_roi, -1, ksize, 1);
- cv::ocl::Laplacian(gmat, gdst, -1, ksize, 1);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, srcx, srcy, dstx, dsty);
-
- EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, sss);
+ cv::Laplacian(mat1_roi, dst_roi, -1, ksize.width, 1);
+ cv::ocl::Laplacian(gmat1, gdst, -1, ksize.width, 1);
+ Near(1e-5);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// erode & dilate
-
-PARAM_TEST_CASE(ErodeDilateBase, MatType, int)
+struct ErodeDilate : FilterTestBase
{
int type;
int iterations;
//erode or dilate kernel
cv::Mat kernel;
- //src mat
- cv::Mat mat1;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int src1x;
- int src1y;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat1_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gdst;
-
virtual void SetUp()
{
type = GET_PARAM(0);
- iterations = GET_PARAM(1);
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
- // rng.fill(kernel, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(3));
- kernel = randomMat(rng, Size(3, 3), CV_8UC1, 0, 3, false);
-
- }
-
- void random_roi()
- {
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat1.cols);
- roirows = rng.uniform(2, mat1.rows);
- src1x = rng.uniform(0, mat1.cols - roicols);
- src1y = rng.uniform(0, mat1.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat1.cols;
- roirows = mat1.rows;
- src1x = 0;
- src1y = 0;
- dstx = 0;
- dsty = 0;
-#endif
-
- mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
-
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
-
-
- gmat1 = mat1_roi;
+ iterations = GET_PARAM(3);
+ Init(type);
+ kernel = randomMat(Size(3, 3), CV_8UC1, 0, 3);
}
};
-// erode
-
-struct Erode : ErodeDilateBase {};
-
-TEST_P(Erode, Mat)
+OCL_TEST_P(ErodeDilate, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
-
cv::erode(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations);
cv::ocl::erode(gmat1, gdst, kernel, Point(-1, -1), iterations);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
-
- EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, sss);
+ Near(1e-5);
}
-
-}
-
-
-
-
-
-// dilate
-
-struct Dilate : ErodeDilateBase {};
-
-TEST_P(Dilate, Mat)
-{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
- cv::erode(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations);
- cv::ocl::erode(gmat1, gdst, kernel, Point(-1, -1), iterations);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
-
- EXPECT_MAT_NEAR(dst, cpu_dst, 1e-5, sss);
+ cv::dilate(mat1_roi, dst_roi, kernel, Point(-1, -1), iterations);
+ cv::ocl::dilate(gmat1, gdst, kernel, Point(-1, -1), iterations);
+ Near(1e-5);
}
-
}
-
-
/////////////////////////////////////////////////////////////////////////////////////////////////
// Sobel
-
-PARAM_TEST_CASE(Sobel, MatType, int, int, int, int)
+struct Sobel : FilterTestBase
{
int type;
int dx, dy, ksize, bordertype;
- //src mat
- cv::Mat mat1;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int src1x;
- int src1y;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat1_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gdst;
-
virtual void SetUp()
{
type = GET_PARAM(0);
- dx = GET_PARAM(1);
- dy = GET_PARAM(2);
- ksize = GET_PARAM(3);
- bordertype = GET_PARAM(4);
-
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
-
- //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
- //CV_Assert(devnums > 0);
- ////if you want to use undefault device, set it here
- ////setDevice(oclinfo[0]);
- }
-
- void random_roi()
- {
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat1.cols);
- roirows = rng.uniform(2, mat1.rows);
- src1x = rng.uniform(0, mat1.cols - roicols);
- src1y = rng.uniform(0, mat1.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat1.cols;
- roirows = mat1.rows;
- src1x = 0;
- src1y = 0;
- dstx = 0;
- dsty = 0;
-#endif
-
- mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
-
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
-
-
- gmat1 = mat1_roi;
+ Size s = GET_PARAM(1);
+ ksize = s.width;
+ s = GET_PARAM(2);
+ dx = s.width;
+ dy = s.height;
+ bordertype = GET_PARAM(3);
+ Init(type);
}
-
};
-TEST_P(Sobel, Mat)
+OCL_TEST_P(Sobel, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
-
cv::Sobel(mat1_roi, dst_roi, -1, dx, dy, ksize, /*scale*/0.00001,/*delta*/0, bordertype);
cv::ocl::Sobel(gmat1, gdst, -1, dx, dy, ksize,/*scale*/0.00001,/*delta*/0, bordertype);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
-
- EXPECT_MAT_NEAR(dst, cpu_dst, 1, sss);
+ Near(1);
}
-
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// Scharr
-
-PARAM_TEST_CASE(Scharr, MatType, int, int, int)
+struct Scharr : FilterTestBase
{
int type;
int dx, dy, bordertype;
- //src mat
- cv::Mat mat1;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int src1x;
- int src1y;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat1_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gdst;
-
virtual void SetUp()
{
type = GET_PARAM(0);
- dx = GET_PARAM(1);
- dy = GET_PARAM(2);
+ Size s = GET_PARAM(2);
+ dx = s.width;
+ dy = s.height;
bordertype = GET_PARAM(3);
- dx = 1;
- dy = 0;
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
-
- //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
- //CV_Assert(devnums > 0);
- ////if you want to use undefault device, set it here
- ////setDevice(oclinfo[0]);
+ Init(type);
}
-
- void random_roi()
- {
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat1.cols);
- roirows = rng.uniform(2, mat1.rows);
- src1x = rng.uniform(0, mat1.cols - roicols);
- src1y = rng.uniform(0, mat1.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat1.cols;
- roirows = mat1.rows;
- src1x = 0;
- src1y = 0;
- dstx = 0;
- dsty = 0;
-#endif
-
- mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
-
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
-
-
- gmat1 = mat1_roi;
- }
-
};
-TEST_P(Scharr, Mat)
+OCL_TEST_P(Scharr, Mat)
{
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
-
cv::Scharr(mat1_roi, dst_roi, -1, dx, dy, /*scale*/1,/*delta*/0, bordertype);
cv::ocl::Scharr(gmat1, gdst, -1, dx, dy,/*scale*/1,/*delta*/0, bordertype);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
-
- EXPECT_MAT_NEAR(dst, cpu_dst, 1, sss);
+ Near(1);
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// GaussianBlur
-
-PARAM_TEST_CASE(GaussianBlur, MatType, cv::Size, int)
+struct GaussianBlur : FilterTestBase
{
int type;
cv::Size ksize;
int bordertype;
-
double sigma1, sigma2;
- //src mat
- cv::Mat mat1;
- cv::Mat dst;
-
- // set up roi
- int roicols;
- int roirows;
- int src1x;
- int src1y;
- int dstx;
- int dsty;
-
- //src mat with roi
- cv::Mat mat1_roi;
- cv::Mat dst_roi;
- //std::vector<cv::ocl::Info> oclinfo;
- //ocl dst mat for testing
- cv::ocl::oclMat gdst_whole;
-
- //ocl mat with roi
- cv::ocl::oclMat gmat1;
- cv::ocl::oclMat gdst;
-
virtual void SetUp()
{
type = GET_PARAM(0);
ksize = GET_PARAM(1);
- bordertype = GET_PARAM(2);
-
- cv::RNG &rng = TS::ptr()->get_rng();
- cv::Size size(MWIDTH, MHEIGHT);
-
+ bordertype = GET_PARAM(3);
+ Init(type);
sigma1 = rng.uniform(0.1, 1.0);
sigma2 = rng.uniform(0.1, 1.0);
-
- mat1 = randomMat(rng, size, type, 5, 16, false);
- dst = randomMat(rng, size, type, 5, 16, false);
-
- //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
- //CV_Assert(devnums > 0);
- ////if you want to use undefault device, set it here
- ////setDevice(oclinfo[0]);
}
+};
- void random_roi()
+OCL_TEST_P(GaussianBlur, Mat)
+{
+ for(int j = 0; j < LOOP_TIMES; j++)
{
-#ifdef RANDOMROI
- //randomize ROI
- cv::RNG &rng = TS::ptr()->get_rng();
- roicols = rng.uniform(2, mat1.cols);
- roirows = rng.uniform(2, mat1.rows);
- src1x = rng.uniform(0, mat1.cols - roicols);
- src1y = rng.uniform(0, mat1.rows - roirows);
- dstx = rng.uniform(0, dst.cols - roicols);
- dsty = rng.uniform(0, dst.rows - roirows);
-#else
- roicols = mat1.cols;
- roirows = mat1.rows;
- src1x = 0;
- src1y = 0;
- dstx = 0;
- dsty = 0;
-#endif
+ random_roi();
+ cv::GaussianBlur(mat1_roi, dst_roi, ksize, sigma1, sigma2, bordertype);
+ cv::ocl::GaussianBlur(gmat1, gdst, ksize, sigma1, sigma2, bordertype);
+ Near(1);
+ }
- mat1_roi = mat1(Rect(src1x, src1y, roicols, roirows));
- dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
+}
- gdst_whole = dst;
- gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
- gmat1 = mat1_roi;
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// Filter2D
+struct Filter2D : FilterTestBase
+{
+ int type;
+ cv::Size ksize;
+ int bordertype;
+ Point anchor;
+ virtual void SetUp()
+ {
+ type = GET_PARAM(0);
+ ksize = GET_PARAM(1);
+ bordertype = GET_PARAM(3);
+ Init(type);
+ anchor = Point(-1,-1);
}
-
};
-TEST_P(GaussianBlur, Mat)
+OCL_TEST_P(Filter2D, Mat)
{
+ cv::Mat kernel = randomMat(cv::Size(ksize.width, ksize.height), CV_32FC1, 0.0, 1.0);
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
+ cv::filter2D(mat1_roi, dst_roi, -1, kernel, anchor, 0.0, bordertype);
+ cv::ocl::filter2D(gmat1, gdst, -1, kernel, anchor, bordertype);
+ Near(1);
+ }
+}
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// Bilateral
+struct Bilateral : FilterTestBase
+{
+ int type;
+ cv::Size ksize;
+ int bordertype;
+ double sigmacolor, sigmaspace;
- cv::GaussianBlur(mat1_roi, dst_roi, ksize, sigma1, sigma2, bordertype);
- cv::ocl::GaussianBlur(gmat1, gdst, ksize, sigma1, sigma2, bordertype);
-
- cv::Mat cpu_dst;
- gdst_whole.download(cpu_dst);
- char sss[1024];
- sprintf(sss, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d", roicols, roirows, src1x, src1y, dstx, dsty);
+ virtual void SetUp()
+ {
+ type = GET_PARAM(0);
+ ksize = GET_PARAM(1);
+ bordertype = GET_PARAM(3);
+ Init(type);
+ sigmacolor = rng.uniform(20, 100);
+ sigmaspace = rng.uniform(10, 40);
+ }
+};
- EXPECT_MAT_NEAR(dst, cpu_dst, 1.0, sss);
+OCL_TEST_P(Bilateral, Mat)
+{
+ for(int j = 0; j < LOOP_TIMES; j++)
+ {
+ random_roi();
+ cv::bilateralFilter(mat1_roi, dst_roi, ksize.width, sigmacolor, sigmaspace, bordertype);
+ cv::ocl::bilateralFilter(gmat1, gdst, ksize.width, sigmacolor, sigmaspace, bordertype);
+ Near(1);
}
}
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// AdaptiveBilateral
+struct AdaptiveBilateral : FilterTestBase
+{
+ int type;
+ cv::Size ksize;
+ int bordertype;
+ Point anchor;
+ virtual void SetUp()
+ {
+ type = GET_PARAM(0);
+ ksize = GET_PARAM(1);
+ bordertype = GET_PARAM(3);
+ Init(type);
+ anchor = Point(-1,-1);
+ }
+};
+OCL_TEST_P(AdaptiveBilateral, Mat)
+{
+ for(int j = 0; j < LOOP_TIMES; j++)
+ {
+ random_roi();
+ cv::adaptiveBilateralFilter(mat1_roi, dst_roi, ksize, 5, anchor, bordertype);
+ cv::ocl::adaptiveBilateralFilter(gmat1, gdst, ksize, 5, anchor, bordertype);
+ Near(1);
+ }
+
+}
-INSTANTIATE_TEST_CASE_P(Filter, Blur, Combine(Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
+INSTANTIATE_TEST_CASE_P(Filter, Blur, Combine(
+ Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
Values(cv::Size(3, 3), cv::Size(5, 5), cv::Size(7, 7)),
+ Values(Size(0, 0)), //not use
Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE, (MatType)cv::BORDER_REFLECT, (MatType)cv::BORDER_REFLECT_101)));
-INSTANTIATE_TEST_CASE_P(Filters, Laplacian, Combine(
- Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
- Values(1, 3)));
+INSTANTIATE_TEST_CASE_P(Filter, Laplacian, Combine(
+ Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
+ Values(Size(3, 3)),
+ Values(Size(0, 0)), //not use
+ Values(0))); //not use
-INSTANTIATE_TEST_CASE_P(Filter, Erode, Combine(Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(1)));
+INSTANTIATE_TEST_CASE_P(Filter, ErodeDilate, Combine(
+ Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4),
+ Values(Size(0, 0)), //not use
+ Values(Size(0, 0)), //not use
+ Values(1)));
-//INSTANTIATE_TEST_CASE_P(Filter, Erode, Combine(Values(CV_8UC1, CV_8UC1), Values(false)));
-INSTANTIATE_TEST_CASE_P(Filter, Dilate, Combine(Values(CV_8UC1, CV_8UC4, CV_32FC1, CV_32FC4), Values(1)));
-
-//INSTANTIATE_TEST_CASE_P(Filter, Dilate, Combine(Values(CV_8UC1, CV_8UC1), Values(false)));
-
-
-INSTANTIATE_TEST_CASE_P(Filter, Sobel, Combine(Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
- Values(1, 2), Values(0, 1), Values(3, 5), Values((MatType)cv::BORDER_CONSTANT,
- (MatType)cv::BORDER_REPLICATE)));
+INSTANTIATE_TEST_CASE_P(Filter, Sobel, Combine(
+ Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
+ Values(Size(3, 3), Size(5, 5)),
+ Values(Size(1, 0), Size(1, 1), Size(2, 0), Size(2, 1)),
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE)));
INSTANTIATE_TEST_CASE_P(Filter, Scharr, Combine(
- Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4), Values(0, 1), Values(0, 1),
- Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE)));
+ Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
+ Values(Size(0, 0)), //not use
+ Values(Size(0, 1), Size(1, 0)),
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE)));
INSTANTIATE_TEST_CASE_P(Filter, GaussianBlur, Combine(
- Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
- Values(cv::Size(3, 3), cv::Size(5, 5)),
- Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE)));
-
-
-
+ Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
+ Values(Size(3, 3), Size(5, 5)),
+ Values(Size(0, 0)), //not use
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE)));
+
+
+
+INSTANTIATE_TEST_CASE_P(Filter, Filter2D, testing::Combine(
+ Values(CV_8UC1, CV_32FC1, CV_32FC4),
+ Values(Size(3, 3), Size(15, 15), Size(25, 25)),
+ Values(Size(0, 0)), //not use
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REFLECT101, (MatType)cv::BORDER_REPLICATE, (MatType)cv::BORDER_REFLECT)));
+
+INSTANTIATE_TEST_CASE_P(Filter, Bilateral, Combine(
+ Values(CV_8UC1, CV_8UC3),
+ Values(Size(5, 5), Size(9, 9)),
+ Values(Size(0, 0)), //not use
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE,
+ (MatType)cv::BORDER_REFLECT, (MatType)cv::BORDER_WRAP, (MatType)cv::BORDER_REFLECT_101)));
+
+INSTANTIATE_TEST_CASE_P(Filter, AdaptiveBilateral, Combine(
+ Values(CV_8UC1, CV_8UC3),
+ Values(Size(5, 5), Size(9, 9)),
+ Values(Size(0, 0)), //not use
+ Values((MatType)cv::BORDER_CONSTANT, (MatType)cv::BORDER_REPLICATE,
+ (MatType)cv::BORDER_REFLECT, (MatType)cv::BORDER_REFLECT_101)));
#endif // HAVE_OPENCL
projects / profile / ivi / opencv.git / blobdiff