generic-library/opencv
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remove redundant OPENCL_DIR flag

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remove as much warnings as possible
use enum instead of MACRO for ocl.hpp
add command line parser in accuracy test and perf test
some bug fix for arthim functions
This commit is contained in:
Niko
2012-10-22 15:14:22 +08:00
parent b6a2717c2b
commit 5df77a841e
44 changed files with 2040 additions and 1593 deletions
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45
modules/ocl/test/main.cpp
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@@ -73,22 +73,53 @@ void print_info()
#endif
}
std::string workdir;
int main(int argc, char **argv)
{
TS::ptr()->init("ocl");
InitGoogleTest(&argc, argv);
const char *keys =
"{ h | help | false | print help message }"
"{ w | workdir | ../../../samples/c/| set working directory }"
"{ t | type | gpu | set device type:cpu or gpu}"
"{ p | platform | 0 | set platform id }"
"{ d | device | 0 | set device id }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Avaible options besides goole test option:" << endl;
cmd.printParams();
return 0;
}
workdir = cmd.get<string>("workdir");
string type = cmd.get<string>("type");
unsigned int pid = cmd.get<unsigned int>("platform");
int device = cmd.get<int>("device");
print_info();
std::vector<cv::ocl::Info> oclinfo;
int devnums = getDevice(oclinfo);
if(devnums < 1)
int flag = CVCL_DEVICE_TYPE_GPU;
if(type == "cpu")
{
std::cout << "no device found\n";
flag = CVCL_DEVICE_TYPE_CPU;
}
std::vector<cv::ocl::Info> oclinfo;
int devnums = getDevice(oclinfo, flag);
if(devnums <= device || device < 0)
{
std::cout << "device invalid\n";
return -1;
}
//setDevice(oclinfo[1]);
if(pid >= oclinfo.size())
{
std::cout << "platform invalid\n";
return -1;
}
if(pid != 0 || device != 0)
{
setDevice(oclinfo[pid], device);
}
cout << "Device type:" << type << endl << "Device name:" << oclinfo[pid].DeviceName[device] << endl;
return RUN_ALL_TESTS();
}

2
modules/ocl/test/precomp.hpp
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@@ -67,7 +67,5 @@
#include "interpolation.hpp"
//#include "add_test_info.h"
#define OPENCV_DEFAULT_OPENCL_DEVICE CVCL_DEVICE_TYPE_GPU
#endif

9
modules/ocl/test/test_arithm.cpp
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@@ -133,10 +133,9 @@ PARAM_TEST_CASE(ArithmTestBase, MatType, bool)
void random_roi()
{
cv::RNG &rng = TS::ptr()->get_rng();
#ifdef RANDOMROI
//randomize ROI
cv::RNG &rng = TS::ptr()->get_rng();
roicols = rng.uniform(1, mat1.cols);
roirows = rng.uniform(1, mat1.rows);
src1x = rng.uniform(0, mat1.cols - roicols);
@@ -234,7 +233,7 @@ TEST_P(Exp, Mat)
char s[1024];
sprintf(s, "roicols=%d,roirows=%d,src1x=%d,src1y=%d,dstx=%d,dsty=%d,maskx=%d,masky=%d,src2x=%d,src2y=%d", roicols, roirows, src1x, src1y, dstx, dsty, maskx, masky, src2x, src2y);
EXPECT_MAT_NEAR(dst, cpu_dst, 1, s);
EXPECT_MAT_NEAR(dst, cpu_dst, 2, s);
}
}
@@ -855,7 +854,7 @@ TEST_P(MinMaxLoc, MAT)
cv::Point minLoc_, maxLoc_;
cv::ocl::minMaxLoc(gmat1, &minVal_, &maxVal_, &minLoc_, &maxLoc_, cv::ocl::oclMat());
double error0, error1, minlocVal, minlocVal_, maxlocVal, maxlocVal_;
double error0 = 0., error1 = 0., minlocVal = 0., minlocVal_ = 0., maxlocVal = 0., maxlocVal_ = 0.;
if(depth == 0)
{
minlocVal = mat1_roi.at<unsigned char>(minLoc);
@@ -975,7 +974,7 @@ TEST_P(MinMaxLoc, MASK)
cv::Point minLoc_, maxLoc_;
cv::ocl::minMaxLoc(gmat1, &minVal_, &maxVal_, &minLoc_, &maxLoc_, gmask);
double error0, error1, minlocVal, minlocVal_, maxlocVal, maxlocVal_;
double error0 = 0., error1 = 0., minlocVal = 0., minlocVal_ = 0., maxlocVal = 0., maxlocVal_ = 0.;
if(minLoc_.x == -1 || minLoc_.y == -1 || maxLoc_.x == -1 || maxLoc_.y == -1) continue;
if(depth == 0)
{

11
modules/ocl/test/test_canny.cpp
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@@ -45,16 +45,11 @@
#include "precomp.hpp"
#ifdef HAVE_OPENCL
#ifdef WIN32
#define FILTER_IMAGE "C:/Users/Public/Pictures/Sample Pictures/Penguins.jpg"
#else
#define FILTER_IMAGE "/Users/Test/Valve_original.PNG" // user need to specify a valid image path
#endif
#define SHOW_RESULT 0
////////////////////////////////////////////////////////
// Canny
extern std::string workdir;
IMPLEMENT_PARAM_CLASS(AppertureSize, int);
IMPLEMENT_PARAM_CLASS(L2gradient, bool);
@@ -76,7 +71,7 @@ PARAM_TEST_CASE(Canny, AppertureSize, L2gradient)
TEST_P(Canny, Accuracy)
{
cv::Mat img = readImage(FILTER_IMAGE, cv::IMREAD_GRAYSCALE);
cv::Mat img = readImage(workdir + "fruits.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
double low_thresh = 50.0;
@@ -110,4 +105,4 @@ TEST_P(Canny, Accuracy)
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Canny, testing::Combine(
testing::Values(AppertureSize(3), AppertureSize(5)),
testing::Values(L2gradient(false), L2gradient(true))));
#endif
#endif

15
modules/ocl/test/test_haar.cpp
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@@ -52,7 +52,7 @@ using namespace cvtest;
using namespace testing;
using namespace std;
using namespace cv;
extern string workdir;
struct getRect
{
Rect operator ()(const CvAvgComp &e) const
@@ -75,14 +75,11 @@ PARAM_TEST_CASE(HaarTestBase, int, int)
{
scale = 1.0;
index = 0;
string cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
string cascadeName = workdir + "../../data/haarcascades/haarcascade_frontalface_alt.xml";
if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
{
cout << "ERROR: Could not load classifier cascade" << endl;
cout << "Usage: facedetect [--cascade=<cascade_path>]\n"
" [--scale[=<image scale>\n"
" [filename|camera_index]\n" << endl ;
return;
}
//int devnums = getDevice(oclinfo);
@@ -99,17 +96,17 @@ struct Haar : HaarTestBase {};
TEST_F(Haar, FaceDetect)
{
string imgName = "../../../samples/c/lena.jpg";
string imgName = workdir + "lena.jpg";
Mat img = imread( imgName, 1 );
if(img.empty())
{
std::cout << "Couldn't read test" << index << ".jpg" << std::endl;
std::cout << "Couldn't read " << imgName << std::endl;
return ;
}
int i = 0;
double t = 0;
//int i = 0;
//double t = 0;
vector<Rect> faces, oclfaces;
const static Scalar colors[] = { CV_RGB(0, 0, 255),

6
modules/ocl/test/test_hog.cpp
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@@ -48,7 +48,7 @@
using namespace std;
#ifdef HAVE_OPENCL
extern string workdir;
PARAM_TEST_CASE(HOG, cv::Size, int)
{
cv::Size winSize;
@@ -63,7 +63,7 @@ PARAM_TEST_CASE(HOG, cv::Size, int)
TEST_P(HOG, GetDescriptors)
{
// Load image
cv::Mat img_rgb = readImage("../../../samples/gpu/road.png");
cv::Mat img_rgb = readImage(workdir + "lena.jpg");
ASSERT_FALSE(img_rgb.empty());
// Convert image
@@ -120,7 +120,7 @@ bool match_rect(cv::Rect r1, cv::Rect r2, int threshold)
TEST_P(HOG, Detect)
{
// Load image
cv::Mat img_rgb = readImage("../../../samples/gpu/road.png");
cv::Mat img_rgb = readImage(workdir + "lena.jpg");
ASSERT_FALSE(img_rgb.empty());
// Convert image

16
modules/ocl/test/test_imgproc.cpp
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@@ -1008,7 +1008,7 @@ TEST_P(Remap, Mat)
int bordertype[] = {cv::BORDER_CONSTANT, cv::BORDER_REPLICATE/*,BORDER_REFLECT,BORDER_WRAP,BORDER_REFLECT_101*/};
const char *borderstr[] = {"BORDER_CONSTANT", "BORDER_REPLICATE"/*, "BORDER_REFLECT","BORDER_WRAP","BORDER_REFLECT_101"*/};
// for(int i = 0; i < sizeof(bordertype)/sizeof(int); i++)
for(int j = 0; j < 100; j++)
for(int j = 0; j < LOOP_TIMES; j++)
{
random_roi();
cv::remap(src_roi, dst_roi, map1_roi, map2_roi, interpolation, bordertype[0], val);
@@ -1017,7 +1017,7 @@ TEST_P(Remap, Mat)
gdst.download(cpu_dst);
char sss[1024];
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d", src_roicols, src_roirows, dst_roicols, dst_roirows, srcx, srcy, dstx, dsty);
sprintf(sss, "src_roicols=%d,src_roirows=%d,dst_roicols=%d,dst_roirows=%d,src1x =%d,src1y=%d,dstx=%d,dsty=%d bordertype=%s", src_roicols, src_roirows, dst_roicols, dst_roirows, srcx, srcy, dstx, dsty, borderstr[0]);
if(interpolation == 0)
@@ -1371,7 +1371,9 @@ TEST_P(meanShiftFiltering, Mat)
gdst.download(cpu_gdst);
char sss[1024];
char warning[300] = "Warning: If the selected device doesn't support double, a deviation will exist.\nIf the accuracy is acceptable, please ignore it.\n";
sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
strcat(sss, warning);
EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);
}
@@ -1397,7 +1399,9 @@ TEST_P(meanShiftProc, Mat)
gdstCoor.download(cpu_gdstCoor);
char sss[1024];
char warning[300] = "Warning: If the selected device doesn't support double, a deviation will exist.\nIf the accuracy is acceptable, please ignore it.\n";
sprintf(sss, "roicols=%d,roirows=%d,srcx=%d,srcy=%d,dstx=%d,dsty=%d\n", roicols, roirows, srcx, srcy, dstx, dsty);
strcat(sss, warning);
EXPECT_MAT_NEAR(dst, cpu_gdst, 0.0, sss);
EXPECT_MAT_NEAR(dstCoor, cpu_gdstCoor, 0.0, sss);
}
@@ -1740,7 +1744,7 @@ INSTANTIATE_TEST_CASE_P(Imgproc, meanShiftProc, Combine(
));
INSTANTIATE_TEST_CASE_P(Imgproc, Remap, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC4),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values(CV_32FC1, CV_16SC2, CV_32FC2), Values(-1, CV_32FC1),
Values((int)cv::INTER_NEAREST, (int)cv::INTER_LINEAR),
Values((int)cv::BORDER_CONSTANT)));
@@ -1751,7 +1755,7 @@ INSTANTIATE_TEST_CASE_P(histTestBase, calcHist, Combine(
ONE_TYPE(CV_32SC1) //no use
));
INSTANTIATE_TEST_CASE_P(ConvolveTestBase, Convolve, Combine(
Values(CV_32FC1, CV_32FC1),
Values(false))); // Values(false) is the reserved parameter
//INSTANTIATE_TEST_CASE_P(ConvolveTestBase, Convolve, Combine(
// Values(CV_32FC1, CV_32FC1),
// Values(false))); // Values(false) is the reserved parameter
#endif // HAVE_OPENCL

30
modules/ocl/test/test_match_template.cpp
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@@ -44,7 +44,7 @@
#include "precomp.hpp"
#define PERF_TEST 0
//#define PERF_TEST 0
#ifdef HAVE_OPENCL
////////////////////////////////////////////////////////////////////////////////
// MatchTemplate
@@ -157,18 +157,18 @@ TEST_P(MatchTemplate32F, Accuracy)
#endif // PERF_TEST
}
//INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U,
// testing::Combine(
// MTEMP_SIZES,
// testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
// testing::Values(Channels(1), Channels(3), Channels(4)),
// ALL_TEMPLATE_METHODS
// )
// );
//
//INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
// MTEMP_SIZES,
// testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
// testing::Values(Channels(1), Channels(3), Channels(4)),
// testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U,
testing::Combine(
MTEMP_SIZES,
testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
testing::Values(Channels(1), Channels(3), Channels(4)),
ALL_TEMPLATE_METHODS
)
);
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
MTEMP_SIZES,
testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
testing::Values(Channels(1), Channels(3), Channels(4)),
testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));
#endif

6
modules/ocl/test/test_pyrlk.cpp
View File

@@ -54,7 +54,7 @@ using namespace std;
/////////////////////////////////////////////////////////////////////////////////////////////////
// BroxOpticalFlow
extern string workdir;
#define BROX_OPTICAL_FLOW_DUMP_FILE "opticalflow/brox_optical_flow.bin"
#define BROX_OPTICAL_FLOW_DUMP_FILE_CC20 "opticalflow/brox_optical_flow_cc20.bin"
@@ -78,10 +78,10 @@ PARAM_TEST_CASE(Sparse, bool, bool)
TEST_P(Sparse, Mat)
{
cv::Mat frame0 = readImage("../../../samples/gpu/rubberwhale1.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
cv::Mat frame0 = readImage(workdir + "../gpu/rubberwhale1.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame0.empty());
cv::Mat frame1 = readImage("../../../samples/gpu/rubberwhale2.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
cv::Mat frame1 = readImage(workdir + "../gpu/rubberwhale2.png", useGray ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR);
ASSERT_FALSE(frame1.empty());
cv::Mat gray_frame;