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Merge pull request #2658 from akarsakov:ipp_hough

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This commit is contained in:
Alexander Alekhin 2014-05-07 17:07:22 +04:00 committed by OpenCV Buildbot
commit 9e47672b2b
3 changed files with 202 additions and 80 deletions
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4
modules/imgproc/perf/perf_houghLines.cpp
View File

@ -37,5 +37,9 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
TEST_CYCLE() HoughLines(image, lines, rhoStep, thetaStep, threshold);
transpose(lines, lines);
#if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
SANITY_CHECK_NOTHING();
#else
SANITY_CHECK(lines);
#endif
}

48
modules/imgproc/src/hough.cpp
View File

@ -12,6 +12,7 @@
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2014, Itseez, 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,
@ -97,6 +98,28 @@ HoughLinesStandard( const Mat& img, float rho, float theta,
int numangle = cvRound((max_theta - min_theta) / theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho);
#if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
IppiSize srcSize = { width, height };
IppPointPolar delta = { rho, theta };
IppPointPolar dstRoi[2] = {{(Ipp32f) -(width + height), (Ipp32f) min_theta},{(Ipp32f) (width + height), (Ipp32f) max_theta}};
int bufferSize;
int nz = countNonZero(img);
int ipp_linesMax = std::min(linesMax, nz*numangle/threshold);
int linesCount = 0;
lines.resize(ipp_linesMax);
IppStatus ok = ippiHoughLineGetSize_8u_C1R(srcSize, delta, ipp_linesMax, &bufferSize);
Ipp8u* buffer = ippsMalloc_8u(bufferSize);
if (ok >= 0) ok = ippiHoughLine_Region_8u32f_C1R(image, step, srcSize, (IppPointPolar*) &lines[0], dstRoi, ipp_linesMax, &linesCount, delta, threshold, buffer);
ippsFree(buffer);
if (ok >= 0)
{
lines.resize(linesCount);
return;
}
lines.clear();
setIppErrorStatus();
#endif
AutoBuffer<int> _accum((numangle+2) * (numrho+2));
std::vector<int> _sort_buf;
AutoBuffer<float> _tabSin(numangle);
@ -404,6 +427,31 @@ HoughLinesProbabilistic( Mat& image,
int numangle = cvRound(CV_PI / theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho);
#if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
IppiSize srcSize = { width, height };
IppPointPolar delta = { rho, theta };
IppiHoughProbSpec* pSpec;
int bufferSize, specSize;
int ipp_linesMax = std::min(linesMax, numangle*numrho);
int linesCount = 0;
lines.resize(ipp_linesMax);
IppStatus ok = ippiHoughProbLineGetSize_8u_C1R(srcSize, delta, &specSize, &bufferSize);
Ipp8u* buffer = ippsMalloc_8u(bufferSize);
pSpec = (IppiHoughProbSpec*) malloc(specSize);
if (ok >= 0) ok = ippiHoughProbLineInit_8u32f_C1R(srcSize, delta, ippAlgHintNone, pSpec);
if (ok >= 0) ok = ippiHoughProbLine_8u32f_C1R(image.data, image.step, srcSize, threshold, lineLength, lineGap, (IppiPoint*) &lines[0], ipp_linesMax, &linesCount, buffer, pSpec);
free(pSpec);
ippsFree(buffer);
if (ok >= 0)
{
lines.resize(linesCount);
return;
}
lines.clear();
setIppErrorStatus();
#endif
Mat accum = Mat::zeros( numangle, numrho, CV_32SC1 );
Mat mask( height, width, CV_8UC1 );
std::vector<float> trigtab(numangle*2);

230
modules/imgproc/test/test_houghLines.cpp
View File

@ -12,6 +12,7 @@
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014, Itseez, 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,
@ -45,107 +46,176 @@
using namespace cv;
using namespace std;
class CV_HoughLinesTest : public cvtest::BaseTest
template<typename T>
struct SimilarWith
{
T value;
float theta_eps;
float rho_eps;
SimilarWith<T>(T val, float e, float r_e): value(val), theta_eps(e), rho_eps(r_e) { };
bool operator()(T other);
};
template<>
bool SimilarWith<Vec2f>::operator()(Vec2f other)
{
return abs(other[0] - value[0]) < rho_eps && abs(other[1] - value[1]) < theta_eps;
}
template<>
bool SimilarWith<Vec4i>::operator()(Vec4i other)
{
return norm(value, other) < theta_eps;
}
template <typename T>
int countMatIntersection(Mat expect, Mat actual, float eps, float rho_eps)
{
int count = 0;
if (!expect.empty() && !actual.empty())
{
for (MatIterator_<T> it=expect.begin<T>(); it!=expect.end<T>(); it++)
{
MatIterator_<T> f = std::find_if(actual.begin<T>(), actual.end<T>(), SimilarWith<T>(*it, eps, rho_eps));
if (f != actual.end<T>())
count++;
}
}
return count;
}
String getTestCaseName(String filename)
{
string temp(filename);
size_t pos = temp.find_first_of("\\/.");
while ( pos != string::npos ) {
temp.replace( pos, 1, "_" );
pos = temp.find_first_of("\\/.");
}
return String(temp);
}
class BaseHoughLineTest
{
public:
enum {STANDART = 0, PROBABILISTIC};
CV_HoughLinesTest() {}
~CV_HoughLinesTest() {}
protected:
void run_test(int type);
string picture_name;
double rhoStep;
double thetaStep;
int threshold;
int minLineLength;
int maxGap;
};
class CV_StandartHoughLinesTest : public CV_HoughLinesTest
typedef std::tr1::tuple<string, double, double, int> Image_RhoStep_ThetaStep_Threshold_t;
class StandartHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_t>
{
public:
CV_StandartHoughLinesTest() {}
~CV_StandartHoughLinesTest() {}
virtual void run(int);
StandartHoughLinesTest()
{
picture_name = std::tr1::get<0>(GetParam());
rhoStep = std::tr1::get<1>(GetParam());
thetaStep = std::tr1::get<2>(GetParam());
threshold = std::tr1::get<3>(GetParam());
minLineLength = 0;
maxGap = 0;
}
};
class CV_ProbabilisticHoughLinesTest : public CV_HoughLinesTest
typedef std::tr1::tuple<string, double, double, int, int, int> Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t;
class ProbabilisticHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t>
{
public:
CV_ProbabilisticHoughLinesTest() {}
~CV_ProbabilisticHoughLinesTest() {}
virtual void run(int);
ProbabilisticHoughLinesTest()
{
picture_name = std::tr1::get<0>(GetParam());
rhoStep = std::tr1::get<1>(GetParam());
thetaStep = std::tr1::get<2>(GetParam());
threshold = std::tr1::get<3>(GetParam());
minLineLength = std::tr1::get<4>(GetParam());
maxGap = std::tr1::get<5>(GetParam());
}
};
void CV_StandartHoughLinesTest::run(int)
void BaseHoughLineTest::run_test(int type)
{
string filename = cvtest::TS::ptr()->get_data_path() + picture_name;
Mat src = imread(filename, IMREAD_GRAYSCALE);
EXPECT_FALSE(src.empty()) << "Invalid test image: " << filename;
string xml;
if (type == STANDART)
xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLines.xml";
else if (type == PROBABILISTIC)
xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLinesP.xml";
Mat dst;
Canny(src, dst, 100, 150, 3);
EXPECT_FALSE(dst.empty()) << "Failed Canny edge detector";
Mat lines;
if (type == STANDART)
HoughLines(dst, lines, rhoStep, thetaStep, threshold, 0, 0);
else if (type == PROBABILISTIC)
HoughLinesP(dst, lines, rhoStep, thetaStep, threshold, minLineLength, maxGap);
String test_case_name = format("lines_%s_%.0f_%.2f_%d_%d_%d", picture_name.c_str(), rhoStep, thetaStep,
threshold, minLineLength, maxGap);
test_case_name = getTestCaseName(test_case_name);
FileStorage fs(xml, FileStorage::READ);
FileNode node = fs[test_case_name];
if (node.empty())
{
fs.release();
fs.open(xml, FileStorage::APPEND);
EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
fs << test_case_name << lines;
fs.release();
fs.open(xml, FileStorage::READ);
EXPECT_TRUE(fs.isOpened()) << "Cannot open sanity data file: " << xml;
}
Mat exp_lines;
read( fs[test_case_name], exp_lines, Mat() );
fs.release();
int count = -1;
if (type == STANDART)
count = countMatIntersection<Vec2f>(exp_lines, lines, (float) thetaStep + FLT_EPSILON, (float) rhoStep + FLT_EPSILON);
else if (type == PROBABILISTIC)
count = countMatIntersection<Vec4i>(exp_lines, lines, 1e-4f, 0.f);
#if (0 && defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801)
EXPECT_GE( count, (int) (exp_lines.total() * 0.8) );
#else
EXPECT_EQ( count, (int) exp_lines.total());
#endif
}
TEST_P(StandartHoughLinesTest, regression)
{
run_test(STANDART);
}
void CV_ProbabilisticHoughLinesTest::run(int)
TEST_P(ProbabilisticHoughLinesTest, regression)
{
run_test(PROBABILISTIC);
}
void CV_HoughLinesTest::run_test(int type)
{
Mat src = imread(string(ts->get_data_path()) + "shared/pic1.png");
if (src.empty())
{
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ),
testing::Values( 1, 10 ),
testing::Values( 0.05, 0.1 ),
testing::Values( 80, 150 )
));
string xml;
if (type == STANDART)
xml = string(ts->get_data_path()) + "imgproc/HoughLines.xml";
else if (type == PROBABILISTIC)
xml = string(ts->get_data_path()) + "imgproc/HoughLinesP.xml";
else
{
ts->printf(cvtest::TS::LOG, "Error: unknown HoughLines algorithm type.\n");
ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
return;
}
Mat dst;
Canny(src, dst, 50, 200, 3);
Mat lines;
if (type == STANDART)
HoughLines(dst, lines, 1, CV_PI/180, 100, 0, 0);
else if (type == PROBABILISTIC)
HoughLinesP(dst, lines, 1, CV_PI/180, 100, 0, 0);
FileStorage fs(xml, FileStorage::READ);
if (!fs.isOpened())
{
fs.open(xml, FileStorage::WRITE);
if (!fs.isOpened())
{
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
fs << "exp_lines" << lines;
fs.release();
fs.open(xml, FileStorage::READ);
if (!fs.isOpened())
{
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
}
Mat exp_lines;
read( fs["exp_lines"], exp_lines, Mat() );
fs.release();
if( exp_lines.size != lines.size )
transpose(lines, lines);
if ( exp_lines.size != lines.size || cvtest::norm(exp_lines, lines, NORM_INF) > 1e-4 )
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return;
}
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Imgproc_HoughLines, regression) { CV_StandartHoughLinesTest test; test.safe_run(); }
TEST(Imgproc_HoughLinesP, regression) { CV_ProbabilisticHoughLinesTest test; test.safe_run(); }
INSTANTIATE_TEST_CASE_P( ImgProc, ProbabilisticHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "shared/pic1.png" ),
testing::Values( 5, 10 ),
testing::Values( 0.05, 0.1 ),
testing::Values( 75, 150 ),
testing::Values( 0, 10 ),
testing::Values( 0, 4 )
));