Added ippiHoughProbLine to cv::HoughLinesP

pull/2658/head
Alexander Karsakov 11 years ago
parent f3d1001c5d
commit 1909978f7d
  1. 11
      modules/imgproc/perf/perf_houghLines.cpp
  2. 32
      modules/imgproc/src/hough.cpp
  3. 49
      modules/imgproc/test/test_houghLines.cpp

@ -8,11 +8,6 @@ using namespace perf;
using std::tr1::make_tuple;
using std::tr1::get;
bool polarComp(Vec2f a, Vec2f b)
{
return a[1] > b[1] || (a[1] == b[1] && a[0] < b[0]);
}
typedef std::tr1::tuple<string, double, double, int> Image_RhoStep_ThetaStep_Threshold_t;
typedef perf::TestBaseWithParam<Image_RhoStep_ThetaStep_Threshold_t> Image_RhoStep_ThetaStep_Threshold;
@ -20,8 +15,8 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
testing::Combine(
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( 0.05, 0.1 ),
testing::Values( 80 , 150 )
)
)
{
@ -34,7 +29,7 @@ PERF_TEST_P(Image_RhoStep_ThetaStep_Threshold, HoughLines,
if (image.empty())
FAIL() << "Unable to load source image" << filename;
Canny(image, image, 0, 0);
Canny(image, image, 100, 150, 3);
Mat lines;
declare.time(60);

@ -103,11 +103,12 @@ HoughLinesStandard( const Mat& img, float rho, float theta,
IppPointPolar delta = { rho, theta };
IppPointPolar dstRoi[2] = {{(Ipp32f) -(width + height), (Ipp32f) min_theta},{(Ipp32f) (width + height), (Ipp32f) max_theta}};
int bufferSize;
int ipp_linesMax = std::min(linesMax, numangle*numrho);
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);
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)
@ -115,6 +116,8 @@ HoughLinesStandard( const Mat& img, float rho, float theta,
lines.resize(linesCount);
return;
}
lines.clear();
setIppErrorStatus();
#endif
AutoBuffer<int> _accum((numangle+2) * (numrho+2));
@ -424,6 +427,31 @@ HoughLinesProbabilistic( Mat& image,
int numangle = cvRound(CV_PI / theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho);
#if (defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY) && IPP_VERSION_X100 >= 801 && 0)
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);

@ -50,26 +50,26 @@ template<typename T>
struct SimilarWith
{
T value;
double eps;
double rho_eps;
SimilarWith<T>(T val, double e, double r_e): value(val), eps(e), rho_eps(r_e) { };
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]) < eps;
return abs(other[0] - value[0]) < rho_eps && abs(other[1] - value[1]) < theta_eps;
}
template<>
bool SimilarWith<Vec4i>::operator()(Vec4i other)
{
return abs(other[0] - value[0]) < eps && abs(other[1] - value[1]) < eps && abs(other[2] - value[2]) < eps && abs(other[2] - value[2]) < eps;
return norm(value, other) < theta_eps;
}
template <typename T>
int countMatIntersection(Mat expect, Mat actual, double eps, double rho_eps)
int countMatIntersection(Mat expect, Mat actual, float eps, float rho_eps)
{
int count = 0;
if (!expect.empty() && !actual.empty())
@ -116,27 +116,27 @@ class StandartHoughLinesTest : public BaseHoughLineTest, public testing::TestWit
public:
StandartHoughLinesTest()
{
picture_name = get<0>(GetParam());
rhoStep = get<1>(GetParam());
thetaStep = get<2>(GetParam());
threshold = get<3>(GetParam());
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;
}
};
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>
class ProbabilisticHoughLinesTest : public BaseHoughLineTest, public testing::TestWithParam<Image_RhoStep_ThetaStep_Threshold_MinLine_MaxGap_t>
{
public:
ProbabilisticHoughLinesTest()
{
picture_name = get<0>(GetParam());
rhoStep = get<1>(GetParam());
thetaStep = get<2>(GetParam());
threshold = get<3>(GetParam());
minLineLength = get<4>(GetParam());
maxGap = get<5>(GetParam());
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());
}
};
@ -153,7 +153,7 @@ void BaseHoughLineTest::run_test(int type)
xml = string(cvtest::TS::ptr()->get_data_path()) + "imgproc/HoughLinesP.xml";
Mat dst;
Canny(src, dst, 50, 200, 3);
Canny(src, dst, 100, 150, 3);
EXPECT_FALSE(dst.empty()) << "Failed Canny edge detector";
Mat lines;
@ -162,7 +162,7 @@ void BaseHoughLineTest::run_test(int type)
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,
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);
@ -183,12 +183,11 @@ void BaseHoughLineTest::run_test(int type)
read( fs[test_case_name], exp_lines, Mat() );
fs.release();
float eps = 1e-2f;
int count = -1;
if (type == STANDART)
count = countMatIntersection<Vec2f>(exp_lines, lines, thetaStep + FLT_EPSILON, rhoStep + FLT_EPSILON);
count = countMatIntersection<Vec2f>(exp_lines, lines, (float) thetaStep + FLT_EPSILON, (float) rhoStep + FLT_EPSILON);
else if (type == PROBABILISTIC)
count = countMatIntersection<Vec4i>(exp_lines, lines, thetaStep, 0.0);
count = countMatIntersection<Vec4i>(exp_lines, lines, 1e-4f, 0.f);
EXPECT_GE( count, (int) (exp_lines.total() * 0.8) );
}
@ -205,13 +204,13 @@ TEST_P(ProbabilisticHoughLinesTest, regression)
INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ),
testing::Values( 1, 10 ),
testing::Values( 0.01, 0.1 ),
testing::Values( 100, 200 )
testing::Values( 0.05, 0.1 ),
testing::Values( 80, 150 )
));
INSTANTIATE_TEST_CASE_P( ImgProc, ProbabilisticHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "shared/pic1.png" ),
testing::Values( 5, 10 ),
testing::Values( 0.01, 0.1 ),
testing::Values( 0.05, 0.1 ),
testing::Values( 75, 150 ),
testing::Values( 0, 10 ),
testing::Values( 0, 4 )

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