gpu::HoughLinesP

This commit is contained in:
Vladislav Vinogradov 2012-12-06 15:14:20 +04:00
parent a6dc6f72b3
commit aad76090ce
7 changed files with 291 additions and 4 deletions

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@ -847,6 +847,11 @@ CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, float rho, float th
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines, OutputArray h_votes = noArray());
//! HoughLinesP
//! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS void HoughLinesP(const GpuMat& image, GpuMat& lines, CannyBuf& cannyBuf, int minLineLength, int maxLineGap, int maxLines = 4096);
//! HoughCircles
struct HoughCirclesBuf

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@ -1706,6 +1706,16 @@ PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidGetLayer, Combine(GPU_TYPICAL_MAT_S
}
namespace {
struct Vec4iComparator
{
bool operator()(const cv::Vec4i& a, const cv::Vec4i b) const
{
if (a[0] != b[0]) return a[0] < b[0];
else if(a[1] != b[1]) return a[1] < b[1];
else if(a[2] != b[2]) return a[2] < b[2];
else return a[3] < b[3];
}
};
struct Vec3fComparator
{
bool operator()(const cv::Vec3f& a, const cv::Vec3f b) const
@ -1784,6 +1794,62 @@ PERF_TEST_P(Sz, ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)
}
}
//////////////////////////////////////////////////////////////////////
// HoughLinesP
DEF_PARAM_TEST_1(Image, std::string);
PERF_TEST_P(Image, ImgProc_HoughLinesP, testing::Values("cv/shared/pic5.png", "stitching/a1.png"))
{
declare.time(30.0);
std::string fileName = getDataPath(GetParam());
const double rho = 1.0f;
const double theta = CV_PI / 180.0;
const int threshold = 100;
const int minLineLenght = 50;
const int maxLineGap = 5;
cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE);
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat d_image(image);
cv::gpu::GpuMat d_lines;
cv::gpu::CannyBuf d_buf;
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, minLineLenght, maxLineGap);
TEST_CYCLE()
{
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, minLineLenght, maxLineGap);
}
cv::Mat h_lines(d_lines);
cv::Vec4i* begin = h_lines.ptr<cv::Vec4i>();
cv::Vec4i* end = h_lines.ptr<cv::Vec4i>() + h_lines.cols;
std::sort(begin, end, Vec4iComparator());
SANITY_CHECK(h_lines);
}
else
{
cv::Mat mask;
cv::Canny(image, mask, 50, 100);
std::vector<cv::Vec4i> lines;
cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap);
TEST_CYCLE()
{
cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap);
}
std::sort(lines.begin(), lines.end(), Vec4iComparator());
SANITY_CHECK(lines);
}
}
//////////////////////////////////////////////////////////////////////
// HoughCircles

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@ -177,7 +177,7 @@ namespace
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x >= dx.cols || y >= dx.rows)
if (x == 0 || x >= dx.cols - 1 || y == 0 || y >= dx.rows - 1)
return;
int dxVal = dx(y, x);
@ -378,7 +378,7 @@ namespace
pos.x += c_dx[threadIdx.x];
pos.y += c_dy[threadIdx.x];
if (pos.x > 0 && pos.x <= map.cols && pos.y > 0 && pos.y <= map.rows && map(pos.y, pos.x) == 1)
if (pos.x > 0 && pos.x < map.cols && pos.y > 0 && pos.y < map.rows && map(pos.y, pos.x) == 1)
{
map(pos.y, pos.x) = 2;
@ -410,7 +410,7 @@ namespace
pos.x += c_dx[threadIdx.x & 7];
pos.y += c_dy[threadIdx.x & 7];
if (pos.x > 0 && pos.x <= map.cols && pos.y > 0 && pos.y <= map.rows && map(pos.y, pos.x) == 1)
if (pos.x > 0 && pos.x < map.cols && pos.y > 0 && pos.y < map.rows && map(pos.y, pos.x) == 1)
{
map(pos.y, pos.x) = 2;

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@ -291,6 +291,108 @@ namespace cv { namespace gpu { namespace device
return totalCount;
}
////////////////////////////////////////////////////////////////////////
// houghLinesProbabilistic
texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_mask(false, cudaFilterModePoint, cudaAddressModeClamp);
__global__ void houghLinesProbabilistic(const PtrStepSzi Dx, const PtrStepi Dy,
int4* out, const int maxSize,
const int lineGap, const int lineLength)
{
const int SHIFT = 10;
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (x >= Dx.cols || y >= Dx.rows || tex2D(tex_mask, x, y) == 0)
return;
const int dx = Dx(y, x);
const int dy = Dy(y, x);
if (dx == 0 && dy == 0)
return;
const int vx = dy;
const int vy = -dx;
const float mag = ::sqrtf(vx * vx + vy * vy);
const int x0 = x << SHIFT;
const int y0 = y << SHIFT;
int sx = __float2int_rn((vx << SHIFT) / mag);
int sy = __float2int_rn((vy << SHIFT) / mag);
int2 line_end[2] = {make_int2(x,y), make_int2(x,y)};
for (int k = 0; k < 2; ++k)
{
int gap = 0;
int x1 = x0 + sx;
int y1 = y0 + sy;
for (;; x1 += sx, y1 += sy)
{
const int x2 = x1 >> SHIFT;
const int y2 = y1 >> SHIFT;
if (x2 < 0 || x2 >= Dx.cols || y2 < 0 || y2 >= Dx.rows)
break;
if (tex2D(tex_mask, x2, y2))
{
gap = 0;
line_end[k].x = x2;
line_end[k].y = y2;
}
else if(++gap > lineGap)
break;
}
sx = -sx;
sy = -sy;
}
const bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
::abs(line_end[1].y - line_end[0].y) >= lineLength;
if (good_line)
{
const int ind = ::atomicAdd(&g_counter, 1);
if (ind < maxSize)
out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
}
}
int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi Dx, PtrStepSzi Dy,
int4* out, int maxSize,
int lineGap, int lineLength)
{
void* counterPtr;
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
const dim3 block(32, 8);
const dim3 grid(divUp(mask.cols, block.x), divUp(mask.rows, block.y));
bindTexture(&tex_mask, mask);
houghLinesProbabilistic<<<grid, block>>>(Dx, Dy, out, maxSize, lineGap, lineLength);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
int totalCount;
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
totalCount = ::min(totalCount, maxSize);
return totalCount;
}
////////////////////////////////////////////////////////////////////////
// circlesAccumCenters
@ -1509,4 +1611,4 @@ namespace cv { namespace gpu { namespace device
}}}
#endif /* CUDA_DISABLER */
#endif /* CUDA_DISABLER */

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@ -52,6 +52,8 @@ void cv::gpu::HoughLines(const GpuMat&, GpuMat&, float, float, int, bool, int) {
void cv::gpu::HoughLines(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, bool, int) { throw_nogpu(); }
void cv::gpu::HoughLinesDownload(const GpuMat&, OutputArray, OutputArray) { throw_nogpu(); }
void cv::gpu::HoughLinesP(const GpuMat&, GpuMat&, CannyBuf&, int, int, int) { throw_nogpu(); }
void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
void cv::gpu::HoughCirclesDownload(const GpuMat&, OutputArray) { throw_nogpu(); }
@ -155,6 +157,42 @@ void cv::gpu::HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines_, Ou
}
}
//////////////////////////////////////////////////////////
// HoughLinesP
namespace cv { namespace gpu { namespace device
{
namespace hough
{
int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi Dx, PtrStepSzi Dy,
int4* out, int maxSize,
int lineGap, int lineLength);
}
}}}
void cv::gpu::HoughLinesP(const GpuMat& image, GpuMat& lines, CannyBuf& cannyBuf, int minLineLength, int maxLineGap, int maxLines)
{
using namespace cv::gpu::device::hough;
CV_Assert( image.type() == CV_8UC1 );
CV_Assert( image.cols < std::numeric_limits<unsigned short>::max() );
CV_Assert( image.rows < std::numeric_limits<unsigned short>::max() );
GpuMat mask;
Canny(image, cannyBuf, mask, 50, 100);
ensureSizeIsEnough(1, maxLines, CV_32SC4, lines);
int linesCount = houghLinesProbabilistic_gpu(mask, cannyBuf.dx, cannyBuf.dy,
lines.ptr<int4>(), maxLines,
maxLineGap, minLineLength);
if (linesCount > 0)
lines.cols = linesCount;
else
lines.release();
}
//////////////////////////////////////////////////////////
// HoughCircles

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@ -1484,6 +1484,7 @@ namespace
{
using namespace canny;
buf.map.setTo(Scalar::all(0));
calcMap(dx, dy, buf.mag, buf.map, low_thresh, high_thresh);
edgesHysteresisLocal(buf.map, buf.st1.ptr<ushort2>());

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@ -0,0 +1,75 @@
#include <cmath>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
using namespace std;
using namespace cv;
using namespace cv::gpu;
static void help()
{
cout << "This program demonstrates line finding with the Hough transform." << endl;
cout << "Usage:" << endl;
cout << "./gpu-example-houghlines <image_name>, Default is pic1.png\n" << endl;
}
int main(int argc, const char* argv[])
{
const string filename = argc >= 2 ? argv[1] : "pic1.png";
Mat src = imread(filename, IMREAD_GRAYSCALE);
if (src.empty())
{
help();
cout << "can not open " << filename << endl;
return -1;
}
Mat mask;
Canny(src, mask, 50, 200, 3);
Mat dst_cpu;
cvtColor(mask, dst_cpu, CV_GRAY2BGR);
Mat dst_gpu = dst_cpu.clone();
vector<Vec4i> lines_cpu;
HoughLinesP(mask, lines_cpu, 1, CV_PI / 180, 50, 50, 5);
cout << lines_cpu.size() << endl;
for (size_t i = 0; i < lines_cpu.size(); ++i)
{
Vec4i l = lines_cpu[i];
line(dst_cpu, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 0, 255), 3, CV_AA);
}
GpuMat d_src(src);
GpuMat d_lines;
CannyBuf d_buf;
gpu::HoughLinesP(d_src, d_lines, d_buf, 50, 5);
vector<Vec4i> lines_gpu;
if (!d_lines.empty())
{
lines_gpu.resize(d_lines.cols);
Mat h_lines(1, d_lines.cols, CV_32SC4, &lines_gpu[0]);
d_lines.download(h_lines);
}
cout << lines_gpu.size() << endl;
for (size_t i = 0; i < lines_gpu.size(); ++i)
{
Vec4i l = lines_gpu[i];
line(dst_gpu, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 0, 255), 3, CV_AA);
}
imshow("source", src);
imshow("detected lines [CPU]", dst_cpu);
imshow("detected lines [GPU]", dst_gpu);
waitKey();
return 0;
}