mirror of
https://github.com/opencv/opencv.git
synced 2024-11-24 19:20:28 +08:00
204 lines
6.7 KiB
C++
204 lines
6.7 KiB
C++
#include <vector>
|
|
#include <iostream>
|
|
#include <string>
|
|
|
|
#include "opencv2/core/core.hpp"
|
|
#include "opencv2/imgproc/imgproc.hpp"
|
|
#include "opencv2/gpu/gpu.hpp"
|
|
#include "opencv2/highgui/highgui.hpp"
|
|
#include "opencv2/contrib/contrib.hpp"
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
using namespace cv::gpu;
|
|
|
|
static Mat loadImage(const string& name)
|
|
{
|
|
Mat image = imread(name, IMREAD_GRAYSCALE);
|
|
if (image.empty())
|
|
{
|
|
cerr << "Can't load image - " << name << endl;
|
|
exit(-1);
|
|
}
|
|
return image;
|
|
}
|
|
|
|
int main(int argc, const char* argv[])
|
|
{
|
|
CommandLineParser cmd(argc, argv,
|
|
"{ i | image | pic1.png | input image }"
|
|
"{ t | template | templ.png | template image }"
|
|
"{ s | scale | | estimate scale }"
|
|
"{ r | rotation | | estimate rotation }"
|
|
"{ | gpu | | use gpu version }"
|
|
"{ | minDist | 100 | minimum distance between the centers of the detected objects }"
|
|
"{ | levels | 360 | R-Table levels }"
|
|
"{ | votesThreshold | 30 | the accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected }"
|
|
"{ | angleThresh | 10000 | angle votes treshold }"
|
|
"{ | scaleThresh | 1000 | scale votes treshold }"
|
|
"{ | posThresh | 100 | position votes threshold }"
|
|
"{ | dp | 2 | inverse ratio of the accumulator resolution to the image resolution }"
|
|
"{ | minScale | 0.5 | minimal scale to detect }"
|
|
"{ | maxScale | 2 | maximal scale to detect }"
|
|
"{ | scaleStep | 0.05 | scale step }"
|
|
"{ | minAngle | 0 | minimal rotation angle to detect in degrees }"
|
|
"{ | maxAngle | 360 | maximal rotation angle to detect in degrees }"
|
|
"{ | angleStep | 1 | angle step in degrees }"
|
|
"{ | maxSize | 1000 | maximal size of inner buffers }"
|
|
"{ h | help | | print help message }"
|
|
);
|
|
|
|
//cmd.about("This program demonstrates arbitary object finding with the Generalized Hough transform.");
|
|
|
|
if (cmd.get<bool>("help"))
|
|
{
|
|
cmd.printParams();
|
|
return 0;
|
|
}
|
|
|
|
const string templName = cmd.get<string>("template");
|
|
const string imageName = cmd.get<string>("image");
|
|
const bool estimateScale = cmd.get<bool>("scale");
|
|
const bool estimateRotation = cmd.get<bool>("rotation");
|
|
const bool useGpu = cmd.get<bool>("gpu");
|
|
const double minDist = cmd.get<double>("minDist");
|
|
const int levels = cmd.get<int>("levels");
|
|
const int votesThreshold = cmd.get<int>("votesThreshold");
|
|
const int angleThresh = cmd.get<int>("angleThresh");
|
|
const int scaleThresh = cmd.get<int>("scaleThresh");
|
|
const int posThresh = cmd.get<int>("posThresh");
|
|
const double dp = cmd.get<double>("dp");
|
|
const double minScale = cmd.get<double>("minScale");
|
|
const double maxScale = cmd.get<double>("maxScale");
|
|
const double scaleStep = cmd.get<double>("scaleStep");
|
|
const double minAngle = cmd.get<double>("minAngle");
|
|
const double maxAngle = cmd.get<double>("maxAngle");
|
|
const double angleStep = cmd.get<double>("angleStep");
|
|
const int maxSize = cmd.get<int>("maxSize");
|
|
|
|
Mat templ = loadImage(templName);
|
|
Mat image = loadImage(imageName);
|
|
|
|
int method = GHT_POSITION;
|
|
if (estimateScale)
|
|
method += GHT_SCALE;
|
|
if (estimateRotation)
|
|
method += GHT_ROTATION;
|
|
|
|
vector<Vec4f> position;
|
|
cv::TickMeter tm;
|
|
|
|
if (useGpu)
|
|
{
|
|
GpuMat d_templ(templ);
|
|
GpuMat d_image(image);
|
|
GpuMat d_position;
|
|
|
|
Ptr<GeneralizedHough_GPU> d_hough = GeneralizedHough_GPU::create(method);
|
|
d_hough->set("minDist", minDist);
|
|
d_hough->set("levels", levels);
|
|
d_hough->set("dp", dp);
|
|
d_hough->set("maxSize", maxSize);
|
|
if (estimateScale && estimateRotation)
|
|
{
|
|
d_hough->set("angleThresh", angleThresh);
|
|
d_hough->set("scaleThresh", scaleThresh);
|
|
d_hough->set("posThresh", posThresh);
|
|
}
|
|
else
|
|
{
|
|
d_hough->set("votesThreshold", votesThreshold);
|
|
}
|
|
if (estimateScale)
|
|
{
|
|
d_hough->set("minScale", minScale);
|
|
d_hough->set("maxScale", maxScale);
|
|
d_hough->set("scaleStep", scaleStep);
|
|
}
|
|
if (estimateRotation)
|
|
{
|
|
d_hough->set("minAngle", minAngle);
|
|
d_hough->set("maxAngle", maxAngle);
|
|
d_hough->set("angleStep", angleStep);
|
|
}
|
|
|
|
d_hough->setTemplate(d_templ);
|
|
|
|
tm.start();
|
|
|
|
d_hough->detect(d_image, d_position);
|
|
d_hough->download(d_position, position);
|
|
|
|
tm.stop();
|
|
}
|
|
else
|
|
{
|
|
Ptr<GeneralizedHough> hough = GeneralizedHough::create(method);
|
|
hough->set("minDist", minDist);
|
|
hough->set("levels", levels);
|
|
hough->set("dp", dp);
|
|
if (estimateScale && estimateRotation)
|
|
{
|
|
hough->set("angleThresh", angleThresh);
|
|
hough->set("scaleThresh", scaleThresh);
|
|
hough->set("posThresh", posThresh);
|
|
hough->set("maxSize", maxSize);
|
|
}
|
|
else
|
|
{
|
|
hough->set("votesThreshold", votesThreshold);
|
|
}
|
|
if (estimateScale)
|
|
{
|
|
hough->set("minScale", minScale);
|
|
hough->set("maxScale", maxScale);
|
|
hough->set("scaleStep", scaleStep);
|
|
}
|
|
if (estimateRotation)
|
|
{
|
|
hough->set("minAngle", minAngle);
|
|
hough->set("maxAngle", maxAngle);
|
|
hough->set("angleStep", angleStep);
|
|
}
|
|
|
|
hough->setTemplate(templ);
|
|
|
|
tm.start();
|
|
|
|
hough->detect(image, position);
|
|
|
|
tm.stop();
|
|
}
|
|
|
|
cout << "Found : " << position.size() << " objects" << endl;
|
|
cout << "Detection time : " << tm.getTimeMilli() << " ms" << endl;
|
|
|
|
Mat out;
|
|
cvtColor(image, out, COLOR_GRAY2BGR);
|
|
|
|
for (size_t i = 0; i < position.size(); ++i)
|
|
{
|
|
Point2f pos(position[i][0], position[i][1]);
|
|
float scale = position[i][2];
|
|
float angle = position[i][3];
|
|
|
|
RotatedRect rect;
|
|
rect.center = pos;
|
|
rect.size = Size2f(templ.cols * scale, templ.rows * scale);
|
|
rect.angle = angle;
|
|
|
|
Point2f pts[4];
|
|
rect.points(pts);
|
|
|
|
line(out, pts[0], pts[1], Scalar(0, 0, 255), 3);
|
|
line(out, pts[1], pts[2], Scalar(0, 0, 255), 3);
|
|
line(out, pts[2], pts[3], Scalar(0, 0, 255), 3);
|
|
line(out, pts[3], pts[0], Scalar(0, 0, 255), 3);
|
|
}
|
|
|
|
imshow("out", out);
|
|
waitKey();
|
|
|
|
return 0;
|
|
}
|