take1014
7 years ago
parent
0a6d190095
commit
4ec9afac57
6 changed files with 195 additions and 219 deletions
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/highgui.hpp> |
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#include <math.h> |
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using namespace cv; |
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using namespace std; |
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int main(int argc, char** argv) |
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{ |
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Mat img, gray; |
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if( argc != 2 || !(img=imread(argv[1], 1)).data) |
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return -1; |
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cvtColor(img, gray, COLOR_BGR2GRAY); |
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// smooth it, otherwise a lot of false circles may be detected
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GaussianBlur( gray, gray, Size(9, 9), 2, 2 ); |
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vector<Vec3f> circles; |
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HoughCircles(gray, circles, HOUGH_GRADIENT, |
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2, gray.rows/4, 200, 100 ); |
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for( size_t i = 0; i < circles.size(); i++ ) |
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{ |
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Point center(cvRound(circles[i][0]), cvRound(circles[i][1])); |
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int radius = cvRound(circles[i][2]); |
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// draw the circle center
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circle( img, center, 3, Scalar(0,255,0), -1, 8, 0 ); |
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// draw the circle outline
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circle( img, center, radius, Scalar(0,0,255), 3, 8, 0 ); |
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} |
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namedWindow( "circles", 1 ); |
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imshow( "circles", img ); |
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waitKey(0); |
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return 0; |
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} |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/highgui.hpp> |
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using namespace cv; |
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using namespace std; |
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int main(int argc, char** argv) |
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{ |
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Mat src, dst, color_dst; |
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if( argc != 2 || !(src=imread(argv[1], 0)).data) |
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return -1; |
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Canny( src, dst, 50, 200, 3 ); |
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cvtColor( dst, color_dst, COLOR_GRAY2BGR ); |
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vector<Vec4i> lines; |
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HoughLinesP( dst, lines, 1, CV_PI/180, 80, 30, 10 ); |
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for( size_t i = 0; i < lines.size(); i++ ) |
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{ |
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line( color_dst, Point(lines[i][0], lines[i][1]), |
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Point( lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 ); |
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} |
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namedWindow( "Source", 1 ); |
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imshow( "Source", src ); |
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namedWindow( "Detected Lines", 1 ); |
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imshow( "Detected Lines", color_dst ); |
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waitKey(0); |
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return 0; |
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} |
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#include <opencv2/core.hpp> |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/imgcodecs.hpp> |
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#include <opencv2/highgui.hpp> |
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using namespace cv; |
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#include <iostream> |
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using namespace std; |
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int main(int argc, const char *argv[]) |
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{ |
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// We need an input image. (can be grayscale or color)
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if (argc < 2) |
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{ |
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cerr << "We need an image to process here. Please run: colorMap [path_to_image]" << endl; |
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return -1; |
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} |
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Mat img_in = imread(argv[1]); |
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if(img_in.empty()) |
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{ |
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cerr << "Sample image (" << argv[1] << ") is empty. Please adjust your path, so it points to a valid input image!" << endl; |
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return -1; |
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} |
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// Holds the colormap version of the image:
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Mat img_color; |
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// Apply the colormap:
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applyColorMap(img_in, img_color, COLORMAP_JET); |
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// Show the result:
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imshow("colorMap", img_color); |
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waitKey(0); |
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return 0; |
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} |
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#include <opencv2/imgproc.hpp> |
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#include <opencv2/highgui.hpp> |
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using namespace cv; |
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int main( int argc, char** argv ) |
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{ |
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Mat src, hsv; |
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if( argc != 2 || !(src=imread(argv[1], 1)).data ) |
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return -1; |
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cvtColor(src, hsv, COLOR_BGR2HSV); |
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// Quantize the hue to 30 levels
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// and the saturation to 32 levels
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int hbins = 30, sbins = 32; |
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int histSize[] = {hbins, sbins}; |
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// hue varies from 0 to 179, see cvtColor
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float hranges[] = { 0, 180 }; |
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// saturation varies from 0 (black-gray-white) to
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// 255 (pure spectrum color)
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float sranges[] = { 0, 256 }; |
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const float* ranges[] = { hranges, sranges }; |
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MatND hist; |
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// we compute the histogram from the 0-th and 1-st channels
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int channels[] = {0, 1}; |
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calcHist( &hsv, 1, channels, Mat(), // do not use mask
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hist, 2, histSize, ranges, |
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true, // the histogram is uniform
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false ); |
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double maxVal=0; |
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minMaxLoc(hist, 0, &maxVal, 0, 0); |
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int scale = 10; |
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Mat histImg = Mat::zeros(sbins*scale, hbins*10, CV_8UC3); |
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for( int h = 0; h < hbins; h++ ) |
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for( int s = 0; s < sbins; s++ ) |
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{ |
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float binVal = hist.at<float>(h, s); |
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int intensity = cvRound(binVal*255/maxVal); |
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rectangle( histImg, Point(h*scale, s*scale), |
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Point( (h+1)*scale - 1, (s+1)*scale - 1), |
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Scalar::all(intensity), |
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-1 ); |
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} |
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namedWindow( "Source", 1 ); |
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imshow( "Source", src ); |
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namedWindow( "H-S Histogram", 1 ); |
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imshow( "H-S Histogram", histImg ); |
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waitKey(); |
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} |
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@ -0,0 +1,39 @@ |
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#include "opencv2/imgproc.hpp" |
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#include "opencv2/highgui.hpp" |
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using namespace cv; |
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using namespace std; |
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int main( int argc, char** argv ) |
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{ |
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Mat src; |
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// the first command-line parameter must be a filename of the binary
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// (black-n-white) image
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if( argc != 2 || !(src=imread(argv[1], 0)).data) |
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return -1; |
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Mat dst = Mat::zeros(src.rows, src.cols, CV_8UC3); |
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src = src > 1; |
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namedWindow( "Source", 1 ); |
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imshow( "Source", src ); |
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vector<vector<Point> > contours; |
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vector<Vec4i> hierarchy; |
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findContours( src, contours, hierarchy, |
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RETR_CCOMP, CHAIN_APPROX_SIMPLE ); |
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// iterate through all the top-level contours,
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// draw each connected component with its own random color
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int idx = 0; |
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for( ; idx >= 0; idx = hierarchy[idx][0] ) |
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{ |
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Scalar color( rand()&255, rand()&255, rand()&255 ); |
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drawContours( dst, contours, idx, color, FILLED, 8, hierarchy ); |
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} |
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namedWindow( "Components", 1 ); |
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imshow( "Components", dst ); |
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waitKey(0); |
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} |
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