/** usage: java HoughLines imageDir\imageName TransformType */
public static void main(String[] args) {
String fileName =
args.length >= 1 ? args[0] : "pic1.png"; // if no params provided, compute the defaut image
IplImage src = cvLoadImage(fileName, 0);
IplImage dst;
IplImage colorDst;
CvMemStorage storage = cvCreateMemStorage(0);
CvSeq lines = new CvSeq();
CanvasFrame source = new CanvasFrame("Source");
CanvasFrame hough = new CanvasFrame("Hough");
if (src == null) {
System.out.println("Couldn't load source image.");
return;
}
dst = cvCreateImage(cvGetSize(src), src.depth(), 1);
colorDst = cvCreateImage(cvGetSize(src), src.depth(), 3);
cvCanny(src, dst, 50, 200, 3);
cvCvtColor(dst, colorDst, CV_GRAY2BGR);
/*
* apply the probabilistic hough transform
* which returns for each line deteced two points ((x1, y1); (x2,y2))
* defining the detected segment
*/
if (args.length == 2 && args[1].contentEquals("probabilistic")) {
System.out.println("Using the Probabilistic Hough Transform");
lines = cvHoughLines2(dst, storage, CV_HOUGH_PROBABILISTIC, 1, Math.PI / 180, 40, 50, 10);
for (int i = 0; i <= lines.total(); i++) {
// from JavaCPP, the equivalent of the C code:
// CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
// CvPoint first=line[0], second=line[1]
// is:
// CvPoint first=line.position(0), secon=line.position(1);
Pointer line = cvGetSeqElem(lines, i);
CvPoint pt1 = new CvPoint(line).position(0);
CvPoint pt2 = new CvPoint(line).position(1);
System.out.println("Line spotted: ");
System.out.println("\t pt1: " + pt1);
System.out.println("\t pt2: " + pt2);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0); // draw the segment on the image
}
}
/*
* Apply the multiscale hough transform which returns for each line two float parameters (rho, theta)
* rho: distance from the origin of the image to the line
* theta: angle between the x-axis and the normal line of the detected line
*/
else if (args.length == 2 && args[1].contentEquals("multiscale")) {
System.out.println("Using the multiscale Hough Transform"); //
lines = cvHoughLines2(dst, storage, CV_HOUGH_MULTI_SCALE, 1, Math.PI / 180, 40, 1, 1);
for (int i = 0; i < lines.total(); i++) {
CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));
float rho = point.x();
float theta = point.y();
double a = Math.cos((double) theta), b = Math.sin((double) theta);
double x0 = a * rho, y0 = b * rho;
CvPoint
pt1 =
new CvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))),
pt2 =
new CvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));
System.out.println("Line spoted: ");
System.out.println("\t rho= " + rho);
System.out.println("\t theta= " + theta);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);
}
}
/*
* Default: apply the standard hough transform. Outputs: same as the multiscale output.
*/
else {
System.out.println("Using the Standard Hough Transform");
lines = cvHoughLines2(dst, storage, CV_HOUGH_STANDARD, 1, Math.PI / 180, 90, 0, 0);
for (int i = 0; i < lines.total(); i++) {
CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));
float rho = point.x();
float theta = point.y();
double a = Math.cos((double) theta), b = Math.sin((double) theta);
double x0 = a * rho, y0 = b * rho;
CvPoint
pt1 =
new CvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))),
pt2 =
new CvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));
System.out.println("Line spotted: ");
System.out.println("\t rho= " + rho);
System.out.println("\t theta= " + theta);
cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);
}
}
source.showImage(src);
hough.showImage(colorDst);
source.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
hough.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
}
public void generatePGMFromPic(String srcPath, String file, String destPath) throws Exception {
String srcFilePath = srcPath + "/" + file;
System.out.println("Loading image from " + srcFilePath);
IplImage origImg = cvLoadImage(srcFilePath);
// convert to grayscale
IplImage grayImg = IplImage.create(origImg.width(), origImg.height(), IPL_DEPTH_8U, 1);
cvCvtColor(origImg, grayImg, CV_BGR2GRAY);
// scale the grayscale (to speed up face detection)
IplImage smallImg =
IplImage.create(grayImg.width() / SCALE, grayImg.height() / SCALE, IPL_DEPTH_8U, 1);
cvResize(grayImg, smallImg, CV_INTER_LINEAR);
// equalize the small grayscale
IplImage equImg = IplImage.create(smallImg.width(), smallImg.height(), IPL_DEPTH_8U, 1);
cvEqualizeHist(smallImg, equImg);
CvMemStorage storage = CvMemStorage.create();
CvHaarClassifierCascade cascade = new CvHaarClassifierCascade(cvLoad(CASCADE_FILE));
System.out.println("Detecting faces...");
CvSeq faces = cvHaarDetectObjects(equImg, cascade, storage, 1.1, 3, CV_HAAR_DO_CANNY_PRUNING);
cvClearMemStorage(storage);
int total = faces.total();
System.out.println("Found " + total + " face(s)");
for (int i = 0; i < total; i++) {
CvRect r = new CvRect(cvGetSeqElem(faces, i));
cvSetImageROI(
origImg, cvRect(r.x() * SCALE, r.y() * SCALE, r.width() * SCALE, r.height() * SCALE));
IplImage origface = cvCreateImage(cvSize(r.width() * SCALE, r.height() * SCALE), 8, 3);
IplImage smallface = cvCreateImage(cvSize(120, 120), 8, 3);
cvCopy(origImg, origface);
cvResize(origface, smallface, CV_INTER_LINEAR);
cvSaveImage(destPath + "/" + file + i + ".pgm", smallface);
cvResetImageROI(origImg);
}
}