private double match_eye(Rect area, Mat mTemplate, int type) {
Point matchLoc;
Mat mROI = mGray.submat(area);
int result_cols = mGray.cols() - mTemplate.cols() + 1;
int result_rows = mGray.rows() - mTemplate.rows() + 1;
if (mTemplate.cols() == 0 || mTemplate.rows() == 0) {
return 0.0;
}
mResult = new Mat(result_cols, result_rows, CvType.CV_32FC1);
switch (type) {
case TM_SQDIFF:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF);
break;
case TM_SQDIFF_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF_NORMED);
break;
case TM_CCOEFF:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF);
break;
case TM_CCOEFF_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF_NORMED);
break;
case TM_CCORR:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR);
break;
case TM_CCORR_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR_NORMED);
break;
}
Core.MinMaxLocResult mmres = Core.minMaxLoc(mResult);
if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
matchLoc = mmres.minLoc;
} else {
matchLoc = mmres.maxLoc;
}
Point matchLoc_tx = new Point(matchLoc.x + area.x, matchLoc.y + area.y);
Point matchLoc_ty =
new Point(matchLoc.x + mTemplate.cols() + area.x, matchLoc.y + mTemplate.rows() + area.y);
Core.rectangle(mRgba, matchLoc_tx, matchLoc_ty, new Scalar(255, 255, 0, 255));
if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
return mmres.maxVal;
} else {
return mmres.minVal;
}
}
/**
* @param source
* @param delta
* @return Mat
*/
public static Mat Sobel(Mat source, int delta) {
Mat grey = new Mat();
Imgproc.cvtColor(source, grey, Imgproc.COLOR_BGR2GRAY);
Mat sobelx = new Mat();
Imgproc.Sobel(grey, sobelx, CvType.CV_32F, 1, delta);
double minVal, maxVal;
Core.MinMaxLocResult minMaxLocResult = Core.minMaxLoc(sobelx);
minVal = minMaxLocResult.minVal;
maxVal = minMaxLocResult.maxVal;
Mat draw = new Mat();
sobelx.convertTo(
draw, CvType.CV_8U, 255.0 / (maxVal - minVal), -minVal * 255.0 / (maxVal - minVal));
return draw;
}
private Mat get_template(CascadeClassifier clasificator, Rect area, int size) {
Mat template = new Mat();
Mat mROI = mGray.submat(area);
MatOfRect eyes = new MatOfRect();
Point iris = new Point();
Rect eye_template = new Rect();
clasificator.detectMultiScale(
mROI,
eyes,
1.15,
2,
Objdetect.CASCADE_FIND_BIGGEST_OBJECT | Objdetect.CASCADE_SCALE_IMAGE,
new Size(30, 30),
new Size());
Rect[] eyesArray = eyes.toArray();
for (int i = 0; i < eyesArray.length; ) {
Rect e = eyesArray[i];
e.x = area.x + e.x;
e.y = area.y + e.y;
Rect eye_only_rectangle =
new Rect(
(int) e.tl().x,
(int) (e.tl().y + e.height * 0.4),
(int) e.width,
(int) (e.height * 0.6));
mROI = mGray.submat(eye_only_rectangle);
Mat vyrez = mRgba.submat(eye_only_rectangle);
Core.MinMaxLocResult mmG = Core.minMaxLoc(mROI);
Imgproc.circle(vyrez, mmG.minLoc, 2, new Scalar(255, 255, 255, 255), 2);
iris.x = mmG.minLoc.x + eye_only_rectangle.x;
iris.y = mmG.minLoc.y + eye_only_rectangle.y;
eye_template = new Rect((int) iris.x - size / 2, (int) iris.y - size / 2, size, size);
Imgproc.rectangle(mRgba, eye_template.tl(), eye_template.br(), new Scalar(255, 0, 0, 255), 2);
template = (mGray.submat(eye_template)).clone();
return template;
}
return template;
}
public void templateMatching() {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
int match_method = 5;
int max_Trackbar = 5;
Mat data = Highgui.imread("images/training_data/1" + "/data (" + 1 + ").jpg");
Mat temp = Highgui.imread("images/template.jpg");
Mat img = data.clone();
int result_cols = img.cols() - temp.cols() + 1;
int result_rows = img.rows() - temp.rows() + 1;
Mat result = new Mat(result_rows, result_cols, CvType.CV_32FC1);
Imgproc.matchTemplate(img, temp, result, match_method);
Core.normalize(result, result, 0, 1, Core.NORM_MINMAX, -1, new Mat());
double minVal;
double maxVal;
Point minLoc;
Point maxLoc;
Point matchLoc;
// minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );
Core.MinMaxLocResult res = Core.minMaxLoc(result);
if (match_method == Imgproc.TM_SQDIFF || match_method == Imgproc.TM_SQDIFF_NORMED) {
matchLoc = res.minLoc;
} else {
matchLoc = res.maxLoc;
}
// / Show me what you got
Core.rectangle(
img,
matchLoc,
new Point(matchLoc.x + temp.cols(), matchLoc.y + temp.rows()),
new Scalar(0, 255, 0));
// Save the visualized detection.
Highgui.imwrite("images/samp.jpg", img);
}
private void match_eye(Rect area, Mat mTemplate, int type) {
Point matchLoc;
Mat mROI = mGray.submat(area);
int result_cols = mROI.cols() - mTemplate.cols() + 1;
int result_rows = mROI.rows() - mTemplate.rows() + 1;
// Check for bad template size
if (mTemplate.cols() == 0 || mTemplate.rows() == 0) {
return;
}
Mat mResult = new Mat(result_cols, result_rows, CvType.CV_8U);
long nbPixels = (mResult.rows() * mResult.cols()) - getBlackPixels(mResult);
if (Math.abs(nbPixels) < 2000) {
final MediaPlayer mp = new MediaPlayer();
try {
mp.reset();
AssetFileDescriptor afd;
afd = getAssets().openFd("wakeUp.mp3");
mp.setDataSource(afd.getFileDescriptor(), afd.getStartOffset(), afd.getLength());
mp.prepare();
mp.start();
Thread.sleep(60000);
} catch (IllegalStateException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
Log.i("You are sleeping", "YOU SLEPT");
} else Log.i("M_match_eye: else ", "nbPixels = " + nbPixels);
switch (type) {
case TM_SQDIFF:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF);
break;
case TM_SQDIFF_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_SQDIFF_NORMED);
break;
case TM_CCOEFF:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF);
break;
case TM_CCOEFF_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCOEFF_NORMED);
break;
case TM_CCORR:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR);
break;
case TM_CCORR_NORMED:
Imgproc.matchTemplate(mROI, mTemplate, mResult, Imgproc.TM_CCORR_NORMED);
break;
}
Core.MinMaxLocResult mmres = Core.minMaxLoc(mResult);
// there is difference in matching methods - best match is max/min value
if (type == TM_SQDIFF || type == TM_SQDIFF_NORMED) {
matchLoc = mmres.minLoc;
} else {
matchLoc = mmres.maxLoc;
}
Point matchLoc_tx = new Point(matchLoc.x + area.x, matchLoc.y + area.y);
Point matchLoc_ty =
new Point(matchLoc.x + mTemplate.cols() + area.x, matchLoc.y + mTemplate.rows() + area.y);
Imgproc.rectangle(mRgba, matchLoc_tx, matchLoc_ty, new Scalar(255, 255, 0, 255));
Rect rec = new Rect(matchLoc_tx, matchLoc_ty);
}
