private void CreateAuxiliaryMats() {
if (mRgba.empty()) return;
mSizeRgba = mRgba.size();
int rows = (int) mSizeRgba.height;
int cols = (int) mSizeRgba.width;
int left = cols / 8;
int top = rows / 8;
int width = cols * 3 / 4;
int height = rows * 3 / 4;
if (mRgbaInnerWindow == null)
mRgbaInnerWindow = mRgba.submat(top, top + height, left, left + width);
mSizeRgbaInner = mRgbaInnerWindow.size();
if (mGrayInnerWindow == null && !mGray.empty())
mGrayInnerWindow = mGray.submat(top, top + height, left, left + width);
if (mBlurWindow == null) mBlurWindow = mRgba.submat(0, rows, cols / 3, cols * 2 / 3);
if (mZoomCorner == null)
mZoomCorner = mRgba.submat(0, rows / 2 - rows / 10, 0, cols / 2 - cols / 10);
if (mZoomWindow == null)
mZoomWindow =
mRgba.submat(
rows / 2 - 9 * rows / 100,
rows / 2 + 9 * rows / 100,
cols / 2 - 9 * cols / 100,
cols / 2 + 9 * cols / 100);
}
private void CreateAuxiliaryMats() {
if (mGray.empty()) return;
int rows = mGray.rows();
int cols = mGray.cols();
if (mZoomWindow == null) {
mZoomWindow = mRgba.submat(rows / 2 + rows / 10, rows, cols / 2 + cols / 10, cols);
mZoomWindow2 = mRgba.submat(0, rows / 2 - rows / 10, cols / 2 + cols / 10, cols);
}
}
private ArrayList<Double> applyThresholdOnImage(Mat srcImgMat, Mat outputImgMat) {
double localThreshold;
int startRow;
int endRow;
int startCol;
int endCol;
ArrayList<Double> localThresholds = new ArrayList<Double>();
int numberOfTiles = mPreference.getNumberOfTiles();
int tileWidth = (int) srcImgMat.size().height / numberOfTiles;
int tileHeight = (int) srcImgMat.size().width / numberOfTiles;
// Split image into tiles and apply threshold on each image tile separately.
// process image tiles other than the last one.
for (int tileRowCount = 0; tileRowCount < numberOfTiles; tileRowCount++) {
startRow = tileRowCount * tileWidth;
if (tileRowCount < numberOfTiles - 1) endRow = (tileRowCount + 1) * tileWidth;
else endRow = (int) srcImgMat.size().height;
for (int tileColCount = 0; tileColCount < numberOfTiles; tileColCount++) {
startCol = tileColCount * tileHeight;
if (tileColCount < numberOfTiles - 1) endCol = (tileColCount + 1) * tileHeight;
else endCol = (int) srcImgMat.size().width;
Mat tileThreshold = new Mat();
Mat tileMat = srcImgMat.submat(startRow, endRow, startCol, endCol);
// localThreshold = Imgproc.threshold(tileMat, tileThreshold, 0, 255, Imgproc.THRESH_BINARY
// | Imgproc.THRESH_OTSU);
// RNM: Adaptive threshold rules!
localThreshold = 0x80;
Imgproc.adaptiveThreshold(
tileMat,
tileThreshold,
255,
Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C,
Imgproc.THRESH_BINARY,
91,
2);
Mat copyMat = outputImgMat.submat(startRow, endRow, startCol, endCol);
tileThreshold.copyTo(copyMat);
tileThreshold.release();
localThresholds.add(localThreshold);
}
}
return localThresholds;
}
private void displayMarkerImage(Mat srcImgMat, Mat destImageMat) {
// find location of image segment to be replaced in the destination image.
Rect rect = calculateImageSegmentArea(destImageMat);
Mat destSubmat = destImageMat.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
// copy image.
srcImgMat.copyTo(destSubmat);
}
public static Mat findCardNumber(String path) {
Mat mat = Highgui.imread(path);
int x = 0;
int y = (int) (mat.height() * ((double) 30 / 54));
int width = mat.cols();
int height = (int) (mat.height() * ((double) 7 / 54));
return mat.submat(new Rect(x, y, width, height));
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
if (mIsColorSelected) {
abc = mDetector.process(mRgba);
// hehe.setText(abc.toString());
List<MatOfPoint> contours = mDetector.getContours();
Log.e(TAG, "Contours count: " + contours.size());
Imgproc.drawContours(mRgba, contours, -1, CONTOUR_COLOR);
Mat colorLabel = mRgba.submat(4, 68, 4, 68);
colorLabel.setTo(mBlobColorRgba);
Mat spectrumLabel = mRgba.submat(4, 4 + mSpectrum.rows(), 70, 70 + mSpectrum.cols());
mSpectrum.copyTo(spectrumLabel);
}
return mRgba;
}
private void copyThresholdedImageToRgbImgMat(Mat thresholdedImgMat, Mat dest) {
// convert thresholded image segment to RGB.
Mat smallRegionImg = new Mat();
Imgproc.cvtColor(thresholdedImgMat, smallRegionImg, Imgproc.COLOR_GRAY2BGRA, 4);
// find location of image segment to be replaced in the destination image.
Rect rect = calculateImageSegmentArea(dest);
Mat destSubmat = dest.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
// copy image.
smallRegionImg.copyTo(destSubmat);
smallRegionImg.release();
}
@Override
public void onPreviewFrame(byte[] data, Camera camera) {
if (mDetecting == true) return;
mDetecting = true;
mFrameBuffer.put(0, 0, data);
Message msg = Message.obtain();
msg.obj = mFrameBuffer.submat(0, mFrameWidth, 0, mFrameHeight);
mHandler.sendMessage(msg);
}
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;
}
private Mat buildROI(Mat src) {
int offset = mZoomImg.getWidth();
int rows = src.rows();
int cols = src.cols();
Mat sub =
src.submat(
rows / 2 - offset / 2,
rows / 2 + offset / 2,
cols / 2 - offset / 2,
cols / 2 + offset / 2);
return sub;
}
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;
}
}
// OpenCV code
private void modifyImage(String fileName) {
// Create a face detector from the cascade file
CascadeClassifier faceDetector = new CascadeClassifier("haarcascade_frontalface_alt.xml");
Mat image = Highgui.imread(fileName);
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
// Blur each face
for (Rect rect : faceDetections.toArray()) {
Mat faceArea = image.submat(rect);
Imgproc.blur(faceArea, faceArea, new Size(30, 30));
}
// Save the modified image
Highgui.imwrite("edited_" + fileName, image);
}
@Override
protected Bitmap processFrame(VideoCapture capture) {
capture.retrieve(mRgba, Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA);
capture.retrieve(mGray, Highgui.CV_CAP_ANDROID_GREY_FRAME);
if (mAbsoluteFaceSize == 0) {
int height = mGray.rows();
if (Math.round(height * mRelativeFaceSize) > 0) ;
{
mAbsoluteFaceSize = Math.round(height * mRelativeFaceSize);
}
mNativeDetector.setMinFaceSize(mAbsoluteFaceSize);
}
MatOfRect faces = new MatOfRect();
if (mDetectorType == JAVA_DETECTOR) {
if (mJavaDetector != null)
mJavaDetector.detectMultiScale(
mGray,
faces,
1.1,
2,
2 // TODO: objdetect.CV_HAAR_SCALE_IMAGE
,
new Size(mAbsoluteFaceSize, mAbsoluteFaceSize),
new Size());
if (mZoomCorner == null || mZoomWindow == null) CreateAuxiliaryMats();
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++) {
Rect r = facesArray[i];
Core.rectangle(mGray, r.tl(), r.br(), new Scalar(0, 255, 0, 255), 3);
Core.rectangle(mRgba, r.tl(), r.br(), new Scalar(0, 255, 0, 255), 3);
eyearea =
new Rect(
r.x + r.width / 8,
(int) (r.y + (r.height / 4.5)),
r.width - 2 * r.width / 8,
(int) (r.height / 3.0));
Core.rectangle(mRgba, eyearea.tl(), eyearea.br(), new Scalar(255, 0, 0, 255), 2);
Rect eyearea_right =
new Rect(
r.x + r.width / 16,
(int) (r.y + (r.height / 4.5)),
(r.width - 2 * r.width / 16) / 2,
(int) (r.height / 3.0));
Rect eyearea_left =
new Rect(
r.x + r.width / 16 + (r.width - 2 * r.width / 16) / 2,
(int) (r.y + (r.height / 4.5)),
(r.width - 2 * r.width / 16) / 2,
(int) (r.height / 3.0));
Core.rectangle(mRgba, eyearea_left.tl(), eyearea_left.br(), new Scalar(255, 0, 0, 255), 2);
Core.rectangle(
mRgba, eyearea_right.tl(), eyearea_right.br(), new Scalar(255, 0, 0, 255), 2);
if (learn_frames < 5) {
teplateR = get_template(mCascadeER, eyearea_right, 24);
teplateL = get_template(mCascadeEL, eyearea_left, 24);
learn_frames++;
} else {
match_value = match_eye(eyearea_right, teplateR, FdActivity.method);
match_value = match_eye(eyearea_left, teplateL, FdActivity.method);
;
}
Imgproc.resize(mRgba.submat(eyearea_left), mZoomWindow2, mZoomWindow2.size());
Imgproc.resize(mRgba.submat(eyearea_right), mZoomWindow, mZoomWindow.size());
}
} else if (mDetectorType == NATIVE_DETECTOR) {
if (mNativeDetector != null) mNativeDetector.detect(mGray, faces);
} else {
Log.e(TAG, "Detection method is not selected!");
}
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++)
Core.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), FACE_RECT_COLOR, 3);
Bitmap bmp = Bitmap.createBitmap(mRgba.cols(), mRgba.rows(), Bitmap.Config.ARGB_8888);
try {
Utils.matToBitmap(mRgba, bmp);
} catch (Exception e) {
Log.e(TAG, "Utils.matToBitmap() throws an exception: " + e.getMessage());
bmp.recycle();
bmp = null;
}
return bmp;
}
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);
}
public boolean onTouch(View v, MotionEvent event) {
int cols = mRgba.cols();
int rows = mRgba.rows();
int xOffset = (mOpenCvCameraView.getWidth() - cols) / 2;
int yOffset = (mOpenCvCameraView.getHeight() - rows) / 2;
int x = (int) event.getX() - xOffset;
int y = (int) event.getY() - yOffset;
Log.i(TAG, "Touch image coordinates: (" + x + ", " + y + ")");
if ((x < 0) || (y < 0) || (x > cols) || (y > rows)) return false;
Rect touchedRect = new Rect();
touchedRect.x = (x > 4) ? x - 4 : 0;
touchedRect.y = (y > 4) ? y - 4 : 0;
touchedRect.width = (x + 4 < cols) ? x + 4 - touchedRect.x : cols - touchedRect.x;
touchedRect.height = (y + 4 < rows) ? y + 4 - touchedRect.y : rows - touchedRect.y;
Mat touchedRegionRgba = mRgba.submat(touchedRect);
Mat touchedRegionHsv = new Mat();
Imgproc.cvtColor(touchedRegionRgba, touchedRegionHsv, Imgproc.COLOR_RGB2HSV_FULL);
// Calculate average color of touched region
mBlobColorHsv = Core.sumElems(touchedRegionHsv);
int pointCount = touchedRect.width * touchedRect.height;
for (int i = 0; i < mBlobColorHsv.val.length; i++) mBlobColorHsv.val[i] /= pointCount;
mBlobColorRgba = converScalarHsv2Rgba(mBlobColorHsv);
Log.i(
TAG,
"Touched rgba color: ("
+ mBlobColorRgba.val[0]
+ ", "
+ mBlobColorRgba.val[1]
+ ", "
+ mBlobColorRgba.val[2]
+ ", "
+ mBlobColorRgba.val[3]
+ ")");
mDetector.setHsvColor(mBlobColorHsv);
Imgproc.resize(mDetector.getSpectrum(), mSpectrum, SPECTRUM_SIZE);
mIsColorSelected = true;
final Handler handler = new Handler();
Runnable runable =
new Runnable() {
@Override
public void run() {
try {
// do your code here
hehe.setText(abc.toString());
if (abc > 16000 && abc < 25000) {
imageView.setImageResource(R.drawable.green1);
} else {
imageView.setImageResource(R.drawable.red1);
}
// also call the same runnable
handler.postDelayed(this, 1000);
} catch (Exception e) {
// TODO: handle exception
} finally {
// also call the same runnable
// handler.postDelayed(this, 1000);
}
}
};
handler.postDelayed(runable, 1000);
touchedRegionRgba.release();
touchedRegionHsv.release();
return false; // don't need subsequent touch events
}
public void hpFind(Mat mRgba, Mat mGray, WorkingHeadPose hp, Rect[] facesArray)
// public void hpFind(Mat mRgba,Mat mGray,HeadPose hp)
{
int i;
Log.i("HeadPose", "hpFind:Total Faces Found" + facesArray.length);
if (hp.hpstatus == HeadPoseStatus.NONE) {
if (facesArray.length < 1) return;
TempFace = facesArray.clone();
hp.cornerCount = hp.maxCorners;
Rect roi =
new Rect(
(int) facesArray[0].tl().x,
(int) (facesArray[0].tl().y),
facesArray[0].width,
(int) (facesArray[0].height)); // imran
Mat cropped = new Mat();
Mat GrayClone = new Mat();
GrayClone = mGray.clone();
cropped = GrayClone.submat(roi);
hpFindCorners(cropped, hp);
// mGray is untouched
// ******** working fine upto here
// Map face points to model
if (hp.cornerCount < 4) return;
Vector<Point3> points = new Vector<Point3>();
if (hp.corners.total()
> 0) // adding to make sure, copying is done perfectly.imran,was getting exception
{
Log.i("hpFind+", "hp.corners.total()" + hp.corners.total());
Log.i("hpFind+", "hp.cornerCount" + hp.cornerCount);
// Point3 temp1;//=new Point3();
for (i = 0; i < hp.cornerCount; i++) {
if (i == hp.corners.total()) break;
// Log.i("hpFind+","Itertion"+i);
points.add(
new Point3(
(hp.corners.toList().get(i).x / facesArray[0].width) - 0.5,
-(hp.corners.toList().get(i).y / facesArray[0].height) + 0.5,
0.5 * Math.sin(PI * (hp.corners.toList().get(i).x / facesArray[0].width))));
// modelPoints.toList().set(i,
// hpmodel(hp.corners.toList().get(i).x/facesArray[0].width,hp.corners.toList().get(i).x/facesArray[0].height));
// temp1=new Point3((hp.corners.toList().get(i).x/facesArray[0].width) -
// 0.5,-(hp.corners.toList().get(i).y/facesArray[0].height) + 0.5, 0.5 * Math.sin(PI
// *(hp.corners.toList().get(i).x/facesArray[0].width)));
// modelPoints. .p .toList().set .set(i,temp1);
}
modelPoints.fromList(points);
}
// imran example from marker.java , search for Point3f
// Traslate corners from face coordinated to image coordinates
for (i = 0; i < hp.cornerCount; i++) {
if (i == hp.corners.total()) break;
hp.corners.toList().get(i).x += facesArray[0].tl().x;
hp.corners.toList().get(i).y += facesArray[0].br().y;
// hp.corners.toList().set(i, hp.corners.toList().get(i)+facesArray[0].tl().x);
}
hp.corners.copyTo(hp.tempcorners); // .clone();
// Change status
hp.hpstatus = HeadPoseStatus.KEYFRAME;
} else {
if (facesArray.length > 1)
TempFace = facesArray.clone(); // imran assigning here also,to better measure
MatOfPoint2f corners2f = new MatOfPoint2f();
hp.corners.convertTo(corners2f, CvType.CV_32FC2);
hp.previousCorners = corners2f;
corners2f.convertTo(hp.corners, CvType.CV_32S);
hpTrack(mRgba, hp, facesArray);
Point center = new Point();
if (hp.cornerCount < 4) {
hp.hpstatus = HeadPoseStatus.NONE;
return;
}
hp.hpstatus = HeadPoseStatus.TRACKING;
}
if (hp.previousFrame == null) // imran
{
// hp.previousFrame =new Mat(mRgba.width(),mRgba.height(),CvType);
hp.previousFrame = new Mat(mRgba.size(), CvType.CV_8UC4);
}
mRgba.copyTo(hp.previousFrame);
// cvCopy(frame, headPose->previousFrame, NULL);
}
private Mat cloneMarkerImageSegment(Mat imgMat) {
Rect rect = calculateImageSegmentArea(imgMat);
Mat calculatedImg = imgMat.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
return calculatedImg.clone();
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
mGray = inputFrame.gray();
if (mAbsoluteFaceSize == 0) {
int height = mGray.rows();
if (Math.round(height * mRelativeFaceSize) > 0) {
mAbsoluteFaceSize = Math.round(height * mRelativeFaceSize);
}
}
if (mZoomWindow == null || mZoomWindow2 == null) CreateAuxiliaryMats();
MatOfRect faces = new MatOfRect();
if (mJavaDetector != null)
mJavaDetector.detectMultiScale(
mGray,
faces,
1.1,
2,
2, // TODO: objdetect.CV_HAAR_SCALE_IMAGE
new Size(mAbsoluteFaceSize, mAbsoluteFaceSize),
new Size());
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++) {
Imgproc.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), FACE_RECT_COLOR, 3);
xCenter = (facesArray[i].x + facesArray[i].width + facesArray[i].x) / 2;
yCenter = (facesArray[i].y + facesArray[i].y + facesArray[i].height) / 2;
Point center = new Point(xCenter, yCenter);
Imgproc.circle(mRgba, center, 10, new Scalar(255, 0, 0, 255), 3);
Imgproc.putText(
mRgba,
"[" + center.x + "," + center.y + "]",
new Point(center.x + 20, center.y + 20),
Core.FONT_HERSHEY_SIMPLEX,
0.7,
new Scalar(255, 255, 255, 255));
Rect r = facesArray[i];
// compute the eye area
Rect eyearea =
new Rect(
r.x + r.width / 8,
(int) (r.y + (r.height / 4.5)),
r.width - 2 * r.width / 8,
(int) (r.height / 3.0));
// split it
Rect eyearea_right =
new Rect(
r.x + r.width / 16,
(int) (r.y + (r.height / 4.5)),
(r.width - 2 * r.width / 16) / 2,
(int) (r.height / 3.0));
Rect eyearea_left =
new Rect(
r.x + r.width / 16 + (r.width - 2 * r.width / 16) / 2,
(int) (r.y + (r.height / 4.5)),
(r.width - 2 * r.width / 16) / 2,
(int) (r.height / 3.0));
// draw the area - mGray is working grayscale mat, if you want to
// see area in rgb preview, change mGray to mRgba
Imgproc.rectangle(mRgba, eyearea_left.tl(), eyearea_left.br(), new Scalar(255, 0, 0, 255), 2);
Imgproc.rectangle(
mRgba, eyearea_right.tl(), eyearea_right.br(), new Scalar(255, 0, 0, 255), 2);
if (learn_frames < 5) {
teplateR = get_template(mJavaDetectorEye, eyearea_right, 24);
teplateL = get_template(mJavaDetectorEye, eyearea_left, 24);
learn_frames++;
} else {
// Learning finished, use the new templates for template
// matching
match_eye(eyearea_right, teplateR, method);
match_eye(eyearea_left, teplateL, method);
}
// cut eye areas and put them to zoom windows
Imgproc.resize(mRgba.submat(eyearea_left), mZoomWindow2, mZoomWindow2.size());
Imgproc.resize(mRgba.submat(eyearea_right), mZoomWindow, mZoomWindow.size());
}
return mRgba;
}