public void setDetectorType(int type) {
if (mDetectorType != type) {
mDetectorType = type;
if (type == NATIVE_DETECTOR) {
Log.i(TAG, "Detection Based Tracker enabled");
mNativeDetector.start();
} else {
Log.i(TAG, "Cascade detector enabled");
mNativeDetector.stop();
}
}
}
@Override
public void run() {
super.run();
synchronized (this) {
// Explicitly deallocate Mats
if (mRgba != null) mRgba.release();
if (mGray != null) mGray.release();
if (mCascadeFile != null) mCascadeFile.delete();
if (mNativeDetector != null) mNativeDetector.release();
mRgba = null;
mGray = null;
mCascadeFile = null;
}
}
@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;
}
