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 checkChanges(ScreenImage img) {
if (Settings.UseImageFinder) {
if (_lastImageMat.empty()) {
_lastImageMat = Image.createMat(img.getImage());
return;
}
ImageFinder f = new ImageFinder(_lastImageMat);
f.setMinChanges(_minChanges);
org.opencv.core.Mat current = Image.createMat(img.getImage());
if (f.hasChanges(current)) {
// TODO implement ChangeObserver: processing changes
Debug.log(3, "ChangeObserver: processing changes");
}
_lastImageMat = current;
} else {
if (_lastImgMat == null) {
_lastImgMat = Image.convertBufferedImageToMat(img.getImage());
return;
}
FindInput fin = new FindInput();
fin.setSource(_lastImgMat);
Mat target = Image.convertBufferedImageToMat(img.getImage());
fin.setTarget(target);
fin.setSimilarity(_minChanges);
FindResults results = Vision.findChanges(fin);
try {
callChangeObserver(results);
} catch (AWTException e) {
Debug.error("EventMgr: checkChanges: ", e.getMessage());
}
_lastImgMat = target;
}
}
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);
}
}
@Override
public void onPictureTaken(byte[] arg0, Camera arg1) {
Bitmap bitmapPicture = BitmapFactory.decodeByteArray(arg0, 0, arg0.length);
mView.saveCurrentFilterSet(); // Store filter for later reference
// Get current running filter
if (!mView.curFilterSubset().equals("")) {
Mat imgMAT = new Mat();
Utils.bitmapToMat(bitmapPicture, imgMAT);
// If the image is empty
if (imgMAT.empty()) return; // Ignore
// Apply filters
mView.applyCurrentFilters(imgMAT);
Utils.matToBitmap(imgMAT, bitmapPicture);
} else {
// Log.i(TAG, "no filter");
}
startImageEdit(bitmapPicture);
}
public static void main(String[] args) throws InterruptedException {
// load the Core OpenCV library by name
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// create video capture device object
VideoCapture cap = new VideoCapture();
// try to use the hardware device if present
int CAM_TO_USE = 0;
// create new image objects
Mat frame = new Mat();
Mat foreground = new Mat();
Mat fg_mask = new Mat();
// create new Mixture of Gaussian BG model
BackgroundSubtractorMOG MoG = new BackgroundSubtractorMOG();
// try to open first capture device (0)
try {
cap.open(CAM_TO_USE);
} catch (Exception e1) {
System.out.println("No webcam attached");
// otherwise try opening a video file
try {
cap.open("files/video.mp4");
} catch (Exception e2) {
System.out.println("No video file found");
}
}
// if the a video capture source is now open
if (cap.isOpened()) {
// create new window objects
Imshow imsS = new Imshow("from video Source ... ");
Imshow imsF = new Imshow("Foreground");
boolean keepProcessing = true;
while (keepProcessing) {
// grab and return the next frame from video source
cap.grab();
cap.retrieve(frame);
// if the frame is valid (not end of video for example)
if (!(frame.empty())) {
// add it to the background model with a learning rate of 0.1
MoG.apply(frame, fg_mask, 0.1);
// extract the foreground mask (1 = foreground / 0 - background),
// and convert/expand it to a 3-channel version of the same
Imgproc.cvtColor(fg_mask, fg_mask, Imgproc.COLOR_GRAY2BGR);
// logically AND it with the original frame to extract colour
// pixel only in the foreground regions
Core.bitwise_and(frame, fg_mask, foreground);
// display image with a delay of 40ms (i.e. 1000 ms / 25 = 25 fps)
imsS.showImage(frame);
imsF.showImage(foreground);
Thread.sleep(40);
} else {
keepProcessing = false;
}
}
} else {
System.out.println("error cannot open any capture source - exiting");
}
// close down the camera correctly
cap.release();
}
private void detectObject() {
readLock.lock();
featureDetector.detect(img_scene, keypoints_scene);
featureDetector.detect(img_object, keypoints_object);
extractor.compute(img_object, keypoints_object, descriptors_object);
extractor.compute(img_scene, keypoints_scene, descriptors_scene);
readLock.unlock();
if (!descriptors_scene.empty()) {
matcher.match(descriptors_object, descriptors_scene, matches);
// readLock.unlock();
//
listMatches = matches.toList();
int size = descriptors_object.rows();
// -- Quick calculation of max and min distances between keypoints
for (int i = 0; i < size; i++) {
double dist = listMatches.get(i).distance;
if (dist < min_dist) {
min_dist = dist;
}
}
Log.e("Min", min_dist + "");
threeMinDist = 3 * min_dist;
listGoodMatches.removeAll(listGoodMatches);
for (int i = 0; i < size; i++) {
DMatch dMatch = listMatches.get(i);
float distance = dMatch.distance;
if (distance < threeMinDist) {
listGoodMatches.add(dMatch);
}
}
// good_matches.fromList(listGoodMatches);
Log.e("Matches", listMatches.size() + "");
Log.e("Good Matches", listGoodMatches.size() + "");
//
if (listGoodMatches.size() > 4) {
Point pointObj[] = new Point[listGoodMatches.size()];
Point pointScene[] = new Point[listGoodMatches.size()];
listKeyPointObject = keypoints_object.toList();
listKeyPointScene = keypoints_scene.toList();
// listPointScene.removeAll(listPointScene);
for (int i = 0; i < listGoodMatches.size(); i++) {
// -- Get the keypoints from the good matches
pointObj[i] = listKeyPointObject.get(listGoodMatches.get(i).queryIdx).pt;
pointScene[i] = listKeyPointScene.get(listGoodMatches.get(i).trainIdx).pt;
// listPointScene.add(listKeyPointScene.get(listGoodMatches.get(i).trainIdx).pt);
}
obj.fromArray(pointObj);
scene.fromArray(pointScene);
Log.e("Before findHomography", "");
H = Calib3d.findHomography(obj, scene, Calib3d.RANSAC, 9);
Log.e("AFTERRR findHomography", "");
pointObjConners[0] = new Point(0, 0);
pointObjConners[1] = new Point(img_object.cols(), 0);
pointObjConners[2] = new Point(img_object.cols(), img_object.rows());
pointObjConners[3] = new Point(0, img_object.rows());
obj_corners.fromArray(pointObjConners);
Core.perspectiveTransform(obj_corners, scene_corners, H);
p0 = new Point(scene_corners.toList().get(0).x, scene_corners.toList().get(0).y + 0);
p1 = new Point(scene_corners.toList().get(1).x, scene_corners.toList().get(1).y + 0);
p2 = new Point(scene_corners.toList().get(2).x, scene_corners.toList().get(2).y + 0);
p3 = new Point(scene_corners.toList().get(3).x, scene_corners.toList().get(3).y + 0);
Log.e("POINT THREAD", p0.toString() + p1.toString() + p2.toString() + p3.toString());
Log.e("detect ok", "detect ok");
}
} else {
Log.e("No descritor", "No descritor");
// readLock.unlock();
}
}
