public static void main(String[] args) {
// 指定读出的图片路径和输出的文件
String inputImagePath =
identificate.class.getClassLoader().getResource("hf.jpg").getPath().substring(1);
String outputImageFile = "identificate.png";
String xmlPath =
identificate
.class
.getClassLoader()
.getResource("cascade_storage.xml")
.getPath()
.substring(1);
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
CascadeClassifier faceDetector = new CascadeClassifier(xmlPath);
Mat image = Highgui.imread(inputImagePath);
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
// 画出脸的位置
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(
image,
new Point(rect.x, rect.y),
new Point(rect.x + rect.width, rect.y + rect.height),
new Scalar(0, 0, 255));
}
// 写入到文件
Highgui.imwrite(outputImageFile, image);
System.out.print("\nOK!");
}
@Override
public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
Imgproc.cvtColor(mRgba, grayScaleImage, Imgproc.COLOR_RGBA2RGB);
MatOfRect faces = new MatOfRect();
// detect faces
if (cascadeClassifier != null) {
cascadeClassifier.detectMultiScale(
grayScaleImage,
faces,
1.1,
2,
2,
new Size(absoluteFaceSize, absoluteFaceSize),
new Size());
}
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++)
Core.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), new Scalar(0, 255, 0, 255), 3);
if (facesArray.length > 0) {
facesInASecond.add(true);
} else {
facesInASecond.add(false);
}
return mRgba;
}
// 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);
}
/** Called when the activity is first created. */
@Override
public void onCreate(Bundle savedInstanceState) {
Log.i(TAG, "called onCreate");
super.onCreate(savedInstanceState);
getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
setContentView(R.layout.face_detect_surface_view);
// //
try {
// load cascade file from application resources
InputStream is = getResources().openRawResource(R.raw.lbpcascade_frontalface);
File cascadeDir = getDir("cascade", Context.MODE_PRIVATE);
mCascadeFile = new File(cascadeDir, "lbpcascade_frontalface.xml");
FileOutputStream os = new FileOutputStream(mCascadeFile);
byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
os.write(buffer, 0, bytesRead);
}
is.close();
os.close();
mJavaDetector = new CascadeClassifier(mCascadeFile.getAbsolutePath());
if (mJavaDetector.empty()) {
Log.e(TAG, "Failed to load cascade classifier");
mJavaDetector = null;
} else Log.i(TAG, "Loaded cascade classifier from " + mCascadeFile.getAbsolutePath());
mNativeDetector = new DetectionBasedTracker(mCascadeFile.getAbsolutePath(), 0); // hujiawei
cascadeDir.delete();
} catch (IOException e) {
e.printStackTrace();
Log.e(TAG, "Failed to load cascade. Exception thrown: " + e);
}
mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.fd_activity_surface_view);
mOpenCvCameraView.enableView(); //
mOpenCvCameraView.setCvCameraViewListener(this);
}
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 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);
}
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());
} 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);
return mRgba;
}
public FdView(Context context) {
super(context);
try {
InputStream is = context.getResources().openRawResource(R.raw.lbpcascade_frontalface);
File cascadeDir = context.getDir("cascade", Context.MODE_PRIVATE);
mCascadeFile = new File(cascadeDir, "lbpcascade_frontalface.xml");
FileOutputStream os = new FileOutputStream(mCascadeFile);
byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
os.write(buffer, 0, bytesRead);
}
is.close();
os.close();
// --------------------------------- load left eye classificator
// -----------------------------------
InputStream iser = context.getResources().openRawResource(R.raw.haarcascade_lefteye_2splits);
File cascadeDirER = context.getDir("cascadeER", Context.MODE_PRIVATE);
File cascadeFileER = new File(cascadeDirER, "haarcascade_eye_right.xml");
FileOutputStream oser = new FileOutputStream(cascadeFileER);
byte[] bufferER = new byte[4096];
int bytesReadER;
while ((bytesReadER = iser.read(bufferER)) != -1) {
oser.write(bufferER, 0, bytesReadER);
}
iser.close();
oser.close();
// ----------------------------------------------------------------------------------------------------
// --------------------------------- load right eye classificator
// ------------------------------------
InputStream isel = context.getResources().openRawResource(R.raw.haarcascade_lefteye_2splits);
File cascadeDirEL = context.getDir("cascadeEL", Context.MODE_PRIVATE);
File cascadeFileEL = new File(cascadeDirEL, "haarcascade_eye_left.xml");
FileOutputStream osel = new FileOutputStream(cascadeFileEL);
byte[] bufferEL = new byte[4096];
int bytesReadEL;
while ((bytesReadEL = isel.read(bufferEL)) != -1) {
osel.write(bufferEL, 0, bytesReadEL);
}
isel.close();
osel.close();
// ------------------------------------------------------------------------------------------------------
mJavaDetector = new CascadeClassifier(mCascadeFile.getAbsolutePath());
mCascadeER = new CascadeClassifier(cascadeFileER.getAbsolutePath());
mCascadeEL = new CascadeClassifier(cascadeFileER.getAbsolutePath());
if (mJavaDetector.empty() || mCascadeER.empty() || mCascadeEL.empty()) {
Log.e(TAG, "Failed to load cascade classifier");
mJavaDetector = null;
mCascadeER = null;
mCascadeEL = null;
} else Log.i(TAG, "Loaded cascade classifier from " + mCascadeFile.getAbsolutePath());
mNativeDetector = new DetectionBasedTracker(mCascadeFile.getAbsolutePath(), 0);
cascadeDir.delete();
cascadeFileER.delete();
cascadeDirER.delete();
cascadeFileEL.delete();
cascadeDirEL.delete();
} catch (IOException e) {
e.printStackTrace();
Log.e(TAG, "Failed to load cascade. Exception thrown: " + e);
}
}
@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;
}
public void run() {
System.out.println("\nRunning DetectFaceDemo");
// Create a face detector from the cascade file in the resources
// directory.
// String facefilterpath =
// getClass().getResource("../resources/haarcascade_mcs_eyepair_big.xml").getPath();
String facefilterpath = getClass().getResource("../resources/haarcascade_eye.xml").getPath();
facefilterpath = facefilterpath.substring(1, facefilterpath.length());
CascadeClassifier faceDetector = new CascadeClassifier(facefilterpath);
String pngpath = getClass().getResource("../resources/brown_eyes.jpg").getPath();
pngpath = pngpath.substring(1, pngpath.length());
Mat image = Highgui.imread(pngpath);
// Detect faces in the ismage.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect();
faceDetector.detectMultiScale(image, faceDetections);
Mat image2 = image;
Imgproc.cvtColor(image2, image, 6); // 6 = CV_BGR2GRAY not working
Imgproc.GaussianBlur(image, image, new Size(7, 7), 4, 4);
// Imgproc.medianBlur(image,image, 2);
MatOfPoint3f circles = new MatOfPoint3f();
MatOfPoint3f circles2 = new MatOfPoint3f();
Imgproc.HoughCircles(
image, circles, Imgproc.CV_HOUGH_GRADIENT, 5, image.rows() / 5, 100, 100, 10, 50);
Imgproc.HoughCircles(
image, circles2, Imgproc.CV_HOUGH_GRADIENT, 5, image.rows() / 5, 100, 100, 50, 400);
Imgproc.cvtColor(image, image, 8); // 6 = CV_BGR2GRAY not working
System.out.println(String.format("Detected %s faces", faceDetections));
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
// Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y +
// rect.height), new Scalar(0, 255, 0),100);
}
System.out.println(String.format("Detected %s circles", circles.total()));
for (Point3 circle : circles.toArray()) {
Point center = new Point(circle.x, circle.y);
int radius = (int) Math.round(circle.z);
Core.circle(image, center, 3, new Scalar(0, 255, 0), -1, 8, 0);
Core.circle(image, center, radius, new Scalar(0, 0, 255), 3, 8, 0);
// Core.circle(image, center, radius, new Scalar(0,255,0), 10,8, 0);
}
for (Point3 circle : circles2.toArray()) {
Point center = new Point(circle.x, circle.y);
int radius = (int) Math.round(circle.z);
Core.circle(image, center, 3, new Scalar(0, 255, 0), -1, 8, 0);
Core.circle(image, center, radius, new Scalar(0, 0, 255), 3, 8, 0);
// Core.circle(image, center, radius, new Scalar(0,255,0), 10,8, 0);
}
// Core.circle(image, new Point(100,100), 10, new Scalar(0,255,0), 10, 8, 0);
// Save the visualized detection.
String filename = "faceDetection.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, image);
}
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
try {
// load cascade file from application resources
InputStream is = getResources().openRawResource(R.raw.lbpcascade_frontalface);
File cascadeDir = getDir("cascade", Context.MODE_PRIVATE);
mCascadeFile = new File(cascadeDir, "lbpcascade_frontalface.xml");
FileOutputStream os = new FileOutputStream(mCascadeFile);
byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
os.write(buffer, 0, bytesRead);
}
is.close();
os.close();
// --------------------------------- load left eye
// classificator -----------------------------------
InputStream iser =
getResources().openRawResource(R.raw.haarcascade_lefteye_2splits);
File cascadeDirER = getDir("cascadeER", Context.MODE_PRIVATE);
File cascadeFileER = new File(cascadeDirER, "haarcascade_eye_right.xml");
FileOutputStream oser = new FileOutputStream(cascadeFileER);
byte[] bufferER = new byte[4096];
int bytesReadER;
while ((bytesReadER = iser.read(bufferER)) != -1) {
oser.write(bufferER, 0, bytesReadER);
}
iser.close();
oser.close();
mJavaDetector = new CascadeClassifier(mCascadeFile.getAbsolutePath());
if (mJavaDetector.empty()) {
Log.e(TAG, "Failed to load cascade classifier");
mJavaDetector = null;
} else
Log.i(TAG, "Loaded cascade classifier from " + mCascadeFile.getAbsolutePath());
mJavaDetectorEye = new CascadeClassifier(cascadeFileER.getAbsolutePath());
if (mJavaDetectorEye.empty()) {
Log.e(TAG, "Failed to load cascade classifier");
mJavaDetectorEye = null;
} else
Log.i(TAG, "Loaded cascade classifier from " + mCascadeFile.getAbsolutePath());
cascadeDir.delete();
} catch (IOException e) {
e.printStackTrace();
Log.e(TAG, "Failed to load cascade. Exception thrown: " + e);
}
mOpenCvCameraView.setCameraIndex(1);
mOpenCvCameraView.enableFpsMeter();
mOpenCvCameraView.enableView();
}
break;
default:
{
super.onManagerConnected(status);
}
break;
}
}
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;
}
