android 原生人脸检测
在android打开照相机时自动会对焦，并且能自动识别人脸，这个是利用google自带的FaceDetector做人脸检测识别 下面就简单介绍一下Fade Detector 的用法
1,照相机的打开，拍照识别时首先对摄像头进行配置
a,将摄像头Camera和SurfaceView绑定具体，在百度一搜一大堆 ,具体代码如下
@Override
protected void onPostCreate(@Nullable Bundle savedInstanceState) {
Log.e(TAG, "onPostCreate");
super.onPostCreate(savedInstanceState);
// Check for the camera permission before accessing the camera. If the
// permission is not granted yet, request permission.
SurfaceHolder holder = surfaceView.getHolder();
holder.addCallback(this);
holder.setFormat(ImageFormat.NV21);
}在surfaceHolder中 oncreate方法中打开摄像头
public void surfaceCreated(SurfaceHolder surfaceHolder) {
Log.e(TAG, "surfaceCreated");
//Find the total number of cameras available
numberOfCameras = Camera.getNumberOfCameras();
Camera.CameraInfo cameraInfo=new Camera.CameraInfo();
for (int i=0;i< Camera.getNumberOfCameras();i++){
Camera.getCameraInfo(i,cameraInfo);
if(cameraInfo.facing==Camera.CameraInfo.CAMERA_FACING_FRONT){
if(cameraId==1)
cameraId=i;
}
}
mCamera=Camera.open(cameraId);
Camera.getCameraInfo(cameraId,cameraInfo);
if(cameraInfo.facing==Camera.CameraInfo.CAMERA_FACING_FRONT){
mFaceView.setFront(true);
}
try{
mCamera.setPreviewDisplay(surfaceView.getHolder());
}catch (Exception e){
e.printStackTrace();
}
}当surfaceView调用完onCreate 之后紧接着会回调 onSeurfaceChange()函数因此在次函数中继续做摄像头的一些初始化和配置
public void surfaceChanged(SurfaceHolder surfaceHolder, int format, int width, int height) {
Log.e(TAG, "surfaceChanged");
// We have no surface, return immediately:
if (surfaceHolder.getSurface() == null) {
return;
}
// Try to stop the current preview:
try {
mCamera.stopPreview();
} catch (Exception e) {
// Ignore...
}
configureCamera(width, height);
setDisplayOrientation();
setErrorCallback();
// Create media.FaceDetector
float aspect=(float) previewHeight / (float) previewWidth;
faceDetector=new FaceDetector(prevSettingWidth,(int)(prevSettingWidth*aspect),MAX_FACE);
// Everything is configured! Finally start the camera preview again:
startPreview();
}
public void configureCamera(int width,int height){
Camera.Parameters parameters=mCamera.getParameters();
// Set the PreviewSize and AutoFocus:
setOptimalPreviewSize(parameters, width, height);
setAutoFocus(parameters);
// And set the parameters:
mCamera.setParameters(parameters);
}
private void setDisplayOrientation(){
mDisplayRotation = Utils.getDisplayRotation(FaceRGBAct.this);
mDisplayOrientation = Utils.getDisplayOrientation(mDisplayRotation, cameraId);
mCamera.setDisplayOrientation(mDisplayOrientation);
if (mFaceView != null) {
mFaceView.setDisplayOrientation(mDisplayOrientation);
}
}
private void setErrorCallback() {
mCamera.setErrorCallback(mErrorCallback);
}
private void setOptimalPreviewSize(Camera.Parameters cameraParameters,int width,int height){
List previewSizes=cameraParameters.getSupportedPreviewSizes();
float targetRatio=(float)width/height;
Camera.Size previewSize=Utils.getOptimalPreviewSize(this,previewSizes,targetRatio);
previewWidth = previewSize.width;
previewHeight = previewSize.height;
Log.e(TAG, "previewWidth" + previewWidth);
Log.e(TAG, "previewHeight" + previewHeight);
/**
* Calculate size to scale full frame bitmap to smaller bitmap
* Detect face in scaled bitmap have high performance than full bitmap.
* The smaller image size -> detect faster, but distance to detect face shorter,
* so calculate the size follow your purpose
*/
if (previewWidth / 4 > 360) {
prevSettingWidth = 360;
prevSettingHeight = 270;
} else if (previewWidth / 4 > 320) {
prevSettingWidth = 320;
prevSettingHeight = 240;
} else if (previewWidth / 4 > 240) {
prevSettingWidth = 240;
prevSettingHeight = 160;
} else {
prevSettingWidth = 160;
prevSettingHeight = 120;
}
Log.i(TAG, "****************");
Log.e(TAG, "previewWidth****" + prevSettingWidth);
Log.e(TAG, "previewHeight****" + prevSettingHeight);
cameraParameters.setPreviewSize(previewSize.width, previewSize.height);
mFaceView.setPreviewWidth(previewWidth);
mFaceView.setPreviewHeight(previewHeight);
}
关键点
onPreviewFrame回调函数，当摄像头设置好开始预览时，会不断的回调次函数，实时的将每次预览的数据通过该函数传传递回来，我们要获取图像只需要再次函数中获取就行，同时注意性能问题，因为次函数不断地会回调，因此不能做耗时的操作，需要开启子线程去处理即可,具体如下：
@Override
public void onPreviewFrame(byte[] bytes, Camera camera) {
if(!isThreadWorking){
if (counter == 0)
start = System.currentTimeMillis();
isThreadWorking=true;
waitForFdetThreadComplete();
detectThread=new FaceDetectThread(handler,this);
detectThread.setData(bytes);
detectThread.start();
}
} private class FaceDetectThread extends Thread{
private Handler handler;
private byte[] data=null;
private Context context;
private Bitmap mBitmap;
static final int REFRESH_COMPLETE=0x1112;
public FaceDetectThread(Handler handler, Context context) {
this.context = context;
this.handler = handler;
}
public void setData(byte[] data) {
this.data = data;
}
@Override
public void run() {
float aspect = (float)previewHeight / (float)previewWidth;
int w = prevSettingWidth;
int h = (int)(prevSettingWidth * aspect);
Bitmap bitmap = Bitmap.createBitmap(previewWidth, previewHeight, Bitmap.Config.RGB_565);
// face detection: first convert the image from NV21 to RGB_565
YuvImage yuv = new YuvImage(data, ImageFormat.NV21,
bitmap.getWidth(),
bitmap.getHeight(),
null);
// TODO: make rect a member and use it for width and height values above
Rect rectImage = new Rect(0, 0, bitmap.getWidth(), bitmap.getHeight());
// TODO: use a threaded option or a circular buffer for converting streams?
//see http://ostermiller.org/convert_java_outputstream_inputstream.html
ByteArrayOutputStream baout = new ByteArrayOutputStream();
if (!yuv.compressToJpeg(rectImage, 100, baout)) {
Log.e("CreateBitmap", "compressToJpeg failed");
}
BitmapFactory.Options bfo = new BitmapFactory.Options();
bfo.inPreferredConfig = Bitmap.Config.RGB_565;
bitmap = BitmapFactory.decodeStream(
new ByteArrayInputStream(baout.toByteArray()), null, bfo);
/* Log.i(TAG, "bitmapWidth****" + bitmap.getWidth());
Log.i(TAG, "bitmapHeight****" + bitmap.getHeight());
*/
Bitmap bmp = Bitmap.createScaledBitmap(bitmap, 320, 240, false);
/* Log.i(TAG, "**********************************");
Log.i(TAG, "bitmapWidth****" + bmp.getWidth());
Log.i(TAG, "bitmapHeight****" + bmp.getHeight());*/
float xScale = (float) previewWidth / (float) prevSettingWidth;
float yScale = (float) previewHeight / (float) h;
Camera.CameraInfo info = new Camera.CameraInfo();
Camera.getCameraInfo(cameraId, info);
int rotate = mDisplayOrientation;
//Log.e("***ortate***",rotate+"");
if (info.facing == Camera.CameraInfo.CAMERA_FACING_FRONT && mDisplayRotation % 180 == 0) {
if (rotate + 180 > 360) {
//Log.e("***ortate-180***",rotate+"");
rotate = rotate - 180;
} else
//Log.e("***ortate+180***",rotate+"");
rotate = rotate + 180;
}
switch (rotate) {
case 90:
bmp = ImageUtils.rotate(bmp, 90);
xScale = (float) previewHeight / bmp.getWidth();
yScale = (float) previewWidth / bmp.getHeight();
break;
case 180:
bmp = ImageUtils.rotate(bmp, 180);
break;
case 270:
bmp = ImageUtils.rotate(bmp, 270);
xScale = (float) previewHeight / (float) h;
yScale = (float) previewWidth / (float) prevSettingWidth;
break;
}
/* Log.i(TAG, "%%%%%%%%%%%%%%%%%%%%%%");
Log.i(TAG, "bitmapWidth****" + bmp.getWidth());
Log.i(TAG, "bitmapHeight****" + bmp.getHeight());*/
FaceApp.getInstance().getNetInfo().runOnThreadServer(Constant.DETECTED,bmp,mHandler);
faceDetector = new FaceDetector(bmp.getWidth(), bmp.getHeight(), MAX_FACE);
FaceDetector.Face[] fullResults = new FaceDetector.Face[MAX_FACE];
faceDetector.findFaces(bmp, fullResults);
for (int i = 0; i < MAX_FACE; i++) {
if (fullResults[i] == null) {
faces[i].clear();
} else {
PointF mid = new PointF();
fullResults[i].getMidPoint(mid);
mid.x *= xScale;
mid.y *= yScale-0.5;
float eyesDis = fullResults[i].eyesDistance() * xScale;
float confidence = fullResults[i].confidence();
float pose = fullResults[i].pose(android.media.FaceDetector.Face.EULER_Y);
int idFace = Id;
/*Rect rect = new Rect(
(int) (mid.x - eyesDis * 1.20f),
(int) (mid.y - eyesDis * 0.10f),
(int) (mid.x + eyesDis * 1.20f),
(int) (mid.y + eyesDis * 1.85f));*/
Rect rect = new Rect(
(int) (mid.x - eyesDis * 1.20f),
(int) (mid.y - eyesDis * 0.30f),
(int) (mid.x + eyesDis * 1.20f),
(int) (mid.y + eyesDis * 1.85f));
/**
* Only detect face size > 100x100
*/
if (rect.height() * rect.width() > 100 * 100) {
for (int j = 0; j < MAX_FACE; j++) {
float eyesDisPre = faces_previous[j].eyesDistance();
PointF midPre = new PointF();
faces_previous[j].getMidPoint(midPre);
RectF rectCheck = new RectF(
(midPre.x - eyesDisPre * 1.5f),
(midPre.y - eyesDisPre * 1.15f),
(midPre.x + eyesDisPre * 1.5f),
(midPre.y + eyesDisPre * 1.85f));
if (rectCheck.contains(mid.x, mid.y) &&
(System.currentTimeMillis() - faces_previous[j].getTime()) < 1000) {
idFace = faces_previous[j].getId();
break;
}
}
if (idFace == Id)
Id++;
faces[i].setFace(idFace, mid, eyesDis, confidence, pose, System.currentTimeMillis());
faces_previous[i].set(faces[i].getId(), faces[i].getMidEye(),
faces[i].eyesDistance(), faces[i].getConfidence(),
faces[i].getPose(), faces[i].getTime());
//
// if focus in a face 5 frame -> take picture face display in RecyclerView
// because of some first frame have low quality
//
if (facesCount.get(idFace) == null) {
facesCount.put(idFace, 0);
} else {
int count = facesCount.get(idFace) + 1;
if (count <= 5)
facesCount.put(idFace, count);
//
// Crop Face to display in RecylerView
//
/* if (count == 5) {
mBitmap = ImageUtils.cropFace(faces[i], bitmap, rotate);
if (mBitmap != null) {
handler.post(new Runnable() {
public void run() {
//FaceObServernotice.getInstance().notifyObserver(0,mbitmap);
mHandler.sendEmptyMessageDelayed(REFRESH_COMPLETE, 0);
// imagePreviewAdapter.add(mbitmap);
}
});
}
}*/
}
}
}
}
handler.post(new Runnable() {
public void run() {
//send face to FaceView to draw rect
mFaceView.setFaces(faces);
//calculate FPS
end = System.currentTimeMillis();
counter++;
double time = (double) (end - start) / 1000;
if (time != 0)
fps = counter / time;
mFaceView.setFPS(fps);
if (counter == (Integer.MAX_VALUE - 1000))
counter = 0;
isThreadWorking = false;
}
});
}
/*private Handler mHandler = new Handler() {
public void handleMessage(android.os.Message msg) {
switch (msg.what) {
case REFRESH_COMPLETE:
if(ScanApp.scanInfo==null){
*//* Intent intent = new Intent(FaceDetectRGBActivity.this, MainAct.class);
startActivity( intent);*//*
setResult(RESULT_OK);
}else{
Intent intent = new Intent(FaceDetectRGBActivity.this, FaceVerifyAct.class);
ByteArrayOutputStream output = new ByteArrayOutputStream();//初始化一个流对象
//把bitmap100%高质量压缩 到 output对象里
mbitmap.compress(Bitmap.CompressFormat.PNG, 100, output);
//result = output.toByteArray();//转换成功了 result就是一个bit的资源数组
intent.putExtra("bitmap",output.toByteArray());
startActivity(intent);
}
FaceDetectRGBActivity.this.finish();
break;
}
}
};*/
}
注意再此处将图片压缩为320* 240 具体可根据自己的摄像头来调试，
最后再交个FaceDetector 检测处理
具体可参照如下代码，此代码包含华为云人脸识别活体检测等功能 去掉及原生的人脸识别
https://github.com/lvzongning/android-FaceDetected/tree/5dcb9ed49387b0bbc59fd6eaad61c471c247dea8