Android OpenCV 人脸识别 Opencv3.1

只是一个简单的demo。只能检测人脸，识别率很低，以后还要实现人脸的识别，认出你是谁。以后补充。。。

1.配置环境

参考之前的文章

http://blog.csdn.net/aaron121314/article/details/53465547

2.布局

    android:layout_width="fill_parent"
    android:layout_height="fill_parent"
    android:id="@+id/HelloOpenCvView" />

3.权限

android:name="android.permission.CAMERA"/>

android:name="android.hardware.camera" android:required="false"/>
android:name="android.hardware.camera.autofocus" android:required="false"/>
android:name="android.hardware.camera.front" android:required="false"/>
android:name="android.hardware.camera.front.autofocus" android:required="false"/>

4.初始化

private CameraBridgeViewBase mOpenCvCameraView;

@Override
protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    setContentView(R.layout.activity_main);

    getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
    mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.HelloOpenCvView);
    mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
    mOpenCvCameraView.setCvCameraViewListener(this);
}

@Override
protected void onResume() {
    super.onResume();
    OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_3_0_0, this, mLoaderCallback);
}

private BaseLoaderCallback  mLoaderCallback = new BaseLoaderCallback(this) {
    @Override
    public void onManagerConnected(int status) {
        switch (status) {
            case LoaderCallbackInterface.SUCCESS:
            {
                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()) {
                        mJavaDetector = null;
                    }


                    cascadeDir.delete();

                } catch (IOException e) {
                    e.printStackTrace();
                }

                mOpenCvCameraView.enableView();
            } break;
            default:
            {
                super.onManagerConnected(status);
            } break;
        }
    }
};

到这里就可以显示Camera的画面了。

lbpcascade_frontalface.xml 这个人脸训练数据。用来检测人脸的。

5.检测人脸

实现这个listener

public class MainActivity extends AppCompatActivity implements CameraBridgeViewBase.CvCameraViewListener2

@Override
public void onCameraViewStarted(int width, int height) {
    mGray = new Mat();
    mRgba = new Mat();

mRgbaT=new Mat();

} @Override public void onCameraViewStopped() { mGray.release() ; mRgba.release() ;

mRgbaT.release();

}

   @Override
    public Mat onCameraFrame(CameraBridgeViewBase.CvCameraViewFrame inputFrame) {
        mRgba = inputFrame.rgba();
        mGray = inputFrame.gray();

        Core.transpose(mRgba,mRgbaT); //转置函数，可以水平的图像变为垂直
        Imgproc.resize(mRgbaT,mRgba, mRgba.size(), 0.0D, 0.0D, 0); //将转置后的图像缩放为mRgbaF的大小
        Core.flip(mRgba, mRgba,0); //根据x,y轴翻转，0-x 1-y

        Core.transpose(mGray,mRgbaT); //转置函数，可以水平的图像变为垂直
        Imgproc.resize(mRgbaT,mGray, mGray.size(), 0.0D, 0.0D, 0); //将转置后的图像缩放为mRgbaF的大小
        Core.flip(mGray, mGray,0); //根据x,y轴翻转，0-x 1-y

        if (mAbsoluteFaceSize == 0) {
            int height = mGray.rows();
            if (Math.round(height * mRelativeFaceSize) > 0) {
                mAbsoluteFaceSize = Math.round(height * mRelativeFaceSize);
            }
        }

        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++) {
            Log.i("a","face "+facesArray[i]);
            Imgproc.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), FACE_RECT_COLOR, 3);
        }
        return mRgba;
    }
}

然后去检测人脸。

注意：我在测试的时候，preview画面的被旋转了90度，所以这样要把图像弄正。2个参数都要旋转，mGray也要选择，要不画面是正的，但是检测不到人脸。

Core.transpose(mRgba,mRgbaT); //转置函数，可以水平的图像变为垂直
Imgproc.resize(mRgbaT,mRgba, mRgba.size(), 0.0D, 0.0D, 0); //将转置后的图像缩放为mRgbaF的大小
Core.flip(mRgba, mRgba,0); //根据x,y轴翻转，0-x 1-y

Core.transpose(mGray,mRgbaT); //转置函数，可以水平的图像变为垂直
Imgproc.resize(mRgbaT,mGray, mGray.size(), 0.0D, 0.0D, 0); //将转置后的图像缩放为mRgbaF的大小
Core.flip(mGray, mGray,0); //根据x,y轴翻转，0-x 1-y