使用OpenCV Android SDK从摄像头帧实时检测人脸

在配置好 OpenCV Android SDK 之后(具体见前一篇文章Android Studio中使用OpenCV Android SDK
)，可以使用 OpenCV 封装的接口很方便地进行各种图像处理操作。

这里简单介绍如何直接使用 OpenCV 训练的人脸模型直接从摄像头帧检测人脸。

1. 新建Android Project

这里可以直接使用默认的 Android Studio 项目模板， Activity 选择 Empty Activity 。

2. 配置OpenCV Android SDK

参考前一篇文章: Android Studio中使用OpenCV Android SDK

3. 向 AndroidManifest.xml 中添加 Camera 相关的 Permission

在 AndroidManifest.xml 文件 <application> 节点前添加如下代码：

<uses-permission android:name="android.permission.CAMERA"/><uses-feature android:name="android.hardware.camera" android:required="false"/><uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/><uses-feature android:name="android.hardware.camera.front" android:required="false"/><uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>

4. 添加OpenCV训练的人脸模型

将 OpenCV Android SDK 中 sdk/etc 目录下的 lbpcascade_frontalface.xml 文件复制到项目 app/src/main/res/raw 目录下。

5. 修改 MainActivity.java 的代码

修改 MainActivity.java 的代码为:

public class MainActivity extends AppCompatActivity        implements CameraBridgeViewBase.CvCameraViewListener {    private CameraBridgeViewBase openCvCameraView;    private CascadeClassifier cascadeClassifier;    private Mat grayscaleImage;    private int absoluteFaceSize;    private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {        @Override        public void onManagerConnected(int status) {            switch (status) {                case LoaderCallbackInterface.SUCCESS:                    initializeOpenCVDependencies();                    break;                default:                    super.onManagerConnected(status);                    break;            }        }    };    private void initializeOpenCVDependencies() {        try {            // Copy the resource into a temp file so OpenCV can load it            InputStream is = getResources().openRawResource(R.raw.lbpcascade_frontalface);            File cascadeDir = getDir("cascade", Context.MODE_PRIVATE);            File 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 the cascade classifier            cascadeClassifier = new CascadeClassifier(mCascadeFile.getAbsolutePath());        } catch (Exception e) {            Log.e("OpenCVActivity", "Error loading cascade", e);        }        // And we are ready to go        openCvCameraView.enableView();    }    @Override    public void onCreate(Bundle savedInstanceState) {        super.onCreate(savedInstanceState);        getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);        openCvCameraView = new JavaCameraView(this, -1);        setContentView(openCvCameraView);        openCvCameraView.setCvCameraViewListener(this);    }    @Override    public void onCameraViewStarted(int width, int height) {        grayscaleImage = new Mat(height, width, CvType.CV_8UC4);        // The faces will be a 20% of the height of the screen        absoluteFaceSize = (int) (height * 0.2);    }    @Override    public void onCameraViewStopped() {    }    @Override    public Mat onCameraFrame(Mat aInputFrame) {        // Create a grayscale image        Imgproc.cvtColor(aInputFrame, grayscaleImage, Imgproc.COLOR_RGBA2RGB);        MatOfRect faces = new MatOfRect();        // Use the classifier to detect faces        if (cascadeClassifier != null) {            cascadeClassifier.detectMultiScale(grayscaleImage, faces, 1.1, 2, 2,                    new Size(absoluteFaceSize, absoluteFaceSize), new Size());        }        // If there are any faces found, draw a rectangle around it        Rect[] facesArray = faces.toArray();        for (int i = 0; i <facesArray.length; i++)            Core.rectangle(aInputFrame, facesArray[i].tl(), facesArray[i].br(), new Scalar(0, 255, 0, 255), 3);        return aInputFrame;    }    @Override    public void onResume() {        super.onResume();        if (!OpenCVLoader.initDebug()) {            Log.e("log_wons", "OpenCV init error");            // Handle initialization error        }        initializeOpenCVDependencies();        //OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_6, this, mLoaderCallback);    }}

6. 编译程序，运行

编译之后运行程序，程序会获取手机上的默认相机(一般为后置摄像头)并进行人脸检测。

效果：

参考资料

知乎日报: Android相机开发那些坑
Android Developers: Camera
OpenCV Documentation: OpenCV4Android SDK