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  在这个美即真理、全民娱乐的时代，可爱有趣的人脸贴纸在各大美颜软件中得到了广泛的应用，现在已经不仅局限于相机美颜类软件中，在社交、娱乐类的app中对人脸贴纸、AR贴纸的需求也非常广泛。本文详细介绍了集成华为HMS ML kit人脸识别实现2d贴纸的集成过程，在后面的文章中我们还会介绍3D贴纸的开发过程，欢迎大家关注哦~

场景

  在美颜相机、美图app以及社交类app(如抖音、微博、微信)等需要对拍照，或者对照片进行处理的app都会构建自己特有的贴纸的需求。

开发前准备

在项目级gradle里添加华为maven仓

  打开AndroidStudio项目级build.gradle文件

  增量添加如下maven地址：

buildscript {
    {        
       maven {url ‘http://developer.huawei.com/repo/‘}
   }    
}
allprojects {
   repositories {      
       maven { url ‘http://developer.huawei.com/repo/‘}
   }
}

在应用级的build.gradle里面加上SDK依赖

// Face detection SDK.
implementation ‘com.huawei.hms:ml-computer-vision-face:2.0.1.300‘
// Face detection model.
implementation ‘com.huawei.hms:ml-computer-vision-face-shape-point-model:2.0.1.300‘

在AndroidManifest.xml文件里面申请相机、访问网络和存储权限

<!--相机权限-->
<uses-feature android:name="android.hardware.camera" />
<uses-permission android:name="android.permission.CAMERA" />
<!--写权限-->
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
<!--读权限-->
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />

代码开发关键步骤

设置人脸检测器

MLFaceAnalyzerSetting detectorOptions;
detectorOptions = new MLFaceAnalyzerSetting.Factory()
       .setFeatureType(MLFaceAnalyzerSetting.TYPE_UNSUPPORT_FEATURES)
       .setShapeType(MLFaceAnalyzerSetting.TYPE_SHAPES)
       .allowTracing(MLFaceAnalyzerSetting.MODE_TRACING_FAST)
       .create();
detector = MLAnalyzerFactory.getInstance().getFaceAnalyzer(detectorOptions);

这里我们通过相机回调拿到相机帧数据,并通过调用人脸检测器拿到人脸轮廓点后写入FacePointEngine供贴纸滤镜使用

@Override
public void onPreviewFrame(final byte[] imgData, final Camera camera) {
   int width = mPreviewWidth;
   int height = mPreviewHeight;

   long startTime = System.currentTimeMillis();
   //设置前后摄方向一致
   if (isFrontCamera()){
       mOrientation = 0;
   }else {
       mOrientation = 2;
   }
   MLFrame.Property property =
           new MLFrame.Property.Creator()
                   .setFormatType(ImageFormat.NV21)
                   .setWidth(width)
                   .setHeight(height)
                   .setQuadrant(mOrientation)
                   .create();

   ByteBuffer data = ByteBuffer.wrap(imgData);
   // 调用人脸检测接口
   SparseArray<MLFace> faces = detector.analyseFrame(MLFrame.fromByteBuffer(data,property));
   //判断是否获取到人脸信息
   if(faces.size()>0){
       MLFace mLFace = faces.get(0);
       EGLFace EGLFace = FacePointEngine.getInstance().getOneFace(0);
       EGLFace.pitch = mLFace.getRotationAngleX();
       EGLFace.yaw = mLFace.getRotationAngleY();
       EGLFace.roll = mLFace.getRotationAngleZ() - 90;
       if (isFrontCamera())
           EGLFace.roll = -EGLFace.roll;
       if (EGLFace.vertexPoints == null) {
           EGLFace.vertexPoints = new PointF[131];
       }
       int index = 0;
       // 获取一个人的轮廓点坐标并转化到openGL归一化坐标系下的浮点值
       for (MLFaceShape contour : mLFace.getFaceShapeList()) {
           if (contour == null) {
               continue;
           }
           List<MLPosition> points = contour.getPoints();

           for (int i = 0; i < points.size(); i++) {
               MLPosition point = points.get(i);
               float x = ( point.getY() / height) * 2 - 1;
               float y = ( point.getX() / width ) * 2 - 1;
               if (isFrontCamera())
                   x = -x;
               PointF Point = new PointF(x,y);
               EGLFace.vertexPoints[index] = Point;
               index++;
           }
       }
       // 插入人脸对象
       FacePointEngine.getInstance().putOneFace(0, EGLFace);
       // 设置人脸个数
       FacePointEngine.getInstance().setFaceSize(faces!= null ? faces.size() : 0);
   }else{
       FacePointEngine.getInstance().clearAll();
   }
   long endTime = System.currentTimeMillis();
   Log.d("TAG","Face detect time: " + String.valueOf(endTime - startTime));
}

ML kit接口返回的人脸轮廓点情况如图所示：

介绍如何设计贴纸,首先看一下贴纸数JSON数据定义

public class FaceStickerJson {

   public int[] centerIndexList;   // 中心坐标索引列表，有可能是多个关键点计算中心点
   public float offsetX;           // 相对于贴纸中心坐标的x轴偏移像素
   public float offsetY;           // 相对于贴纸中心坐标的y轴偏移像素
   public float baseScale;         // 贴纸基准缩放倍数
   public int startIndex;          // 人脸起始索引，用于计算人脸的宽度
   public int endIndex;            // 人脸结束索引，用于计算人脸的宽度
   public int width;               // 贴纸宽度
   public int height;              // 贴纸高度
   public int frames;              // 贴纸帧数
   public int action;              // 动作，0表示默认显示，这里用来处理贴纸动作等
   public String stickerName;      // 贴纸名称，用于标记贴纸所在文件夹以及png文件的
   public int duration;            // 贴纸帧显示间隔
   public boolean stickerLooping;  // 贴纸是否循环渲染
   public int maxCount;            // 最大贴纸渲染次数
...
}

我们制作猫耳贴纸JSON文件,通过人脸索引找到眉心84号点和鼻尖85号点分别贴上耳朵和鼻子,然后把它和图片都放在assets目录下

{
   "stickerList": [{
       "type": "sticker",
       "centerIndexList": [84],
       "offsetX": 0.0,
       "offsetY": 0.0,
       "baseScale": 1.3024,
       "startIndex": 11,
       "endIndex": 28,
       "width": 495,
       "height": 120,
       "frames": 2,
       "action": 0,
       "stickerName": "nose",
       "duration": 100,
       "stickerLooping": 1,
       "maxcount": 5
   }, {
       "type": "sticker",
       "centerIndexList": [83],
       "offsetX": 0.0,
       "offsetY": -1.1834,
       "baseScale": 1.3453,
       "startIndex": 11,
       "endIndex": 28,
       "width": 454,
       "height": 150,
       "frames": 2,
       "action": 0,
       "stickerName": "ear",
       "duration": 100,
       "stickerLooping": 1,
       "maxcount": 5
   }]
}

这里渲染贴纸纹理我们使用GLSurfaceView,使用起来比TextureView简单, 首先在onSurfaceChanged实例化贴纸滤镜,传入贴纸路径并开启相机

@Override
public void onSurfaceCreated(GL10 gl, EGLConfig config) {

   GLES30.glClearColor(0.0f, 0.0f, 0.0f, 1.0f);
   mTextures = new int[1];
   mTextures[0] = OpenGLUtils.createOESTexture();
   mSurfaceTexture = new SurfaceTexture(mTextures[0]);
   mSurfaceTexture.setOnFrameAvailableListener(this);

   //将samplerExternalOES 输入到纹理中
   cameraFilter = new CameraFilter(this.context);

   //设置assets目录下人脸贴纸路径
   String folderPath ="cat";
   stickerFilter = new FaceStickerFilter(this.context,folderPath);

   //创建屏幕滤镜对象
   screenFilter = new BaseFilter(this.context);

   facePointsFilter = new FacePointsFilter(this.context);
   mEGLCamera.openCamera();
}

然后在onSurfaceChanged初始化贴纸滤镜

@Override
public void onSurfaceChanged(GL10 gl, int width, int height) {
   Log.d(TAG, "onSurfaceChanged. width: " + width + ", height: " + height);
   int previewWidth = mEGLCamera.getPreviewWidth();
   int previewHeight = mEGLCamera.getPreviewHeight();
   if (width > height) {
       setAspectRatio(previewWidth, previewHeight);
   } else {
       setAspectRatio(previewHeight, previewWidth);
   }
   // 设置画面的大小,创建FrameBuffer,设置显示尺寸
   cameraFilter.onInputSizeChanged(previewWidth, previewHeight);
   cameraFilter.initFrameBuffer(previewWidth, previewHeight);
   cameraFilter.onDisplaySizeChanged(width, height);

   stickerFilter.onInputSizeChanged(previewHeight, previewWidth);
   stickerFilter.initFrameBuffer(previewHeight, previewWidth);
   stickerFilter.onDisplaySizeChanged(width, height);

   screenFilter.onInputSizeChanged(previewWidth, previewHeight);
   screenFilter.initFrameBuffer(previewWidth, previewHeight);
   screenFilter.onDisplaySizeChanged(width, height);

   facePointsFilter.onInputSizeChanged(previewHeight, previewWidth);
   facePointsFilter.onDisplaySizeChanged(width, height);
   mEGLCamera.startPreview(mSurfaceTexture);
}

最后通过onDrawFrame把贴纸绘制到屏幕

@Override
public void onDrawFrame(GL10 gl) {
   int textureId;
   // 清除屏幕和深度缓存
   GLES30.glClear(GLES30.GL_COLOR_BUFFER_BIT | GLES30.GL_DEPTH_BUFFER_BIT);
   //更新获取一张图
   mSurfaceTexture.updateTexImage();
   //获取SurfaceTexture转化矩阵
   mSurfaceTexture.getTransformMatrix(mMatrix);
   //设置相机显示转化矩阵
   cameraFilter.setTextureTransformMatrix(mMatrix);

   //绘制相机纹理
   textureId = cameraFilter.drawFrameBuffer(mTextures[0],mVertexBuffer,mTextureBuffer);
   //绘制贴纸纹理
   textureId = stickerFilter.drawFrameBuffer(textureId,mVertexBuffer,mTextureBuffer);
   //绘制到屏幕
   screenFilter.drawFrame(textureId , mDisplayVertexBuffer, mDisplayTextureBuffer);
   if(drawFacePoints){
       facePointsFilter.drawFrame(textureId, mDisplayVertexBuffer, mDisplayTextureBuffer);
   }
}

这样我们的贴纸就画到人脸上了.

Demo效果

原文链接：https://developer.huawei.com/consumer/cn/forum/topicview?tid=0203324526929930082&fid=18

原作者：旭小夜

超简单集成HMS ML Kit 人脸检测实现可爱贴纸

标签：this   cts   oid   列表   isp   rri   nsf   关键点   process   

原文地址：https://blog.51cto.com/14772288/2519549