Android打开相机进行人脸识别，使用虹软人脸识别引擎
上一张效果图，渣画质，能看就好
功能说明：
人脸识别使用的是虹软的FreeSDK，包含人脸追踪，人脸检测，人脸识别，年龄、性别检测功能，其中本demo只使用了FT和FR（人脸追踪和人脸识别），封装了开启相机和人脸追踪、识别功能在FaceCameraHelper中。
实现逻辑：
打开相机，监听预览数据回调进行人脸追踪，且为每个检测到的人脸都分配一个trackID（上下帧位置变化不大的人脸框可认为是同一个人脸，具体实现的逻辑可见代码），同时，为了人脸搜索，为每个trackID都分配一个状态（识别中，识别失败，识别通过）、姓名，识别通过则在人脸框上显示姓名，否则只显示trackID（本demo没配服务端，只做了模拟操作）。流程说明见下图。
FaceCameraHelper包含的接口：
public interface FaceTrackListener {
/**
* 回传相机预览数据和人脸框位置
*
* @param nv21 相机预览数据
* @param ftFaceList 待处理的人脸列表
* @param trackIdList 人脸追踪ID列表
*/
void onPreviewData(byte[] nv21, List<AFT_FSDKFace> ftFaceList, List<Integer> trackIdList);
/**
* 当出现异常时执行
*
* @param e 异常信息
*/
void onFail(Exception e);
/**
* 当相机打开时执行
*
* @param camera 相机实例
*/
void onCameraOpened(Camera camera);
/**
* 根据自己的需要可以删除部分人脸，比如指定区域、留下最大人脸等
*
* @param ftFaceList 人脸列表
* @param trackIdList 人脸追踪ID列表
*/
void adjustFaceRectList(List<AFT_FSDKFace> ftFaceList, List<Integer> trackIdList);
/**
* 请求人脸特征后的回调
*
* @param frFace 人脸特征数据
* @param requestId 请求码
*/
void onFaceFeatureInfoGet(@Nullable AFR_FSDKFace frFace, Integer requestId);
}
```
FT人脸框绘制并回调数据：
@Override
public void onPreviewFrame(byte[] nv21, Camera camera) {
if (faceTrackListener != null) {
ftFaceList.clear();
int ftCode = ftEngine.AFT_FSDK_FaceFeatureDetect(nv21, previewSize.width, previewSize.height, AFT_FSDKEngine.CP_PAF_NV21, ftFaceList).getCode();
if (ftCode != 0) {
faceTrackListener.onFail(new Exception("ft failed,code is " + ftCode));
}
refreshTrackId(ftFaceList);
faceTrackListener.adjustFaceRectList(ftFaceList, currentTrackIdList);
if (surfaceViewRect != null) {
Canvas canvas = surfaceViewRect.getHolder().lockCanvas();
if (canvas == null) {
faceTrackListener.onFail(new Exception("can not get canvas of surfaceViewRect"));
return;
}
canvas.drawColor(0, PorterDuff.Mode.CLEAR);
if (ftFaceList.size() > 0) {
for (int i = 0; i < ftFaceList.size(); i++) {
Rect adjustedRect = TrackUtil.adjustRect(new Rect(ftFaceList.get(i).getRect()), previewSize.width, previewSize.height, surfaceWidth, surfaceHeight, cameraOrientation, mCameraId);
TrackUtil.drawFaceRect(canvas, adjustedRect, faceRectColor, faceRectThickness, currentTrackIdList.get(i), nameMap.get(currentTrackIdList.get(i)));
}
}
surfaceViewRect.getHolder().unlockCanvasAndPost(canvas);
}
faceTrackListener.onPreviewData(nv21, ftFaceList, currentTrackIdList);
}
}
大多数设备相机预览数据图像的朝向在横屏时为0度。其他情况按逆时针依次增加90度，因此人脸框的绘制需要做同步转化。CameraID为0时，也就是后置摄像头情况，相机预览数据的显示为原画面，而CameraID为1时，也就是前置摄像头情况，相机的预览画面显示为镜像画面，适配的代码：
/**
* @param rect FT人脸框
* @param previewWidth 相机预览的宽度
* @param previewHeight 相机预览高度
* @param canvasWidth 画布的宽度
* @param canvasHeight 画布的高度
* @param cameraOri 相机预览方向
* @param mCameraId 相机ID
* @return
*/
static Rect adjustRect(Rect rect, int previewWidth, int previewHeight, int canvasWidth, int canvasHeight, int cameraOri, int mCameraId) {
if (rect == null) {
return null;
}
if (canvasWidth < canvasHeight) {
int t = previewHeight;
previewHeight = previewWidth;
previewWidth = t;
}
float horizontalRatio;
float verticalRatio;
if (cameraOri == 0 || cameraOri == 180) {
horizontalRatio = (float) canvasWidth / (float) previewWidth;
verticalRatio = (float) canvasHeight / (float) previewHeight;
} else {
horizontalRatio = (float) canvasHeight / (float) previewHeight;
verticalRatio = (float) canvasWidth / (float) previewWidth;
}
rect.left *= horizontalRatio;
rect.right *= horizontalRatio;
rect.top *= verticalRatio;
rect.bottom *= verticalRatio;
Rect newRect = new Rect();
switch (cameraOri) {
case 0:
if (mCameraId == Camera.CameraInfo.CAMERA_FACING_FRONT) {
newRect.left = canvasWidth - rect.right;
newRect.right = canvasWidth - rect.left;
} else {
newRect.left = rect.left;
newRect.right = rect.right;
}
newRect.top = rect.top;
newRect.bottom = rect.bottom;
break;
case 90:
newRect.right = canvasWidth - rect.top;
newRect.left = canvasWidth - rect.bottom;
if (mCameraId == Camera.CameraInfo.CAMERA_FACING_FRONT) {
newRect.top = canvasHeight - rect.right;
newRect.bottom = canvasHeight - rect.left;
} else {
newRect.top = rect.left;
newRect.bottom = rect.right;
}
break;
case 180:
newRect.top = canvasHeight - rect.bottom;
newRect.bottom = canvasHeight - rect.top;
if (mCameraId == Camera.CameraInfo.CAMERA_FACING_FRONT) {
newRect.left = rect.left;
newRect.right = rect.right;
} else {
newRect.left = canvasWidth - rect.right;
newRect.right = canvasWidth - rect.left;
}
break;
case 270:
newRect.left = rect.top;
newRect.right = rect.bottom;
if (mCameraId == Camera.CameraInfo.CAMERA_FACING_FRONT) {
newRect.top = rect.left;
newRect.bottom = rect.right;
} else {
newRect.top = canvasHeight - rect.right;
newRect.bottom = canvasHeight - rect.left;
}
break;
default:
break;
}
return newRect;
}
由于FR引擎不支持多线程调用，因此只能串行执行，若需要更高效的实现，可创建多个FREngine实例进行任务分配。
FR线程队列：
private LinkedBlockingQueue<FaceRecognizeRunnable> faceRecognizeRunnables = new LinkedBlockingQueue<FaceRecognizeRunnable>(MAX_FRTHREAD_COUNT);
FR线程：
public class FaceRecognizeRunnable implements Runnable {
private Rect faceRect;
private int width;
private int height;
private int format;
private int ori;
private Integer requestId;
private byte[]nv21Data;
public FaceRecognizeRunnable(byte[]nv21Data,Rect faceRect, int width, int height, int format, int ori, Integer requestId) {
if (nv21Data==null) {
return;
}
this.nv21Data = new byte[nv21Data.length];
System.arraycopy(nv21Data,0,this.nv21Data,0,nv21Data.length);
this.faceRect = new Rect(faceRect);
this.width = width;
this.height = height;
this.format = format;
this.ori = ori;
this.requestId = requestId;
}
@Override
public void run() {
if (faceTrackListener!=null && nv21Data!=null) {
if (frEngine != null) {
AFR_FSDKFace frFace = new AFR_FSDKFace();
int frCode = frEngine.AFR_FSDK_ExtractFRFeature(nv21Data, width, height, format, faceRect, ori, frFace).getCode();
if (frCode == 0) {
faceTrackListener.onFaceFeatureInfoGet(frFace, requestId);
} else {
faceTrackListener.onFaceFeatureInfoGet(null, requestId);
faceTrackListener.onFail(new Exception("fr failed errorCode is " + frCode));
}
nv21Data = null;
}else {
faceTrackListener.onFaceFeatureInfoGet(null, requestId);
faceTrackListener.onFail(new Exception("fr failed ,frEngine is null" ));
}
if (faceRecognizeRunnables.size()>0){
executor.execute(faceRecognizeRunnables.poll());
}
}
}
}
上下帧是否为相同人脸的判断（trackID刷新）：
/**
* 刷新trackId
*
* @param ftFaceList 传入的人脸列表
*/
public void refreshTrackId(List<AFT_FSDKFace> ftFaceList) {
currentTrackIdList.clear();
//每项预先填充-1
for (int i = 0; i < ftFaceList.size(); i++) {
currentTrackIdList.add(-1);
}
//前一次无人脸现在有人脸，填充新增TrackId
if (formerTrackIdList.size() == 0) {
for (int i = 0; i < ftFaceList.size(); i++) {
currentTrackIdList.set(i, ++currentTrackId);
}
} else {
//前后都有人脸,对于每一个人脸框
for (int i = 0; i < ftFaceList.size(); i++) {
//遍历上一次人脸框
for (int j = 0; j < formerFaceRectList.size(); j++) {
//若是同一张人脸
if (TrackUtil.isSameFace(SIMILARITY_RECT, formerFaceRectList.get(j), ftFaceList.get(i).getRect())) {
//记录ID
currentTrackIdList.set(i, formerTrackIdList.get(j));
break;
}
}
}
}
//上一次人脸框不存在此人脸
for (int i = 0; i < currentTrackIdList.size(); i++) {
if (currentTrackIdList.get(i) == -1) {
currentTrackIdList.set(i, ++currentTrackId);
}
}
formerTrackIdList.clear();
formerFaceRectList.clear();
for (int i = 0; i < ftFaceList.size(); i++) {
formerFaceRectList.add(new Rect(ftFaceList.get(i).getRect()));
formerTrackIdList.add(currentTrackIdList.get(i));
}
}
项目地址：https://github.com/wangshengyang1996/FaceTrackDemo
若有不当的地方望指出。
