人工智能时代快速来临，其中人脸识别是当前比较热门的技术，在国内也越来越多的运用，例如刷脸打卡，刷脸APP，身份识别，人脸门禁等。本文将为大家介绍Android基于虹软(ArcSoft)实现人脸识别的demo，快来跟随小编一起学习吧
1、在虹软的开发者中心创建一个自己的应用，将APP_ID与SDK_KEY记录下来，后面会用到。创建完后就可以下载SDK了。
2、下载完后，就可以根据SDK包里的开发说明文档和代码进行参考和学习。以下是开发说明文档中的SDK包结构的截图。
3、创建一个空项目，将SDK包里的.jar文件和.so文件复制到该项目的如下包下。接下来的配置十分重要，稍微没处理一个，就是一个头大的bug。
4、“在app里的build.gradle” 第一个红框原本是androidx的，与support是不兼容的，所以要改，因此，整个项目用到androidx的地方都需要改。第二个红框是ndk，加了这个才能找到刚才复制进去的.so文件。第三个红框也要改成如下。下面的dependencies要注意把androidx的改掉。
5、“在整个项目里的build.gradle” 记得加上jcenter()。
6、在gradle.properties里可能会有androidx的东西，也要删掉。
7、在AndroidManifest.xml中的中添加权限申请，在中添加。
manifest：
provider:
在添加后要在res下创建一个xml包，里面添加一个provider_paths.xml文件，里面的代码如下：
8、从SDK包中引入如下功能包模块和BaseActivity，并将common包下的Constants中的APP_ID，SDK_KEY改成刚才所记录下来的内容。
9、创建3个acvitity,一个是主界面，一个是人脸库的管理界面，一个是人脸识别功能界面。
10、layout包下需要引入以下5个布局文件。
11、主界面主要的功能就是激活权限、连接动态库和激活引擎，我通过修改onCreate()和util包下的ConfigUtil.class的代码，让其能够自动激活和自动修改为全方向人脸检查（其他选择好像不能够实现人脸识别）。以下是激活引擎的代码。
public void activeEngine(final View view) { if (!libraryExists) { Toast.makeText(this, "未找到库文件！", Toast.LENGTH_SHORT).show(); return; } if (!checkPermissions(NEEDED_PERMISSIONS)) { ActivityCompat.requestPermissions(this, NEEDED_PERMISSIONS, ACTION_REQUEST_PERMISSIONS); return; } if (view != null) { view.setClickable(false); } Observable.create(new ObservableOnSubscribe() { @Override public void subscribe(ObservableEmitter emitter) { int activeCode = FaceEngine.activeOnline(MainActivity.this, Constants.APP_ID, Constants.SDK_KEY); emitter.onNext(activeCode); } }) .subscribeOn(Schedulers.io()) .observeOn(AndroidSchedulers.mainThread()) .subscribe(new Observer() { @Override public void onSubscribe(Disposable d) { } @Override public void onNext(Integer activeCode) { if (activeCode == ErrorInfo.MOK) { Toast.makeText(MainActivity.this, "激活成功！", Toast.LENGTH_SHORT).show(); } else if (activeCode == ErrorInfo.MERR_ASF_ALREADY_ACTIVATED){ Toast.makeText(MainActivity.this, "已激活！", Toast.LENGTH_SHORT).show(); } else { Toast.makeText(MainActivity.this, "激活失败！", Toast.LENGTH_SHORT).show(); } if (view != null) { view.setClickable(true); } ActiveFileInfo activeFileInfo = new ActiveFileInfo(); } @Override public void onError(Throwable e) { Toast.makeText(MainActivity.this, e.getMessage(), Toast.LENGTH_SHORT).show(); if (view != null) { view.setClickable(true); } } @Override public void onComplete() { } }); } 12、人脸识别界面是最复杂的。其中不仅有人脸识别的功能，还有注册人脸和活体检测的功能。
通过手机自带的摄像头来实现人脸识别和活体检测的逻辑：
private void initCamera() { DisplayMetrics metrics = new DisplayMetrics(); getWindowManager().getDefaultDisplay().getMetrics(metrics); final FaceListener faceListener = new FaceListener() { @Override public void onFail(Exception e) { Log.e(TAG, "onFail: " + e.getMessage()); } //请求FR的回调 @Override public void onFaceFeatureInfoGet(@Nullable final FaceFeature faceFeature, final Integer requestId, final Integer errorCode) { //FR成功 if (faceFeature != null) { // Log.i(TAG, "onPreview: fr end = " + System.currentTimeMillis() + " trackId = " + requestId); Integer liveness = livenessMap.get(requestId); //不做活体检测的情况，直接搜索 if (!livenessDetect) { searchFace(faceFeature, requestId); } //活体检测通过，搜索特征 else if (liveness != null && liveness == LivenessInfo.ALIVE) { searchFace(faceFeature, requestId); } //活体检测未出结果，或者非活体，延迟执行该函数 else { if (requestFeatureStatusMap.containsKey(requestId)) { Observable.timer(WAIT_LIVENESS_INTERVAL, TimeUnit.MILLISECONDS) .subscribe(new Observer() { Disposable disposable; @Override public void onSubscribe(Disposable d) { disposable = d; getFeatureDelayedDisposables.add(disposable); } @Override public void onNext(Long aLong) { onFaceFeatureInfoGet(faceFeature, requestId, errorCode); } @Override public void onError(Throwable e) { } @Override public void onComplete() { getFeatureDelayedDisposables.remove(disposable); } }); } } } //特征提取失败 else { if (increaseAndGetValue(extractErrorRetryMap, requestId) > MAX_RETRY_TIME) { extractErrorRetryMap.put(requestId, 0); String msg; // 传入的FaceInfo在指定的图像上无法解析人脸，此处使用的是RGB人脸数据，一般是人脸模糊 if (errorCode != null && errorCode == ErrorInfo.MERR_FSDK_FACEFEATURE_LOW_CONFIDENCE_LEVEL) { msg = "人脸置信度低！"; } else { msg = "ExtractCode:" + errorCode; } faceHelper.setName(requestId, "未通过！"); // 在尝试最大次数后，特征提取仍然失败，则认为识别未通过 requestFeatureStatusMap.put(requestId, RequestFeatureStatus.FAILED); retryRecognizeDelayed(requestId); } else { requestFeatureStatusMap.put(requestId, RequestFeatureStatus.TO_RETRY); } } } @Override public void onFaceLivenessInfoGet(@Nullable LivenessInfo livenessInfo, final Integer requestId, Integer errorCode) { if (livenessInfo != null) { int liveness = livenessInfo.getLiveness(); livenessMap.put(requestId, liveness); // 非活体，重试 if (liveness == LivenessInfo.NOT_ALIVE) { faceHelper.setName(requestId, "未通过！非活体！"); // 延迟 FAIL_RETRY_INTERVAL 后，将该人脸状态置为UNKNOWN，帧回调处理时会重新进行活体检测 retryLivenessDetectDelayed(requestId); } } else { if (increaseAndGetValue(livenessErrorRetryMap, requestId) > MAX_RETRY_TIME) { livenessErrorRetryMap.put(requestId, 0); String msg; // 传入的FaceInfo在指定的图像上无法解析人脸，此处使用的是RGB人脸数据，一般是人脸模糊 if (errorCode != null && errorCode == ErrorInfo.MERR_FSDK_FACEFEATURE_LOW_CONFIDENCE_LEVEL) { msg = "人脸置信度低！"; } else { msg = "ProcessCode:" + errorCode; } faceHelper.setName(requestId, "未通过！"); retryLivenessDetectDelayed(requestId); } else { livenessMap.put(requestId, LivenessInfo.UNKNOWN); } } } }; CameraListener cameraListener = new CameraListener() { @Override public void onCameraOpened(Camera camera, int cameraId, int displayOrientation, boolean isMirror) { Camera.Size lastPreviewSize = previewSize; previewSize = camera.getParameters().getPreviewSize(); drawHelper = new DrawHelper(previewSize.width, previewSize.height, previewView.getWidth(), previewView.getHeight(), displayOrientation , cameraId, isMirror, false, false); Log.i(TAG, "onCameraOpened: " + drawHelper.toString()); // 切换相机的时候可能会导致预览尺寸发生变化 if (faceHelper == null || lastPreviewSize == null || lastPreviewSize.width != previewSize.width || lastPreviewSize.height != previewSize.height) { Integer trackedFaceCount = null; // 记录切换时的人脸序号 if (faceHelper != null) { trackedFaceCount = faceHelper.getTrackedFaceCount(); faceHelper.release(); } faceHelper = new FaceHelper.Builder() .ftEngine(ftEngine) .frEngine(frEngine) .flEngine(flEngine) .frQueueSize(MAX_DETECT_NUM) .flQueueSize(MAX_DETECT_NUM) .previewSize(previewSize) .faceListener(faceListener) .trackedFaceCount(trackedFaceCount == null ? ConfigUtil.getTrackedFaceCount(FaceRegisterAndRecognise.this.getApplicationContext()) : trackedFaceCount) .build(); } } @Override public void onPreview(final byte[] nv21, Camera camera) { if (faceRectView != null) { faceRectView.clearFaceInfo(); } List facePreviewInfoList = faceHelper.onPreviewFrame(nv21); if (facePreviewInfoList != null && faceRectView != null && drawHelper != null) { drawPreviewInfo(facePreviewInfoList); } registerFace(nv21, facePreviewInfoList); clearLeftFace(facePreviewInfoList); if (facePreviewInfoList != null && facePreviewInfoList.size() > 0 && previewSize != null) { for (int i = 0; i 注册人脸的逻辑：
private void registerFace(final byte[] nv21, final ListfacePreviewInfoList) { if (registerStatus == REGISTER_STATUS_READY && facePreviewInfoList != null && facePreviewInfoList.size() > 0) { registerStatus = REGISTER_STATUS_PROCESSING; Observable.create(new ObservableOnSubscribe () { @Override public void subscribe(ObservableEmitter emitter) { boolean success = FaceServer.getInstance().registerNv21(FaceRegisterAndRecognise.this, nv21.clone(), previewSize.width, previewSize.height, facePreviewInfoList.get(0).getFaceInfo(), "registered " + faceHelper.getTrackedFaceCount()); emitter.onNext(success); } }) .subscribeOn(Schedulers.computation()) .observeOn(AndroidSchedulers.mainThread()) .subscribe(new Observer () { @Override public void onSubscribe(Disposable d) { } @Override public void onNext(Boolean success) { String result = success ? "register success!" : "register failed!"; showToast(result); registerStatus = REGISTER_STATUS_DONE; } @Override public void onError(Throwable e) { e.printStackTrace(); showToast("register failed!"); registerStatus = REGISTER_STATUS_DONE; } @Override public void onComplete() { } }); } }
13、人脸库的管理界面。
public class FaceLibs extends BaseActivity { private ExecutorService executorService; private TextView textView; private TextView tvNotificationRegisterResult; ProgressDialog progressDialog = null; private static final int ACTION_REQUEST_PERMISSIONS = 0x001; private static String[] NEEDED_PERMISSIONS = new String[]{ Manifest.permission.READ_EXTERNAL_STORAGE, Manifest.permission.WRITE_EXTERNAL_STORAGE }; @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.activity_face_libs); getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON); executorService = Executors.newSingleThreadExecutor(); tvNotificationRegisterResult = findViewById(R.id.notification_register_result); progressDialog = new ProgressDialog(this); int faceLibNum = FaceServer.getInstance().getFaceNumber(this); textView = findViewById(R.id.number); textView.setText(faceLibNum + ""); FaceServer.getInstance().init(this); } @Override protected void onDestroy() { if (executorService != null && !executorService.isShutdown()) { executorService.shutdownNow(); } if (progressDialog != null && progressDialog.isShowing()) { progressDialog.dismiss(); } FaceServer.getInstance().unInit(); super.onDestroy(); } @Override void afterRequestPermission(int requestCode, boolean isAllGranted) { } public void clearFaces(View view) { int faceNum = FaceServer.getInstance().getFaceNumber(this); if (faceNum == 0) { showToast("人脸库已空！"); } else { AlertDialog dialog = new AlertDialog.Builder(this) .setTitle("通知") .setMessage("确定要删除" + faceNum + "个人脸吗？") .setPositiveButton("确定", new DialogInterface.OnClickListener() { @Override public void onClick(DialogInterface dialog, int which) { int deleteCount = FaceServer.getInstance().clearAllFaces(FaceLibs.this); showToast(deleteCount + "个人脸已删除！"); textView.setText("0"); } }) .setNegativeButton("取消", null) .create(); dialog.show(); } } } 14、以上就是大体的介绍，还有一些小的细枝末节需要同志们动手实操一下。下面就来看看实现的效果。
主界面：
注册成功并通过识别：
通过手机照片识别出不是活体：
清理人脸库：
以上就是Android基于虹软(ArcSoft)实现人脸识别的详细内容，更多关于Android人脸识别的资料请关注0133技术站其它相关文章！
以上就是Android基于虹软(ArcSoft)实现人脸识别的详细内容，更多请关注0133技术站其它相关文章！
