前言
最近多个项目需要接入人脸识别功能，之前的方案是使用百度云api集成，但是后续部分项目是内网部署及使用，考虑到接入复杂程度及收费等多种因素，决定参考开源方案自己搭建，保证服务的稳定性与可靠性
项目地址：https://gitee.com/code2roc/fastface
设计
经过检索对别多个方案后，使用了基于seetaface6+springboot的方式进行搭建，能够无缝接入应用
seetaface6是中科视拓最新开源的商业正式版本，包含人脸识别的基本能力：人脸检测、关键点定位、人脸识别，同时增加了活体检测、质量评估、年龄性别估计
官网地址：https://github.com/SeetaFace6Open/index
使用对接的sdk是tracy100大神的封装，支持 jdk8-jdk14，支持windows和Linux，无需考虑部署问题，直接使用jar包实现业务即可，内部同时封装了bean对象spring能够开箱即用
官网地址：https://github.com/tracy100/seetaface6SDK
系统目标实现人脸注册，人脸比对，人脸查找基础功能即可
实现
引用jar包
<dependency><groupId>com.seeta.sdk</groupId><artifactId>seeta-sdk-platform</artifactId><scope>system</scope><version>1.2.1</version><systemPath>${project.basedir}/lib/seetaface.jar</systemPath></dependency>
bean对象注册
FaceDetectorProxy为人脸检测bean，能够检测图像中是否有人脸
FaceRecognizerProxy为人脸比对bean，能够比对两张人脸的相似度
FaceLandmarkerProxy为人脸关键点bean，能够检测人脸的关键点，支持5个点和68个点
@Configuration
public class FaceConfig {@Value("${face.modelPath}")private String modelPath;@Beanpublic FaceDetectorProxy faceDetector() throws FileNotFoundException {SeetaConfSetting detectorPoolSetting = new SeetaConfSetting(new SeetaModelSetting(0, new String[]{modelPath + File.separator + "face_detector.csta"}, SeetaDevice.SEETA_DEVICE_CPU));FaceDetectorProxy faceDetectorProxy = new FaceDetectorProxy(detectorPoolSetting);return faceDetectorProxy;}@Beanpublic FaceRecognizerProxy faceRecognizer() throws FileNotFoundException {SeetaConfSetting detectorPoolSetting = new SeetaConfSetting(new SeetaModelSetting(0, new String[]{modelPath + File.separator + "face_recognizer.csta"}, SeetaDevice.SEETA_DEVICE_CPU));FaceRecognizerProxy faceRecognizerProxy = new FaceRecognizerProxy(detectorPoolSetting);return faceRecognizerProxy;}@Beanpublic FaceLandmarkerProxy faceLandmarker() throws FileNotFoundException {SeetaConfSetting detectorPoolSetting = new SeetaConfSetting(new SeetaModelSetting(0, new String[]{modelPath + File.separator + "face_landmarker_pts5.csta"}, SeetaDevice.SEETA_DEVICE_CPU));FaceLandmarkerProxy faceLandmarkerProxy = new FaceLandmarkerProxy(detectorPoolSetting);return faceLandmarkerProxy;}
}
在使用相关bean对象时，需要进行library的本地注册，指定cpu还是gpu模式
LoadNativeCore.LOAD_NATIVE(SeetaDevice.SEETA_DEVICE_CPU)
人脸检测
public FaceEnum.CheckImageFaceStatus getFace(BufferedImage image) throws Exception {SeetaImageData imageData = SeetafaceUtil.toSeetaImageData(image);SeetaRect[] detects = faceDetectorProxy.detect(imageData);if (detects.length == 0) {return FaceEnum.CheckImageFaceStatus.NoFace;} else if (detects.length == 1) {return FaceEnum.CheckImageFaceStatus.OneFace;} else {return FaceEnum.CheckImageFaceStatus.MoreFace;}}
人脸比对
public FaceEnum.CompareImageFaceStatus compareFace(BufferedImage source, BufferedImage compare) throws Exception {float[] sourceFeature = extract(source);float[] compareFeature = extract(compare);if (sourceFeature != null && compareFeature != null) {float calculateSimilarity = faceRecognizerProxy.calculateSimilarity(sourceFeature, compareFeature);System.out.printf("相似度:%f\n", calculateSimilarity);if (calculateSimilarity >= CHECK_SIM) {return FaceEnum.CompareImageFaceStatus.Same;} else {return FaceEnum.CompareImageFaceStatus.Different;}} else {return FaceEnum.CompareImageFaceStatus.LostFace;}}
人脸关键点
private float[] extract(BufferedImage image) throws Exception {SeetaImageData imageData = SeetafaceUtil.toSeetaImageData(image);SeetaRect[] detects = faceDetectorProxy.detect(imageData);if (detects.length > 0) {SeetaPointF[] pointFS = faceLandmarkerProxy.mark(imageData, detects[0]);float[] features = faceRecognizerProxy.extract(imageData, pointFS);return features;}return null;}
人脸数据库
- 注册
public long registFace(BufferedImage image) throws Exception {long result = -1;SeetaImageData imageData = SeetafaceUtil.toSeetaImageData(image);SeetaRect[] detects = faceDetectorProxy.detect(imageData);if (detects.length > 0) {SeetaPointF[] pointFS = faceLandmarkerProxy.mark(imageData, detects[0]);result = faceDatabase.Register(imageData, pointFS);faceDatabase.Save(dataBasePath);}return result;}
- 查找
public long queryFace(BufferedImage image) throws Exception {long result = -1;SeetaImageData imageData = SeetafaceUtil.toSeetaImageData(image);SeetaRect[] detects = faceDetectorProxy.detect(imageData);if (detects.length > 0) {SeetaPointF[] pointFS = faceLandmarkerProxy.mark(imageData, detects[0]);long[] index = new long[1];float[] sim = new float[1];result = faceDatabase.QueryTop(imageData, pointFS, 1, index, sim);if (result > 0) {float similarity = sim[0];if (similarity >= CHECK_SIM) {result = index[0];} else {result = -1;}}}return result;}
- 删除
public long deleteFace(long index) throws Exception {long result = faceDatabase.Delete(index);faceDatabase.Save(dataBasePath);return result;}
拓展
集成了face-api.js，实现简单的张张嘴，摇摇头活体检测，精确度不是很高，作为一个参考选项
官网地址：https://github.com/justadudewhohacks/face-api.js
加载模型
Promise.all([faceapi.loadFaceDetectionModel('models'),faceapi.loadFaceLandmarkModel('models')]).then(startAnalysis);function startAnalysis() {console.log('模型加载成功！');var canvas1 = faceapi.createCanvasFromMedia(document.getElementById('showImg'))faceapi.detectSingleFace(canvas1).then((detection) => {if (detection) {faceapi.detectFaceLandmarks(canvas1).then((landmarks) => {console.log('模型预热调用成功！');})}})}
打开摄像头
<video id="video" muted playsinline></video>function AnalysisFaceOnline() {var videoElement = document.getElementById('video');// 检查浏览器是否支持getUserMedia APIif (navigator.mediaDevices.getUserMedia) {navigator.mediaDevices.getUserMedia({ video: { facingMode: "user" } }) // 请求视频流.then(function(stream) {videoElement.srcObject = stream; // 将视频流设置到<video>元素videoElement.play();}).catch(function(err) {console.error("获取摄像头错误：", err); // 处理错误});} else {console.error("您的浏览器不支持getUserMedia API");}}
捕捉帧计算关键点
function vedioCatchInit() {video.addEventListener('play', function() {function captureFrame() {if (!video.paused && !video.ended) {// 设置canvas的尺寸与视频帧相同canvas.width = 200;canvas.height = 300;// 绘制当前视频帧到canvascontext.drawImage(video, 0, 0, canvas.width, canvas.height);// 将canvas内容转换为data URL//outputImage.src = canvas.toDataURL('image/png');// 可以在这里添加代码将data URL发送到服务器或进行其他处理faceapi.detectSingleFace(canvas).then((detection) => {if (detection) {faceapi.detectFaceLandmarks(canvas).then((landmarks) => {})} else {console.log("no face")}})// 递归调用以持续捕获帧setTimeout(captureFrame, 100); // 每500毫秒捕获一次}}captureFrame(); // 开始捕获帧});}
