结果
基本实现了识别的功能。基本的界面如下
界面长得比较丑,主要是JavaSwing写界面比较麻烦,写个菜单栏都要那么多代码。目前不打算改了。
实现的思路是:使用opencv中自带的OpenCVFrameGrabber获取摄像头的数据,CanvasFrame来显示摄像头捕获的画面。
点击注册和识别都会在捕获的视频流自动抓取一帧图片,点下面的按钮可以查看拍摄效果
当输入想要比对的身份,点击识别之后,会与注册保存的数据进行比对
准确率还行。
附上部分代码
public static void OpenCamera()throwsException, InterruptedException{
OpenCVFrameGrabber grabber= new OpenCVFrameGrabber(0);//0表示本机摄像头 当然这里也可以换成网络摄像头地址
grabber.start(); //开始获取摄像头数据
CanvasFrame canvas = new CanvasFrame("倒计时5秒自动拍照注册");//新建一个窗口
canvas.setDefaultCloseOperation(JFrame.DISPOSE_ON_CLOSE);//窗口关闭时程序运行结束
canvas.setAlwaysOnTop(true);int i=0;while(true){if(i==30){//窗口是否关闭
System.out.println("已关闭");
grabber.stop();//停止抓取
canvas.dispose();//System.exit(2);//退出
}
canvas.showImage(grabber.grab());//获取摄像头图像并放到窗口上显示, 这里的Frame frame=grabber.grab(); frame表示一帧视频图像//调用doExecuteFrame()方法,将截取的图片保存在本地
if(i==1)CatchPhoto(grabber.grabFrame(),"./register"+"/"+ MainWindow.ID +".jpg");
Thread.sleep(50);//50毫秒刷新一次图像
i++;
}
}
//人脸检测
ImageInfo imageInfo = getRGBData(newFile(register));
List faceInfoList = new ArrayList();
errorCode=faceEngine.detectFaces(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);
System.out.println(faceInfoList);//特征提取
FaceFeature faceFeature = newFaceFeature();
errorCode= faceEngine.extractFaceFeature(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList.get(0), faceFeature);
System.out.println("特征值大小:" +faceFeature.getFeatureData().length);//人脸检测2
ImageInfo imageInfo2 = getRGBData(newFile(discern));
List faceInfoList2 = new ArrayList();
errorCode=faceEngine.detectFaces(imageInfo2.getImageData(), imageInfo2.getWidth(), imageInfo2.getHeight(),imageInfo.getImageFormat(), faceInfoList2);
System.out.println(faceInfoList);//特征提取2
FaceFeature faceFeature2 = newFaceFeature();
errorCode= faceEngine.extractFaceFeature(imageInfo2.getImageData(), imageInfo2.getWidth(), imageInfo2.getHeight(), imageInfo.getImageFormat(), faceInfoList2.get(0), faceFeature2);
System.out.println("特征值大小:" +faceFeature.getFeatureData().length);//特征比对
FaceFeature targetFaceFeature = newFaceFeature();
targetFaceFeature.setFeatureData(faceFeature.getFeatureData());
FaceFeature sourceFaceFeature= newFaceFeature();
sourceFaceFeature.setFeatureData(faceFeature2.getFeatureData());
FaceSimilar faceSimilar= newFaceSimilar();
errorCode=faceEngine.compareFaceFeature(targetFaceFeature, sourceFaceFeature, faceSimilar);//System.out.println("相似度:" + faceSimilar.getScore());
MainWindow.Similarity.setText("相似度:" +faceSimilar.getScore());//设置活体测试
errorCode = faceEngine.setLivenessParam(0.5f, 0.7f);//人脸属性检测
FunctionConfiguration configuration = newFunctionConfiguration();
configuration.setSupportAge(true);
configuration.setSupportFace3dAngle(true);
configuration.setSupportGender(true);
configuration.setSupportLiveness(true);
errorCode=faceEngine.process(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList, configuration);//性别检测
List genderInfoList = new ArrayList();
errorCode=faceEngine.getGender(genderInfoList);//System.out.println("性别:" + genderInfoList.get(0).getGender());
if(genderInfoList.get(0).getGender()==0){
MainWindow.Sex.setText("性别:男");
}else if(genderInfoList.get(0).getGender()==1){
MainWindow.Sex.setText("性别:女");
}else{
MainWindow.Sex.setText("性别:未知");
}//MainWindow.Sex.setText("性别:" + genderInfoList.get(0).getGender());//年龄检测
List ageInfoList = new ArrayList();
errorCode=faceEngine.getAge(ageInfoList);//System.out.println("年龄:" + ageInfoList.get(0).getAge());
MainWindow.Age.setText("年龄:" + ageInfoList.get(0).getAge());//3D信息检测
List face3DAngleList = new ArrayList();
errorCode=faceEngine.getFace3DAngle(face3DAngleList);
System.out.println("3D角度:" + face3DAngleList.get(0).getPitch() + "," + face3DAngleList.get(0).getRoll() + "," + face3DAngleList.get(0).getYaw());
MainWindow.Angle.setText("3D角度:" + face3DAngleList.get(0).getPitch() + "," + face3DAngleList.get(0).getRoll() + "," + face3DAngleList.get(0).getYaw());//活体检测
List livenessInfoList = new ArrayList();
errorCode=faceEngine.getLiveness(livenessInfoList);//System.out.println("活体:" + livenessInfoList.get(0).getLiveness());
MainWindow.LiVing.setText("活体:" + livenessInfoList.get(0).getLiveness());//IR属性处理
ImageInfo imageInfoGray = getGrayData(new File("C:\\Users\\user\\Desktop\\test\\photo\\1.jpg"));
List faceInfoListGray = new ArrayList();
errorCode=faceEngine.detectFaces(imageInfoGray.getImageData(), imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray);
FunctionConfiguration configuration2= newFunctionConfiguration();
configuration2.setSupportIRLiveness(true);
errorCode=faceEngine.processIr(imageInfoGray.getImageData(), imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray, configuration2);//IR活体检测
List irLivenessInfo = new ArrayList<>();
errorCode=faceEngine.getLivenessIr(irLivenessInfo);
System.out.println("IR活体:" + irLivenessInfo.get(0).getLiveness());
ImageInfoEx imageInfoEx= newImageInfoEx();
imageInfoEx.setHeight(imageInfo.getHeight());
imageInfoEx.setWidth(imageInfo.getWidth());
imageInfoEx.setImageFormat(imageInfo.getImageFormat());
imageInfoEx.setImageDataPlanes(new byte[][]{imageInfo.getImageData()});
imageInfoEx.setImageStrides(new int[]{imageInfo.getWidth() * 3});
List faceInfoList1 = new ArrayList<>();
errorCode=faceEngine.detectFaces(imageInfoEx, DetectModel.ASF_DETECT_MODEL_RGB, faceInfoList1);
FunctionConfiguration fun= newFunctionConfiguration();
fun.setSupportAge(true);
errorCode=faceEngine.process(imageInfoEx, faceInfoList1, functionConfiguration);
List ageInfoList1 = new ArrayList<>();int age =faceEngine.getAge(ageInfoList1);
System.out.println("年龄:" + ageInfoList1.get(0).getAge());
FaceFeature feature= newFaceFeature();
errorCode= faceEngine.extractFaceFeature(imageInfoEx, faceInfoList1.get(0), feature);
问题记录
1.捕获视频流
网上找到了很多方法,比如JMF、ffmpeg等。JMF以前用过,过于老旧了,而且只支持32位系统,想用的话还得用32位的IDE,所以忽略。然后发现用opencv集成了ffmpeg,通过grabber.grab()方法就可以获取。很简单。
2.视频显示
一开始的想法,grabber.grab()获取的是一帧一帧的图片,那么可以再frame里加一个显示图片的label,每过十毫秒刷新一次图片,这样就起到了播放视频的效果。但是遇到了问题
使用java.awt.Image 中的方法无法获取grabber.grab()中的数据,强制类型转换无效。后来查看OpenCVFrameGrabber的源码。最后在Frame.Class里发现image的类型
NIO与IO之间是有一些区别的,NIO要更优秀一点,可惜Java界面没有
所以转换思路,没办法在主窗口播放,那就在新建一个窗口,看起来有点别扭,但受限于技术水平,还是先把功能实现了。
javacv里有一个简单的新建窗口方式
CanvasFrame canvas = new CanvasFrame("Camera");//新建一个窗口
通过源码可以看到CanvasFrame是继承了javax.swing.JFrame类的。使用这个类主要是它里面的showimage方法
里面有适合的数据类型。
3.窗口问题
使用新建窗口显示视频时,关闭视频播放窗口,主窗口也会关闭。
原来关闭窗口使用的是System.exit(0);这个方法直接终止了虚拟机。后来改成了dispose()方法(需要.setDefaultCloseOperation设置为JFrame.DISPOSE_ON_CLOSE)