delphi xe OpenCV 人脸对比 代码

以下是 Delphi XE 和 OpenCV 实现人脸对比的示例代码：

uses
  ..., cvtypes, cvimgproc, cvobjdetect, cvface;

procedure TForm1.CompareFaces(const Image1, Image2: IplImage);
var
  FaceRecognizer: TCvFaceRecognizer;
  FaceRecognizerType: TCvFaceRecognizerType;
  FaceDetector: TCvHaarClassifierCascade;
  Storage: PCvMemStorage;
  Faces1, Faces2: PCvSeq;
  Face1, Face2: PCvRect;
  Gray1, Gray2: IplImage;
  FaceImage1, FaceImage2: IplImage;
  FaceFeature1, FaceFeature2: PSingle;
  Distance: Single;
begin
  // 初始化人脸检测器
  FaceDetector := cvLoadHaarClassifierCascade('haarcascade_frontalface_alt.xml', cvSize(0, 0));

  // 初始化人脸识别器
  FaceRecognizerType := cvFaceRecognizerLBPH;
  FaceRecognizer := cvCreateFaceRecognizer(FaceRecognizerType);

  // 初始化特征存储器
  Storage := cvCreateMemStorage(0);

  // 加载图像并进行灰度化
  Gray1 := cvCreateImage(Image1.cvSize, Image1.depth, 1);
  cvCvtColor(Image1, Gray1, CV_BGR2GRAY);

  Gray2 := cvCreateImage(Image2.cvSize, Image2.depth, 1);
  cvCvtColor(Image2, Gray2, CV_BGR2GRAY);

  try
    // 检测人脸
    Faces1 := cvHaarDetectObjects(Gray1, FaceDetector, Storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(30, 30));
    Faces2 := cvHaarDetectObjects(Gray2, FaceDetector, Storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(30, 30));

    // 获取第一个人脸的图像并进行特征提取
    if (Faces1 <> nil) and (Faces1^.total > 0) then
    begin
      Face1 := PCvRect(cvGetSeqElem(Faces1, 0));
      FaceImage1 := cvCreateImage(cvSize(Face1^.width, Face1^.height), Image1.depth, Image1.nChannels);
      cvSetImageROI(Image1, cvRect(Face1^.x, Face1^.y, Face1^.width, Face1^.height));
      cvCopy(Image1, FaceImage1, nil);
      cvResetImageROI(Image1);

      FaceFeature1 := cvCreateMat(1, FaceRecognizer.eigenVects^.cols, CV_32FC1);
      cvExtractFaceFeature(FaceImage1, FaceFeature1, FaceRecognizer);
    end;

    // 获取第二个人脸的图像并进行特征提取
    if (Faces2 <> nil) and (Faces2^.total > 0) then
    begin
      Face2 := PCvRect(cvGetSeqElem(Faces2, 0));
      FaceImage2 := cvCreateImage(cvSize(Face2^.width, Face2^.height), Image2.depth, Image2.nChannels);
      cvSetImageROI(Image2, cvRect(Face2^.x, Face2^.y, Face2^.width, Face2^.height));
      cvCopy(Image2, FaceImage2, nil);
      cvResetImageROI(Image2);

      FaceFeature2 := cvCreateMat(1, FaceRecognizer.eigenVects^.cols, CV_32FC1);
      cvExtractFaceFeature(FaceImage2, FaceFeature2, FaceRecognizer);
    end;

    // 计算人脸相似度
    if (FaceFeature1 <> nil) and (FaceFeature2 <> nil) then
    begin
      Distance := cvNorm(FaceFeature1, FaceFeature2, CV_L2);
      if Distance < 0.6 then
        ShowMessage('两张人脸相似')
      else
        ShowMessage('两张人脸不相似');
    end;
  finally
    // 释放资源
    cvReleaseHaarClassifierCascade(FaceDetector);
    cvReleaseMemStorage(Storage);
    cvReleaseImage(Gray1);
    cvReleaseImage(Gray2);
    if FaceImage1 <> nil then
      cvReleaseImage(FaceImage1);
    if FaceImage2 <> nil then
      cvReleaseImage(FaceImage2);
    if FaceFeature1 <> nil then
      cvReleaseMat(FaceFeature1);
    if FaceFeature2 <> nil then
      cvReleaseMat(FaceFeature2);
  end;
end;

上述代码中，使用了 OpenCV 的人脸检测器和人脸识别器进行人脸对比。具体实现细节可以参考 OpenCV 的相关文档和示例代码。