delphi-opencv 人脸对比 代码

以下是使用 Delphi 和 OpenCV 库实现人脸对比的示例代码：

uses
  cv, highgui;

function CompareFaces(const Img1Path, Img2Path: string): Double;
var
  Img1, Img2: IplImage;
  FaceCascade: pCvHaarClassifierCascade;
  Storage: pCvMemStorage;
  FaceRect1, FaceRect2: CvRect;
  FaceImg1, FaceImg2: IplImage;
  Hist1, Hist2: pCvHistogram;
begin
  Result := 0.0;

  // 加载图像
  Img1 := cvLoadImage(PAnsiChar(AnsiString(Img1Path)), CV_LOAD_IMAGE_GRAYSCALE);
  Img2 := cvLoadImage(PAnsiChar(AnsiString(Img2Path)), CV_LOAD_IMAGE_GRAYSCALE);

  // 加载人脸识别器
  FaceCascade := cvLoadHaarClassifierCascade(PAnsiChar(AnsiString('haarcascade_frontalface_alt.xml')), cvSize(0, 0));

  // 创建内存存储器
  Storage := cvCreateMemStorage(0);

  try
    // 检测人脸
    FaceRect1 := cvHaarDetectObjects(Img1, FaceCascade, Storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(30, 30));
    FaceRect2 := cvHaarDetectObjects(Img2, FaceCascade, Storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(30, 30));

    // 如果检测到的人脸数量不为 1，则返回 0
    if (FaceRect1.total <> 1) or (FaceRect2.total <> 1) then
      Exit;

    // 获取人脸图像
    FaceImg1 := cvCreateImage(cvSize(FaceRect1.width, FaceRect1.height), IPL_DEPTH_8U, 1);
    cvSetImageROI(Img1, FaceRect1);
    cvCopy(Img1, FaceImg1, nil);
    cvResetImageROI(Img1);

    FaceImg2 := cvCreateImage(cvSize(FaceRect2.width, FaceRect2.height), IPL_DEPTH_8U, 1);
    cvSetImageROI(Img2, FaceRect2);
    cvCopy(Img2, FaceImg2, nil);
    cvResetImageROI(Img2);

    // 创建直方图
    Hist1 := cvCreateHist(1, @256, CV_HIST_ARRAY, nil, 1);
    Hist2 := cvCreateHist(1, @256, CV_HIST_ARRAY, nil, 1);

    // 计算直方图
    cvCalcHist(@FaceImg1, Hist1);
    cvCalcHist(@FaceImg2, Hist2);

    // 计算相似度
    Result := cvCompareHist(Hist1, Hist2, CV_COMP_CORREL);

  finally
    // 释放资源
    cvReleaseImage(@Img1);
    cvReleaseImage(@Img2);
    cvReleaseHaarClassifierCascade(FaceCascade);
    cvReleaseMemStorage(@Storage);
    cvReleaseImage(@FaceImg1);
    cvReleaseImage(@FaceImg2);
    cvReleaseHist(@Hist1);
    cvReleaseHist(@Hist2);
  end;
end;

该函数接受两个图像文件路径，返回它们之间的人脸相似度。请注意，该函数假定每个图像中只有一个人脸。如果图像中有多个人脸，则将返回 0。