OpenCV & Python ：使用 haarcascades 的人脸检测将许多框检测为眼睛。

Question

我正在使用 Haarcascades 检测面部和眼睛。我的问题是，它像眼睛一样包围了许多盒子。我的语法是

face_cascade = cv2.CascadeClassifier('haarcascades\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascades\haarcascade_eye.xml')
img = cv2.imread('SAM7.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray,1.2,6)

我目前使用的是 1.2 和 6。faces(5 行) 中的参数值应该是多少，如 scaleFactor、minNeighbors ??

Answer 1

为了找到参数，已经实现了一个非常好的实时实现here用于面部和眼睛检测。在这个项目中，他首先检测面部区域，然后检测眼睛。如果你浏览代码，你会发现你也可以为面部绘制边界框的部分：

main.cpp：检测面部和眼睛

  //-- Detect faces
  face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE|CV_HAAR_FIND_BIGGEST_OBJECT, cv::Size(150, 150) );
//  findSkin(debugImage);

  for( int i = 0; i < faces.size(); i++ )
  {
    rectangle(debugImage, faces[i], 1234);
  }
  //-- Show what you got
  if (faces.size() > 0) {
    findEyes(frame_gray, faces[0]);
  }

它使用面部 ROI 来检测眼睛：

void findEyes(cv::Mat frame_gray, cv::Rect face) {
  cv::Mat faceROI = frame_gray(face);
  cv::Mat debugFace = faceROI;

  if (kSmoothFaceImage) {
    double sigma = kSmoothFaceFactor * face.width;
    GaussianBlur( faceROI, faceROI, cv::Size( 0, 0 ), sigma);
  }
  //-- Find eye regions and draw them
  int eye_region_width = face.width * (kEyePercentWidth/100.0);
  int eye_region_height = face.width * (kEyePercentHeight/100.0);
  int eye_region_top = face.height * (kEyePercentTop/100.0);
  cv::Rect leftEyeRegion(face.width*(kEyePercentSide/100.0),
                         eye_region_top,eye_region_width,eye_region_height);
  cv::Rect rightEyeRegion(face.width - eye_region_width - face.width*(kEyePercentSide/100.0),
                          eye_region_top,eye_region_width,eye_region_height);

  //-- Find Eye Centers
  cv::Point leftPupil = findEyeCenter(faceROI,leftEyeRegion,"Left Eye");
  cv::Point rightPupil = findEyeCenter(faceROI,rightEyeRegion,"Right Eye");
  // get corner regions
  cv::Rect leftRightCornerRegion(leftEyeRegion);
  leftRightCornerRegion.width -= leftPupil.x;
  leftRightCornerRegion.x += leftPupil.x;
  leftRightCornerRegion.height /= 2;
  leftRightCornerRegion.y += leftRightCornerRegion.height / 2;
  cv::Rect leftLeftCornerRegion(leftEyeRegion);
  leftLeftCornerRegion.width = leftPupil.x;
  leftLeftCornerRegion.height /= 2;
  leftLeftCornerRegion.y += leftLeftCornerRegion.height / 2;
  cv::Rect rightLeftCornerRegion(rightEyeRegion);
  rightLeftCornerRegion.width = rightPupil.x;
  rightLeftCornerRegion.height /= 2;
  rightLeftCornerRegion.y += rightLeftCornerRegion.height / 2;
  cv::Rect rightRightCornerRegion(rightEyeRegion);
  rightRightCornerRegion.width -= rightPupil.x;
  rightRightCornerRegion.x += rightPupil.x;
  rightRightCornerRegion.height /= 2;
  rightRightCornerRegion.y += rightRightCornerRegion.height / 2;
  rectangle(debugFace,leftRightCornerRegion,200);
  rectangle(debugFace,leftLeftCornerRegion,200);
  rectangle(debugFace,rightLeftCornerRegion,200);
  rectangle(debugFace,rightRightCornerRegion,200);
  // change eye centers to face coordinates
  rightPupil.x += rightEyeRegion.x;
  rightPupil.y += rightEyeRegion.y;
  leftPupil.x += leftEyeRegion.x;
  leftPupil.y += leftEyeRegion.y;
  // draw eye centers
  circle(debugFace, rightPupil, 3, 1234);
  circle(debugFace, leftPupil, 3, 1234);

  //-- Find Eye Corners
  if (kEnableEyeCorner) {
    cv::Point2f leftRightCorner = findEyeCorner(faceROI(leftRightCornerRegion), true, false);
    leftRightCorner.x += leftRightCornerRegion.x;
    leftRightCorner.y += leftRightCornerRegion.y;
    cv::Point2f leftLeftCorner = findEyeCorner(faceROI(leftLeftCornerRegion), true, true);
    leftLeftCorner.x += leftLeftCornerRegion.x;
    leftLeftCorner.y += leftLeftCornerRegion.y;
    cv::Point2f rightLeftCorner = findEyeCorner(faceROI(rightLeftCornerRegion), false, true);
    rightLeftCorner.x += rightLeftCornerRegion.x;
    rightLeftCorner.y += rightLeftCornerRegion.y;
    cv::Point2f rightRightCorner = findEyeCorner(faceROI(rightRightCornerRegion), false, false);
    rightRightCorner.x += rightRightCornerRegion.x;
    rightRightCorner.y += rightRightCornerRegion.y;
    circle(faceROI, leftRightCorner, 3, 200);
    circle(faceROI, leftLeftCorner, 3, 200);
    circle(faceROI, rightLeftCorner, 3, 200);
    circle(faceROI, rightRightCorner, 3, 200);
  }

Answer 2

您确实需要使用这些参数并找到适合您的参数。总是有更好的方法来做到这一点，但请记住，您永远不会达到 100% 的准确性。您可以了解参数here。

python 中适合我的面部和眼睛检测示例：

    import cv2

    face_cascade = cv2.CascadeClassifier("../haarcascades/haarcascade_frontalface_default.xml")
    eye_cascade = cv2.CascadeClassifier("../haarcascades/haarcascade_eye.xml") 

    cap = cv2.VideoCapture(0)

        while cap.isOpened():
            ret, frame = cap.read()
            if ret:
                gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
                faces = face_cascade.detectMultiScale(
                        gray,
                        scaleFactor=1.3,
                        minNeighbors=5,
                        minSize=(50, 50)
                       )

                for (x, y, w, h) in faces:
                    cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0),2)
                    roi_gray = gray[y:y + h, x:x + w]
                    roi_color = frame[y:y + h, x:x + w]
                    eyes = eye_cascade.detectMultiScale(
                           roi_gray,
                           scaleFactor=1.2,
                           minNeighbors=5,
                           minSize=(10, 10)
                           )

                    for (ex, ey, ew, eh) in eyes:
                        cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (255, 0, 0), 2)

            cv2.imshow("Faces found", frame)

            k = cv2.waitKey(10) & 0xff
            if k == 27:
                break

    cv2.destroyAllWindows()
    cap.release()

希望对您有所帮助。如果您需要有关代码的帮助，请告诉我。

OpenCV & Python ：使用 haarcascades 的人脸检测将许多框检测为眼睛。

OpenCV & Python : Face Detection using haarcascades is detecting many boxes as eyes.

python

opencv

face-detection

eye-detection

haar-classifier