Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );

This code snippet calculates the center point of a detected face in an image.

- `faces[i]` refers to the i-th detected face in the image, represented as a rectangle.
- `faces[i].x` and `faces[i].y` are the coordinates of the top-left corner of the rectangle.
- `faces[i].width` and `faces[i].height` are the dimensions of the rectangle.
- `faces[i].width/2` and `faces[i].height/2` are the distances from the top-left corner to the center of the rectangle, in the x and y directions respectively.
- The `Point` function is used to create a point object with the x and y coordinates of the center of the rectangle. This point represents the center of the detected face.

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for( size_t i = 0; i < faces.size(); i++ ){ Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );

The for loop in this code snippet iterates through a vector of detected faces (stored in the variable "faces") and calculates the center coordinates for each face.

The loop starts with an index variable "i" initialized to zero, and continues as long as "i" is less than the size of the "faces" vector. The loop increments "i" after each iteration.

Inside the loop, the center coordinates of the current face are calculated using the following formula:

Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );

The "faces[i].x" and "faces[i].y" variables represent the top-left corner of the current face rectangle, while "faces[i].width" and "faces[i].height" represent the dimensions of the rectangle. The center coordinates are calculated by adding half of the rectangle's width and height to the top-left corner coordinates, respectively.

The resulting center coordinates are stored in a Point object named "center", which can be used for further processing or analysis of the detected faces.

void detectAndDisplay(Mat frame) { Mat frame_gray; cvtColor(frame, frame_gray, COLOR_BGR2GRAY); equalizeHist(frame_gray, frame_gray); //-- Detect faces std::vector<Rect> faces; face_cascade.detectMultiScale(frame_gray, faces); for (size_t i = 0; i < faces.size(); i++) { Point center(faces[i].x + faces[i].width / 2, faces[i].y + faces[i].height / 2); ellipse(frame, center, Size(faces[i].width / 2, faces[i].height / 2), 0, 0, 360, Scalar(255, 0, 255), 4); Mat faceROI = frame_gray(faces[i]); //-- In each face, detect eyes std::vector<Rect> eyes; eyes_cascade.detectMultiScale(faceROI, eyes); for (size_t j = 0; j < eyes.size(); j++) { Point eye_center(faces[i].x + eyes[j].x + eyes[j].width / 2, faces[i].y + eyes[j].y + eyes[j].height / 2); int radius = cvRound((eyes[j].width + eyes[j].height) * 0.25); circle(frame, eye_center, radius, Scalar(255, 0, 0), 4); } } //-- Show what you got imshow("Capture - Face detection", frame); }

这段代码是一个函数，用于检测输入图像中的人脸和眼睛，并在图像上进行标记。该函数的输入参数是一个Mat类型的图像帧，函数会将其转换为灰度图像，并进行直方图均衡化以增强图像对比度。接着，使用人脸检测分类器face_cascade对图像中的人脸进行检测，得到人脸的位置和大小信息。对于每个检测到的人脸，函数会在图像上绘制椭圆形标记，并使用眼部检测分类器eyes_cascade对人脸区域进行眼睛检测，得到眼睛的位置和大小信息。对于每个检测到的眼睛，函数会在图像上绘制圆形标记。最后，函数会在图像窗口中显示标记后的图像。

该函数的主要功能是人脸和眼睛检测，并将检测结果在图像中进行标记。可以在图像处理和计算机视觉领域的应用中使用，如人脸识别、安防监控等。