Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
时间: 2024-06-01 09:12:41 浏览: 15
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.
for (int i = 0; i < faces.size(); i++) { rectangle(frame, cvPoint(cvRound(faces[i].x * scale), cvRound(faces[i].y * scale)), cvPoint(cvRound((faces[i].x + faces[i].width) * scale), cvRound((faces[i].y + faces[i].height) * scale)), //颜色,像素位 Scalar(0, 0, 255), 2, 8); string label = "face" + to_string(i + 1); int baseline = 0; Size textSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseline); putText(frame, label, Point(cvRound(faces[i].x * scale), cvRound((faces[i].y + faces[i].height + textSize.height + 5) * scale)), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, LINE_AA); } imshow("frame", frame); }
这段代码是`datectFace`函数的后半部分,用于在图像帧中绘制检测到的人脸框和标签,以及在窗口中显示结果。具体来说:
- `for (int i = 0; i < faces.size(); i++)`:遍历检测到的人脸位置。
- `rectangle(frame, cvPoint(cvRound(faces[i].x * scale), cvRound(faces[i].y * scale)), cvPoint(cvRound((faces[i].x + faces[i].width) * scale), cvRound((faces[i].y + faces[i].height) * scale)), Scalar(0, 0, 255), 2, 8);`:在图像帧中绘制人脸框,使用红色的边框表示。函数的参数依次为:图像帧、矩形框左上角的坐标、矩形框右下角的坐标、颜色、线宽、线型。
- `string label = "face" + to_string(i + 1); int baseline = 0; Size textSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseline); putText(frame, label, Point(cvRound(faces[i].x * scale), cvRound((faces[i].y + faces[i].height + textSize.height + 5) * scale)), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, LINE_AA);`:在图像帧中绘制人脸标签,使用红色的字体表示。函数的参数依次为:标签内容、字体类型、字体大小、字体粗细、字体基线、左下角坐标、颜色、线宽、线型。
- `imshow("frame", frame);`:在窗口中显示处理后的图像帧,窗口名称为"frame"。
总之,这段代码的作用是将人脸检测的结果在原图中用红色的矩形框和标签标注出来,并在窗口中显示出来。