如何限制Haar级联检测到的面部数量 [英] how to limit number of faces detected by haar cascades

问题描述

我在情绪检测系统中使用Haar级联.我提供给模型的每个视频输入都只有一个面孔(这是必需的).当我运行Haar级联模型以检测人脸时，它具有一些误报.由于我的视频中只有一张脸，因此我想检测到最正的区域，而忽略所有其他检测.有没有办法做到这一点?

I am using Haar cascade in an emotion detection system. Every video input I am giving to the model has only one face in it (It is a requirement). When I run Haar cascade model to detect faces, it has some false positives. Since I have only one face in the video, I want to take the most positive area detected and ignore all other detection. Is there a way to do that?

推荐答案

在调用detectMultiScale函数时，请将minNeighbours值设置为较高的值，以免出现误报.另外，您可以设置minSize参数以指定要检测的脸部的最小尺寸.这是我正在使用网络摄像头进行人脸检测的东西.

when you are calling detectMultiScale function, set the minNeighbours value to a high value to avoid false positives. Also, you can set the minSize parameter to specify a minimum size of face to be detected. Here is what I am using for face detection using a webcam.

faces = faceCascade.detectMultiScale(
            gray,
            scaleFactor=1.2,
            minNeighbors=10,
            minSize=(64,64),
            flags=cv2.CASCADE_SCALE_IMAGE
        )

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