Basic Face Detection with OpenCV in Python

With the rapid rise of artificial intelligence, computer vision has advanced quickly, especially in areas such as face recognition and object detection. This article presents a basic introduction to face recognition, guiding readers through the essential functions that make this technology work.

When you pass through security checkpoints at airports or train stations, facial verification is often used, but it can be disrupted if someone else steps into the camera view. Understanding how face detection works can help improve such systems.

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#!/usr/bin/env python
# -*- coding:utf-8 -*-
# @Time    : 2021/7/17 下午9:53
# @Author  : huaan

import cv2 as cv
imagepath = "more.jpg"

def more_shibie(imagepath):
    image = cv.imread(imagepath)
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    face_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
    faces = face_cascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=3,
        minSize=(70, 70),
        maxSize=(160, 160),
        flags=cv.IMREAD_GRAYSCALE
    )
    print("检测到{0}个人脸".format(len(faces)))
    for (x, y, w, h) in faces:
        cv.rectangle(image, (x, y), (x + w, y + w), (0, 0, 255), 2)
    cv.imshow("image", image)
    cv.waitKey(0)
    cv.destroyAllWindows()

more_shibie(imagepath)