根据访问图片识别

# coding:utf-8

import sys

import math

import cv2

# 待检测的图片路径

imagepath = r'l.png'

face_cascade = cv2.CascadeClassifier(r'./haarcascade_frontalface_default.xml')

# 读取图片

image = cv2.imread(imagepath)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 探测图片中的人脸

faces = face_cascade.detectMultiScale(

gray,

scaleFactor=1.15,

minNeighbors=5,

minSize=(5, 5),

flags=cv2.CASCADE_SCALE_IMAGE

)

print ("发现{0}个人脸!".format(len(faces)))

for (x, y, w, h) in faces:

#cv2.rectangle(image,(x,y),(x+w,y+w),(0,255,0),2)

green = (0, 255, 0)

cv2.rectangle(image, (x, y), (x + w, y + h), green, 2)

#cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

#cv2.circle(image, ((x + x + w) // 2, (y + y + h) // 2), w // 2, (0, 255, 0), 2)

cv2.imshow("Find Faces!", image)

cv2.waitKey(0)

haarcascade_frontalface_default.xml文件下载：

链接:https://pan.baidu.com/s/1puL055J6CWa6dXks79UYkg  密码:r4sy

开启摄像头检测

# coding:utf-8

import cv2

import numpy as np

# Load the face cascade file 按照自己的文件位置加入，如果是下载的原书的程序包那就不用改了

face_cascade = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')

# Check if the face cascade file has been loaded

if face_cascade.empty():

raise IOError('Unable to load the face cascade classifier xml file')

# Initialize the video capture object

cap = cv2.VideoCapture(0)

# Define the scaling factor

scaling_factor = 0.5

# Loop until you hit the Esc key

while True:

# Capture the current frame and resize it

ret, frame = cap.read()

frame = cv2.resize(frame, None, fx=scaling_factor, fy=scaling_factor,

interpolation=cv2.INTER_AREA)

# Convert to grayscale

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# Run the face detector on the grayscale image

face_rects = face_cascade.detectMultiScale(gray, 1.3, 5)

# Draw rectangles on the image

for (x, y, w, h) in face_rects:

cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)

# Display the image

cv2.imshow('Face Detector', frame)

# Check if Esc key has been pressed

c = cv2.waitKey(1)

if c == 27:

break

# Release the video capture object and close all windows

cap.release()

cv2.destroyAllWindows()