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()
