python基于opencv实现人脸识别

#coding:utf-8
import cv2 as cv

# 读取原始图像
img = cv.imread('face.png')

# 调用熟悉的人脸分类器 识别特征类型
# 人脸 - haarcascade_frontalface_default.xml
# 人眼 - haarcascade_eye.xml
# 微笑 - haarcascade_smile.xml
face_detect = cv.CascadeClassifier('haarcascade_frontalface_default.xml')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

# 检查人脸 按照1.1倍放到 周围最小像素为5
face_zone = face_detect.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)
print ('识别人脸的信息：',face_zone)

# 绘制矩形和圆形检测人脸
for x, y, w, h in face_zone:
  # 绘制矩形人脸区域 thickness表示线的粗细
  cv.rectangle(img, pt1=(x, y), pt2=(x+w, y+h),color=[0,0,255], thickness=2)
  # 绘制圆形人脸区域 radius表示半径
  cv.circle(img, center=(x+w//2, y+h//2), radius=w//2, color=[0,255,0], thickness=2)

# 设置图片可以手动调节大小
cv.namedWindow("Easmount-CSDN", 0)

# 显示图片
cv.imshow("Easmount-CSDN", img)

# 等待显示 设置任意键退出程序
cv.waitKey(0)
cv.destroyAllWindows()

#coding:utf-8
import cv2 as cv
import numpy as np

# 加载视频
cap = cv.VideoCapture('wang.mp4')

# 调用熟悉的人脸分类器 识别特征类型
# 人脸 - haarcascade_frontalface_default.xml
# 人眼 - haarcascade_eye.xm
# 微笑 - haarcascade_smile.xml
face_detect = cv.CascadeClassifier('haarcascade_frontalface_default.xml')

while True:
  # 读取视频片段
  flag, frame = cap.read()
  if flag == False:
    break

  # 灰度处理
  gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)

  # 检查人脸 按照1.1倍放到 周围最小像素为5
  face_zone = face_detect.detectMultiScale(gray, scaleFactor = 1.5, minNeighbors = 8)

  # 绘制矩形和圆形检测人脸
  for x, y, w, h in face_zone:
    cv.rectangle(frame, pt1 = (x, y), pt2 = (x+w, y+h), color = [0,0,255], thickness=2)
    cv.circle(frame, center = (x + w//2, y + h//2), radius = w//2, color = [0,255,0], thickness = 2)

  # 显示图片
  cv.imshow('video', frame)
  
  # 设置退出键和展示频率
  if ord('q') == cv.waitKey(25):
    break

# 释放资源
cv.destroyAllWindows()
cap.release()

#coding:utf-8
import cv2 as cv

# 识别电脑摄像头并打开
cap = cv.VideoCapture(0)

# 调用熟悉的人脸分类器 识别特征类型
# 人脸 - haarcascade_frontalface_default.xml
# 人眼 - haarcascade_eye.xm
# 微笑 - haarcascade_smile.xml
face_detect = cv.CascadeClassifier('haarcascade_frontalface_default.xml')

while True:
  # 读取视频片段
  flag, frame = cap.read()
  if flag == False:
    break

  # 灰度处理
  gray = cv.cvtColor(frame, code=cv.COLOR_BGR2GRAY)

  # 检查人脸 按照1.1倍放到 周围最小像素为5
  face_zone = face_detect.detectMultiScale(gray, scaleFactor = 1.1, minNeighbors = 5)

  # 绘制矩形和圆形检测人脸
  for x, y, w, h in face_zone:
    cv.rectangle(frame, pt1 = (x, y), pt2 = (x+w, y+h), color = [0,0,255], thickness=2)
    cv.circle(frame, center = (x + w//2, y + h//2), radius = w//2, color = [0,255,0], thickness = 2)

  # 显示图片
  cv.imshow('video', frame)
  
  # 设置退出键和展示频率
  if ord('q') == cv.waitKey(40):
    break

# 释放资源
cv.destroyAllWindows()
cap.release()