python实现图片,视频人脸识别(opencv版)

图片人脸识别

import cv2

filepath = "img/xingye-1.png"

img = cv2.imread(filepath) # 读取图片

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转换灰色

# OpenCV人脸识别分类器

classifier = cv2.CascadeClassifier(

"C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml"

)

color = (0, 255, 0) # 定义绘制颜色

# 调用识别人脸

faceRects = classifier.detectMultiScale(

gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))

if len(faceRects): # 大于0则检测到人脸

for faceRect in faceRects: # 单独框出每一张人脸

x, y, w, h = faceRect

# 框出人脸

cv2.rectangle(img, (x, y), (x + h, y + w), color, 2)

# 左眼

cv2.circle(img, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8),

color)

#右眼

cv2.circle(img, (x + 3 * w // 4, y + h // 4 + 30), min(w // 8, h // 8),

color)

#嘴巴

cv2.rectangle(img, (x + 3 * w // 8, y + 3 * h // 4),

(x + 5 * w // 8, y + 7 * h // 8), color)

cv2.imshow("image", img) # 显示图像

c = cv2.waitKey(10)

cv2.waitKey(0)

cv2.destroyAllWindows()

视频人脸识别

# -*- coding:utf-8 -*-

# OpenCV版本的视频检测

import cv2

# 图片识别方法封装

def discern(img):

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

cap = cv2.CascadeClassifier(

"C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml"

)

faceRects = cap.detectMultiScale(

gray, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50))

if len(faceRects):

for faceRect in faceRects:

x, y, w, h = faceRect

cv2.rectangle(img, (x, y), (x + h, y + w), (0, 255, 0), 2) # 框出人脸

cv2.imshow("Image", img)

# 获取摄像头0表示第一个摄像头

cap = cv2.VideoCapture(0)

while (1): # 逐帧显示

ret, img = cap.read()

# cv2.imshow("Image", img)

discern(img)

if cv2.waitKey(1) & 0xFF == ord('q'):

break

cap.release() # 释放摄像头

cv2.destroyAllWindows() # 释放窗口资源

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