Opencv 入门学习之图片人脸识别

import cv2
from PIL import Image,ImageDraw
import os

def detectFaces(image_name):
img = cv2.imread(image_name)
face_cascade = cv2.CascadeClassifier('../opencv-2.4.9/data/haarcascades/haarcascade_frontalface_default.xml')
if img.ndim==3: # 如果是三维就转换成二维
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
else:
gray = img
faces = face_cascade.detectMultiScale(gray,scaleFactor = 1.3,minNeighbors=4)
result = []
for (x,y,width,height) in faces:
result.append((x,y,x+width,y+height))
return result

def saveFaces(image_name):
faces = detectFaces(image_name)
if faces:
save_dir = image_name.split('.')[0]+"_faces"
os.mkdir(save_dir)
count = 0
for (x1,y1,x2,y2) in faces:
file_name = os.path.join(save_dir,str(count)+".jpg")
Image.open(image_name).crop((x1,y1,x2,y2)).save(file_name)
count +=1

#在原图像上画矩形，框出所有人脸。
#调用Image模块的draw方法，Image.open获取图像句柄， ImageDraw获取该图像的draw实例，然后调用该draw实例的rectangle方法画矩形 (矩形的坐标即mZdetectFaces返回的坐标)，outline是矩
形线条颜色(B,G,R)。
#注：原始图像如果是灰度图，则去掉outline，因为灰度图没有RGB可言。drawEyes、detectSmiles也一样

def drawFaces(image_name):
faces = detectFaces(image_name)
if faces:
img = Image.open(image_name)
draw_instance = ImageDraw.Draw(img)
for(x1,y1,x2,y2) in faces:
draw_instance.rectangle((x1,y1,x2,y2),outline=(25,255,0))
img.save('drawFaces_'+image_name)
saveFaces(image_name)
image = cv2.imread('drawFaces_'+image_name)
return image

if __name__=="__main__":
img = drawFaces('obama.jpg')
cv2.imshow("drawFaces",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

运行 python faceDetect.py 后效果如图：前2个识别错误！