基础知识（七）opencv、python、人脸框检测

一、环境搭建

电脑系统：window7 64位

opencv版本：opencv 2.49

python版本：python 2.7

1、首先就是安装opencv，从官网下载.exe文件，然后直接安装。安装完opencv后，找到文件：cv2.pyd。这个文件，我安装完后，是放在：opencv\build\python\2.7\x64。因为我的电脑是64位所以选择x64下的文件cv2.pyd。

2、把cv2.pyd文件放到python安装目录里的：Lib\site-packages文件夹下。这样就OK了，接着就可以直接调用opencv库了。

二、人脸检测

<span style="font-size:18px;">import numpy as np
import cv2
import cv2.cv as cv
from matplotlib import pyplot as plt

face_cascade = cv2.CascadeClassifier('C:\Program Files\opencv\sources\data\haarcascades\haarcascade_frontalface_default.xml')

img = cv2.imread('113.jpg')
gray = cv2.cvtColor(img,cv2.cv.CV_BGR2GRAY)

divisor=8
h, w =np.shape(img)[:2]
minSize=(w/divisor, h/divisor)
color = (0,0,0)
faces = face_cascade.detectMultiScale(gray, 1.2, 2, cv2.CASCADE_SCALE_IMAGE,minSize)

if len(faces)>0:
for faceRect in faces:
x, y, w, h = faceRect
cv2.rectangle(img, (x, y), (x+w, y+h), color)
roi = img[y:(h+y), x:(w+x)]

cv2.imshow('img',img)
cv2.imshow('facerect',roi)
cv2.waitKey(0)
cv2.destroyAllWindows()</span>

上面的cv2.CascadeClassifier函数的参数是.xml所在的路径。结果如下：

import numpy as np
import cv2
import cv2.cv as cv
from matplotlib import pyplot as plt

def GetFileList(FindPath,FlagStr=[]):
import os
FileList=[]
FileNames=os.listdir(FindPath)
if len(FileNames)>0:
for fn in FileNames:
if len(FlagStr)>0:
if IsSubString(FlagStr,fn):
fullfilename=os.path.join(FindPath,fn)
FileList.append(fullfilename)
else:
fullfilename=os.path.join(FindPath,fn)
FileList.append(fullfilename)

if len(FileList)>0:
FileList.sort()

return FileList
def IsSubString(SubStrList,Str):
flag=True
for substr in SubStrList:
if not(substr in Str):
flag=False

return flag

def facedetect(newname,filepath,face_cascade):

img = cv2.imread(filepath)
print filepath
gray = cv2.cvtColor(img,cv2.cv.CV_BGR2GRAY)

divisor=8
height, weight =np.shape(img)[:2]
minSize=(weight/divisor, height/divisor)
color = (0,0,0)
faces = face_cascade.detectMultiScale(gray, 1.2, 2, cv2.CASCADE_SCALE_IMAGE,minSize)
print faces

if len(faces)>0:
for faceRect in faces:
x, y, w, h = faceRect
img0=np.zeros((h+0.2*h,w+0.2*w,3))
m,n,c=img0.shape
miny=max(0,y-0.3*h)
minx=max(0,(x-0.3*w))
maxy=min(height,(y+1.3*h))
maxx=min(weight,(x+1.3*w))
roi=img[miny:maxy,minx:maxx]
rectshape=roi.shape
maxlenght=max(rectshape[0],rectshape[1])
img0=np.zeros((maxlenght,maxlenght,3))
img0[(maxlenght*.5-rectshape[0]*.5):(maxlenght*.5+rectshape[0]*.5),(maxlenght*.5-rectshape[1]*.5):(maxlenght*.5+rectshape[1]*.5)]=roi
cv2.imwrite(newname,img0)

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
imgfile=GetFileList('face','.jpg')
i=0
for imgf in imgfile:
name='face1/'+str(i)+'.jpg'
i+=1
facedetect(name,imgf,face_cascade)

[align=left]人脸裁剪为矩阵，并填充[/align]

import numpy as np
import cv2
import cv2.cv as cv
from matplotlib import pyplot as plt

def GetFileList(FindPath,FlagStr=[]):
import os
FileList=[]
FileNames=os.listdir(FindPath)
if len(FileNames)>0:
for fn in FileNames:
if len(FlagStr)>0:
if IsSubString(FlagStr,fn):
fullfilename=os.path.join(FindPath,fn)
FileList.append(fullfilename)
else:
fullfilename=os.path.join(FindPath,fn)
FileList.append(fullfilename)

if len(FileList)>0:
FileList.sort()

return FileList
def IsSubString(SubStrList,Str):
flag=True
for substr in SubStrList:
if not(substr in Str):
flag=False

return flag

def facedetect(newname,filepath,face_cascade):

img = cv2.imread(filepath)
gray = cv2.cvtColor(img,cv2.cv.CV_BGR2GRAY)

divisor=8
height, weight =np.shape(img)[:2]
minSize=(weight/divisor, height/divisor)
color = (0,0,0)
faces = face_cascade.detectMultiScale(gray, 1.2, 2, cv2.CASCADE_SCALE_IMAGE,minSize)
print faces

if len(faces)>0:
for faceRect in faces:
x, y, w, h = faceRect
img0=np.zeros((h+0.2*h,w+0.2*w,3))
m,n,c=img0.shape
miny=max(0,y-0.3*h)
minx=max(0,(x-0.3*w))
maxy=min(height,(y+1.3*h))
maxx=min(weight,(x+1.3*w))
roi=img[miny:maxy,minx:maxx]
rectshape=roi.shape
maxlenght=max(rectshape[0],rectshape[1])
img0=np.zeros((maxlenght,maxlenght,3))
img0[(maxlenght*.5-rectshape[0]*.5):(maxlenght*.5+rectshape[0]*.5),(maxlenght*.5-rectshape[1]*.5):(maxlenght*.5+rectshape[1]*.5)]=roi
cv2.imwrite(newname,img0)

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
imgfile=GetFileList('ff')
i=0
for imgf in imgfile:
name='ff_face/'+str(i)+'.jpg'
i+=1
facedetect(name,imgf,face_cascade)

**********************作者：hjimce 时间：2015.9.1 联系QQ：1393852684 地址：http://blog.csdn.net/hjimce 转载请保留本行信息********************