火山高校国语,笨笨卡盟,蓝色大海的传说结局
python3+虹软2.0的所有功能整合测试完成,并对虹软所有功能进行了封装,现提供demo
主要功能,
1.人脸识别
2.人脸特征提取
3.特征比对
4.特征数据存储与比对
其他特征没有添加
face_class.py
我要评论复制代码
from ctypes import *
#人脸框
class mrect(structure):
_fields_=[(u'left1',c_int32),(u'top1',c_int32),(u'right1',c_int32),(u'bottom1',c_int32)]
#版本信息 版本号,构建日期,版权说明
class asf_version(structure):
_fields_=[('version',c_char_p),('builddate',c_char_p),('copyright',c_char_p)]
#单人人脸信息 人脸狂,人脸角度
class asf_singlefaceinfo(structure):
_fields_=[('facerect',mrect),('faceorient',c_int32)]
#多人人脸信息 人脸框数组,人脸角度数组,人脸数
class asf_multifaceinfo(structure):
# _fields_=[('facerect',pointer(mrect)),('faceorient',pointer( c_int32)),('facenum',c_int32)]
_fields_=[(u'facerect',pointer(mrect)),(u'faceorient',pointer(c_int32)),(u'facenum', c_int32)]
# _fields_=[(u'facerect',mrect*50),(u'faceorient',c_int32*50),(u'facenum',c_int32)]
#人脸特征 人脸特征,人脸特征长度
class asf_facefeature(structure):
_fields_=[('feature',c_void_p),('featuresize',c_int32)]
#自定义图片类
class im:
def __init__(self):
self.filepath=none
self.date=none
self.width=0
self.height=0
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face_dll.py
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from ctypes import *
from face_class import *
wuyongdll=cdll('d:\python\test\face\lib\x64\libarcsoft_face.dll')
dll=cdll('d:\python\test\face\lib\x64\libarcsoft_face_engine.dll')
dllc=cdll.msvcrt
asf_detect_mode_video = 0x00000000
asf_detect_mode_image = 0xffffffff
c_ubyte_p = pointer(c_ubyte)
#激活
jihuo=dll.asfactivation
jihuo.restype = c_int32
jihuo.argtypes = (c_char_p,c_char_p)
#初始化
chushihua=dll.asfinitengine
chushihua.restype=c_int32
chushihua.argtypes=(c_long,c_int32,c_int32,c_int32,c_int32,pointer(c_void_p))
#人脸识别
shibie=dll.asfdetectfaces
shibie.restype=c_int32
shibie.argtypes=(c_void_p,c_int32,c_int32,c_int32,pointer(c_ubyte),pointer(asf_multifaceinfo))
#特征提取
tezheng=dll.asffacefeatureextract
tezheng.restype=c_int32
tezheng.argtypes=(c_void_p,c_int32,c_int32,c_int32,pointer(c_ubyte),pointer(asf_singlefaceinfo),pointer(asf_facefeature))
#特征比对
bidui=dll.asffacefeaturecompare
bidui.restype=c_int32
bidui.argtypes=(c_void_p,pointer(asf_facefeature),pointer(asf_facefeature),pointer(c_float))
malloc = dllc.malloc
free = dllc.free
memcpy = dllc.memcpy
malloc.restype = c_void_p
malloc.argtypes = (c_size_t, )
free.restype = none
free.argtypes = (c_void_p, )
memcpy.restype = c_void_p
memcpy.argtypes = (c_void_p, c_void_p, c_size_t)
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face_function.py
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import face_dll,face_class
from ctypes import *
import cv2
from io import bytesio
# from main import *
handle=c_void_p()
c_ubyte_p = pointer(c_ubyte)
# 激活函数
def jh(appkey,sdkey):
ret=face_dll.jihuo(appkey,sdkey)
return ret
# 初始化函数
def csh():# 1：视频或图片模式,2角度,3最小人脸尺寸推荐16,4最多人脸数最大50,5功能,6返回激活句柄
ret=face_dll.chushihua(0xffffffff,0x1,16,50,5,byref(handle))
# main.handle=handle
return ret,handle
# cv2记载图片并处理
def loadimg(im):
img=cv2.imread(im.filepath)
sp=img.shape
img=cv2.resize(img,(sp[1]//4*4,sp[0]//4*4))
sp=img.shape
im.data=img
im.width=sp[1]
im.height=sp[0]
return im
def rlsb(im):
faces=face_class.asf_multifaceinfo()
img=im.data
imgby=bytes(im.data)
imgcuby=cast(imgby,c_ubyte_p)
ret=face_dll.shibie(handle,im.width,im.height,0x201,imgcuby,byref(faces))
return ret,faces
# 显示人脸识别图片
def showimg(im,faces):
for i in range(0,faces.facenum):
ra=faces.facerect[i]
cv2.rectangle(im.data,(ra.left1,ra.top1),(ra.right1,ra.bottom1),(255,0,0,),2)
cv2.imshow('faces',im.data)
cv2.waitkey(0)
#提取人脸特征
def rltz(im,ft):
detectedfaces=face_class.asf_facefeature()
img=im.data
imgby=bytes(im.data)
imgcuby=cast(imgby,c_ubyte_p)
ret=face_dll.tezheng(handle,im.width,im.height,0x201,imgcuby,ft,byref(detectedfaces))
if ret==0:
retz=face_class.asf_facefeature()
retz.featuresize=detectedfaces.featuresize
#必须操作内存来保留特征值,因为c++会在过程结束后自动释放内存
retz.feature=face_dll.malloc(detectedfaces.featuresize)
face_dll.memcpy(retz.feature,detectedfaces.feature,detectedfaces.featuresize)
# print('提取特征成功:',detectedfaces.featuresize,mem)
return ret,retz
else:
return ret
#特征值比对,返回比对结果
def bd(tz1,tz2):
jg=c_float()
ret=face_dll.bidui(handle,tz1,tz2,byref(jg))
return ret,jg.value
#单人特征写入文件
def writeftfile(feature,filepath):
f = bytesio(string_at(feature.feature,feature.featuresize))
a=open(filepath,'wb')
a.write(f.getvalue())
a.close()
#从多人中提取单人数据
def getsingleface(singleface,index):
ft=face_class.asf_singlefaceinfo()
ra=singleface.facerect[index]
ft.facerect.left1=ra.left1
ft.facerect.right1=ra.right1
ft.facerect.top1=ra.top1
ft.facerect.bottom1=ra.bottom1
ft.faceorient=singleface.faceorient[index]
return ft
#从文件获取特征值
def ftfromfile(filepath):
fas=face_class.asf_facefeature()
f=open('d:/1.dat','rb')
b=f.read()
f.close()
fas.featuresize=b.__len__()
fas.feature=face_dll.malloc(fas.featuresize)
face_dll.memcpy(fas.feature,b,fas.featuresize)
return fas
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import face_dll,face_class
from ctypes import *
import cv2
import face_function as fun
appkey=b''
sdkey=b''
# 激活
ret=fun.jh(appkey,sdkey)
if ret==0 or ret==90114:
print('激活成功:',ret)
else:
print('激活失败:',ret)
pass
# 初始化
ret=fun.csh()
if ret[0]==0:
print('初始化成功:',ret,'句柄',fun.handle)
else:
print('初始化失败:',ret)
# 加载图片
im=face_class.im()
im.filepath='e:/2.jpg'
im=fun.loadimg(im)
print(im.filepath,im.width,im.height)
# cv2.imshow('im',im.data)
# cv2.waitkey(0)
print('加载图片完成:',im)
ret=fun.rlsb(im)
if ret[0]==-1:
print('人脸识别失败:',ret)
pass
else:
print('人脸识别成功:',ret)
# 显示人脸照片
# showimg(im,ret)
#提取单人1特征
ft=fun.getsingleface(ret[1],0)
tz1=fun.rltz(im,ft)[1]
#提取单人2特征
ft=fun.getsingleface(ret[1],1)
tz2=fun.rltz(im,ft)[1]
#特征保存到文件
# fun.writeftfile(tz1,'d:/1.dat')
# fun.writeftfile(tz2,'d:/2.dat')
#文件获取特征
tz=fun.ftfromfile('d:/1.dat')
jg=fun.bd(tz1,tz)
print(jg[1])
#结果比对
# jg=fun.bd(tz1,tz2)
# print(jg[1])
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