python调用虹软2.0第三版的具体使用
这一版,对虹软的功能进行了一些封装,添加了人脸特征比对,比对结果保存到文件,和从文件提取特征进行比对,大体功能基本都已经实现,可以进行下一步的应用开发了
face_class.py
fromctypesimport*
#人脸框
classMRECT(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
classASF_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
classASF_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
classASF_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
classASF_FaceFeature(Structure):
_fields_=[('feature',c_void_p),('featureSize',c_int32)]
#自定义图片类
classIM:
def__init__(self):
self.filepath=None
self.date=None
self.width=0
self.height=0
face_dll.py
fromctypesimport*
fromface_classimport*
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)
face_function.py
importface_dll,face_class
fromctypesimport*
importcv2
fromioimportBytesIO
#fromMainimport*
Handle=c_void_p()
c_ubyte_p=POINTER(c_ubyte)
#激活函数
defJH(appkey,sdkey):
ret=face_dll.jihuo(appkey,sdkey)
returnret
#初始化函数
defCSH():#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
returnret,Handle
#cv2记载图片并处理
defLoadImg(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]
returnim
defRLSB(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))
returnret,faces
#显示人脸识别图片
defshowimg(im,faces):
foriinrange(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
defRLTZ(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))
ifret==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)
returnret,retz
else:
returnret
#特征值比对,返回比对结果
defBD(tz1,tz2):
jg=c_float()
ret=face_dll.bidui(Handle,tz1,tz2,byref(jg))
returnret,jg.value
#单人特征写入文件
defwriteFTFile(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
defgetsingleface(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]
returnft
#从文件获取特征值
defftfromfile(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)
returnfas
Main1.py
importface_dll,face_class
fromctypesimport*
importcv2
importface_functionasfun
Appkey=b''
SDKey=b''
#激活
ret=fun.JH(Appkey,SDKey)
ifret==0orret==90114:
print('激活成功:',ret)
else:
print('激活失败:',ret)
pass
#初始化
ret=fun.CSH()
ifret[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)
ifret[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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