python调用虹软2.0第三版的具体使用_Python

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

				?

									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

face_dll.py

				?

									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)

face_function.py

				?

									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

Main1.py

				?

									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])