python3+虹软2.0 离线人脸识别 demo

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

虹软SDK下载戳这里

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]) 

 

 

转载于:https://www.cnblogs.com/Zzz-/p/10494187.html