python3+arcface2.0 离线人脸识别 demo
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2022-05-17 16:42:55
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 sdk 下载请戳这里 face_class.py face_dll.py face_function.py Main1 ......
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
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 复制代码
face_dll.py
复制代码 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) 复制代码
face_function.py
复制代码 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 复制代码
复制代码 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]) 复制代码
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