如何使用 python 接入虹軟 ArcFace SDK

公司須要在項目中使用人臉識別SDK,而且對信息安全的要求很是高,在詳細瞭解市場上幾個主流人臉識別SDK後,綜合來看虹軟的Arcface SDK比較符合咱們的需求,它提供了免費版本,而且能夠在離線環境下使用,這一點很是符合咱們對安全性的要求。python

但有個遺憾的事情,咱們的項目主要使用了Python語言,虹軟官方並無提供Python版本的SDK,所以我本身使用Python封裝了Arcface C++ SDK,便於在項目中使用,這裏將主要過程寫出來供你們探討下。 數組

1.環境說明 

a. 注意Win64環境的Python必須使用ArcFace C++(Win64) SDK,若是平臺不一致, 不然可能會出現如下錯誤。 安全

OSError: [WinError 193] %1 不是有效的 Win32 應用程序複製代碼

b. 因爲SDK中涉及到內存操做,本文使用了ctypes包和cdll包提供的如下幾種方式  bash

c_ubyte_p = POINTER(c_ubyte) memcpy = cdll.msvcrt.memcpy malloc = cdll.msvcrt.malloc malloc.restype = c_void_p free = cdll.msvcrt.free複製代碼

2.Arcface SDK基本數據結構封裝

 在封裝數據結構時,必定要注意參數類型,不然可能會致使程序出錯。數據結構

class MRECT(Structure): # 人臉框 
    _fields_ = [(u'left', c_int32), 
           (u'top', c_int32), 
           (u'right', c_int32), 
           (u'bottom', c_int32)]  class ASFVersion(Structure): # 版本信息 版本號 構建日期 版權說明 
    _fields_ = [ ('Version', c_char_p), 
           ('BuildDate', c_char_p), 
           ('CopyRight', c_char_p)]  class ASFSingleFaceInfo(Structure): # 單人臉信息 人臉框 人臉角度 
   _fields_ = [ ('faceRect', MRECT), 
          ('faceOrient', c_int32)]  class ASFMultiFaceInfo(Structure): # 多人臉信息 人臉框數組 人臉角度數組 人臉數 
    _fields_ = [ (u'faceRect', POINTER(MRECT)), 
           (u'faceOrient', POINTER(c_int32)), 
           (u'faceNum', c_int32)]  class ASFFaceFeature(Structure): # 人臉特徵 人臉特徵 人臉特徵長度 
    _fields_ = [ ('feature', c_void_p), 
           ('featureSize', c_int32)]  class ASFFace3DAngle(Structure): # 人臉角度信息 
    _fields_ = [ ('roll', c_void_p), 
           ('yaw', c_void_p), 
           ('pitch', c_void_p), 
           ('status', c_void_p), 
           ('num', c_int32)]  class ASFAgeInfo(Structure): # 年齡 
    _fields_ = [ (u'ageArray', c_void_p), 
           (u'num', c_int32)]  class ASFGenderInfo(Structure): # 性別 
    _fields_ = [ (u'genderArray', c_void_p), 
           (u'num', c_int32)]  class ASFLivenessThreshold(Structure): # 活體閾值 
    _fields_ = [ (u'thresholdmodel_BGR', c_float), 
           (u'thresholdmodel_IR', c_int32)]  class ASFLivenessInfo(Structure): # 活體信息 
    _fields_ = [ (u'isLive', c_void_p), 
           (u'num', c_int32)] 複製代碼

3.Arcface SDK接口封裝

 a. 接口封裝以前須要加載dll庫,Arcface SDK 提供的dll都須要加載。 app

 b. 本文中圖片格式使用了ASVL_PAF_RGB24_B8G8R8。 ui

 c. 每一個接口都須要定義返回值以及參數類型,某些參數類型依賴前文所述的基本數據結構。 spa

from arcsoft_face_struct import * from ctypes import * from enum import Enum 

face_dll = CDLL("libarcsoft_face.dll") 
face_engine_dll = CDLL("libarcsoft_face_engine.dll") 

ASF_DETECT_MODE_VIDEO = 0x00000000 
ASF_DETECT_MODE_IMAGE = 0xFFFFFFFF ASF_NONE = 0x00000000 
ASF_FACE_DETECT = 0x00000001 ASF_FACE_RECOGNITION = 0x00000004 
ASF_AGE = 0x00000008 
ASF_GENDER = 0x00000010 
ASF_FACE3DANGLE = 0x00000020 
ASF_LIVENESS = 0x00000080 
ASF_IR_LIVENESS = 0x00000400 
ASVL_PAF_RGB24_B8G8R8 = 0x201 

class ArcSoftFaceOrientPriority(Enum): 
    ASF_OP_0_ONLY = 0x1, 
    ASF_OP_90_ONLY = 0x2, 
    ASF_OP_270_ONLY = 0x3, 
    ASF_OP_180_ONLY = 0x4, 
    ASF_OP_0_HIGHER_EXT = 0x5, 

activate = face_engine_dll.ASFActivation 
activate.restype = c_int32 
activate.argtypes = (c_char_p, c_char_p) 

init_engine = face_engine_dll.ASFInitEngine 
init_engine.restype = c_int32 
init_engine.argtypes = (c_long, c_int32, c_int32, c_int32, c_int32, POINTER(c_void_p)) 

detect_face = face_engine_dll.ASFDetectFaces 
detect_face.restype = c_int32 
detect_face.argtypes = (c_void_p, c_int32, c_int32, c_int32, POINTER(c_ubyte), POINTER(ASFMultiFaceInfo)) 

extract_feature = face_engine_dll.ASFFaceFeatureExtract 
extract_feature.restype = c_int32 
extract_feature.argtypes = (c_void_p, c_int32, c_int32, c_int32, POINTER(c_ubyte), 
                            POINTER(ASFSingleFaceInfo), POINTER(ASFFaceFeature)) 

compare_feature = face_engine_dll.ASFFaceFeature
Compare compare_feature.restype = c_int32 
compare_feature.argtypes = (c_void_p, POINTER(ASFFaceFeature), POINTER(ASFFaceFeature), POINTER(c_float)) 

set_liveness_param = face_engine_dll.ASFSetLivenessParam 
set_liveness_param.restype = c_int32 
set_liveness_param.argtypes = (c_void_p, POINTER(ASFLivenessThreshold)) 

process = face_engine_dll.ASFProcess process.restype = 
c_int32 process.argtypes = (c_void_p, c_int32, c_int32, c_int32, POINTER(c_ubyte), 
                            POINTER(ASFMultiFaceInfo), c_int32) 

get_age = face_engine_dll.ASFGetAge 
get_age.restype = c_int32 
get_age.argtypes = (c_void_p, POINTER(ASFAgeInfo)) 

get_gender = face_engine_dll.ASFGetGender 
get_gender.restype = c_int32 
get_gender.argtypes = (c_void_p, POINTER(ASFGenderInfo)) 

get_3d_angle = face_engine_dll.ASFGetFace3DAngle 
get_3d_angle.restype = c_int32 
get_3d_angle.argtypes = (c_void_p, POINTER(ASFFace3DAngle)) 

get_liveness_info = face_engine_dll.ASFGetLivenessScore 
get_liveness_info.restype = c_int32 
get_liveness_info.argtypes = (c_void_p, POINTER(ASFLivenessInfo)) 複製代碼

4.封裝接口調用 

接下來按照下面的流程圖介紹接口調用(此圖使用 Microsoft Visio 2016自動生成)。3d

                                    

下圖是按照此流程處理獲得的效果圖,因爲畫面有限,只顯示了年齡、性別、活體信息。rest


a. 激活 

須要注意app_id和sdk_key須要使用字節類型。

app_id = b"" 
sdk_key = b"" 
ret = arcsoft_face_func.activate(app_id, sdk_key) # 激活 
if ret == 0 or ret == 90114: 
    print("激活成功") 
else: 
    print("激活失敗:", ret) 複製代碼

b. 初始化 

 初始化須要將全部須要的功能參數一次性傳入,本文使用了人臉檢測、特徵提取等功能。 

mask = arcsoft_face_func.ASF_FACE_DETECT | \
            arcsoft_face_func.ASF_FACE_RECOGNITION | \
            arcsoft_face_func.ASF_AGE | \
            arcsoft_face_func.ASF_GENDER | \
            arcsoft_face_func.ASF_FACE3DANGLE |\
            arcsoft_face_func.ASF_LIVENESS

    engine = c_void_p()
    ret = arcsoft_face_func.init_engine(arcsoft_face_func.ASF_DETECT_MODE_IMAGE,
                                        arcsoft_face_func.ArcSoftFaceOrientPriority.ASF_OP_0_ONLY.value[0],
                                   30, 10, mask, byref(engine))
    if ret == 0:
        print("初始化成功")
    else:
        print("初始化失敗:", ret)複製代碼

c. 人臉檢測 

本文使用了opencv讀圖,兼容性更好,而且自定義的數據結構記錄圖片信息,注意 ArcFace C++ SDK 要求傳入的圖像寬度須要是4的倍數,下面作了裁剪。

 class Image:
    def __init__(self):
        self.width = 0
        self.height = 0
        self.imageData = None

def load_image(file_path):
    img = cv2.imread(file_path)
    sp = img.shape
    img = cv2.resize(img, (sp[1]//4*4, sp[0]))# 四字節對齊

    image = Image()
    image.width = img.shape[1]
    image.height = img.shape[0]
    image.imageData = img
    return image複製代碼
###################### 人臉檢測 ##################################

    image1 = load_image(r"1.jpg")
    image_bytes = bytes(image1.imageData)
    image_ubytes = cast(image_bytes, c_ubyte_p)

    detect_faces = ASFMultiFaceInfo()
    ret = arcsoft_face_func.detect_face(
        engine,
        image1.width,
        image1.height,
        arcsoft_face_func.ASVL_PAF_RGB24_B8G8R8,
        image_ubytes,
        byref(detect_faces)
    )

    if ret == 0:
        print("檢測人臉成功")
    else:
        print("檢測人臉失敗:", ret)複製代碼

d. 特徵提取 

特徵提取只支持單人臉,所以作了人臉處理操做,而且須要及時將提取的人臉特徵拷貝一份,不然會被覆蓋。 

 single_face1 = ASFSingleFaceInfo()
    single_face1.faceRect = detect_faces.faceRect[0]
    single_face1.faceOrient = detect_faces.faceOrient[0]

    face_feature = ASFFaceFeature()
    ret = arcsoft_face_func.extract_feature(
        engine,
        image1.width,
        image1.height,
        arcsoft_face_func.ASVL_PAF_RGB24_B8G8R8,
        image_ubytes,
        single_face1,
        byref(face_feature)
    )

    if ret == 0:
        print("提取特徵1成功")
    else:
        print("提取特徵1失敗:", ret)

    feature1 = ASFFaceFeature()
    feature1.featureSize = face_feature.featureSize
    feature1.feature = malloc(feature1.featureSize)
    memcpy(c_void_p(feature1.feature),
           c_void_p(face_feature.feature),
           feature1.featureSize)複製代碼

e. 特徵比對 

按照前文所述再提取一張人臉的特徵,便可以進行下面的人臉特徵比對操做 

compare_threshold = c_float()
    ret = arcsoft_face_func.compare_feature(
        engine, feature1, feature2, compare_threshold
    )

    free(c_void_p(feature1.feature))
    free(c_void_p(feature2.feature))

    if ret == 0:
        print("特徵比對成功,類似度:", compare_threshold.value)
    else:
        print("特徵比對失敗:", ret)複製代碼

f. 年齡、性別、3D Angle 

process接口目前提供了 年齡、性別、3D Angle、活體檢測, 但年齡、性別、3D Angle支持多人臉,而活體只支持單人臉,所以下面分別處理。 

process_mask = arcsoft_face_func.ASF_AGE | \
                   arcsoft_face_func.ASF_GENDER | \
                   arcsoft_face_func.ASF_FACE3DANGLE

    ret = arcsoft_face_func.process(
        engine,
        image1.width,
        image1.height,
        arcsoft_face_func.ASVL_PAF_RGB24_B8G8R8,
        image_ubytes,
        byref(detect_faces),
        c_int32(process_mask)
    )

    if ret == 0:
        print("process成功")
    else:
        print("process失敗:", ret) 複製代碼
######################## Age ################################

    age_info = ASFAgeInfo()
    ret = arcsoft_face_func.get_age(engine, byref(age_info))

    if ret == 0:
        print("get_age 成功")
        age_ptr = cast(age_info.ageArray, POINTER(c_int))
        for i in range(age_info.num):
            print("face", i, "age:", age_ptr[i])
    else:
        print("get_age 失敗:", ret)

####################### Gender #################################

    gender_info = ASFGenderInfo()
    ret = arcsoft_face_func.get_gender(engine, byref(gender_info))

    if ret == 0:
        print("get_gender 成功")
        gender_ptr = cast(gender_info.genderArray, POINTER(c_int))
        for i in range(gender_info.num):
            print("face", i, "gender:",
                  "女性" if (gender_ptr[i] == 1) else (
                      "男性" if (gender_ptr[i] == 0) else "未知"
                  ))
    else:
        print("get_gender 失敗:", ret)

####################### 3D Angle #################################

    angle_info = ASFFace3DAngle()
    ret = arcsoft_face_func.get_3d_angle(engine, byref(angle_info))

    if ret == 0:
        print("get_3d_angle 成功")
        roll_ptr = cast(angle_info.roll, POINTER(c_float))
        yaw_ptr = cast(angle_info.yaw, POINTER(c_float))
        pitch_ptr = cast(angle_info.pitch, POINTER(c_float))
        status_ptr = cast(angle_info.status, POINTER(c_int32))
        for i in range(angle_info.num):
            print("face", i,
                  "roll:", roll_ptr[i],
                  "yaw:", yaw_ptr[i],
                  "pitch:", pitch_ptr[i],
                  "status:", "正常" if status_ptr[i] == 0 else "出錯")

    else:
        print("get_3d_angle 失敗:", ret)複製代碼

g. RGB活體 

在活體檢測以前建議按照實際場景設置活體閾值,不設置即便用默認閾值,這裏設置了RGB活體的閾值爲0.75。並將檢測的多人臉分別轉爲單張人臉的參數傳到接口中。

######################### 活體閾值設置 ############################### 
    threshold_param = ASFLivenessThreshold()
    threshold_param.thresholdmodel_BGR = 0.75
    ret = arcsoft_face_func.set_liveness_param(engine,threshold_param)

    if ret == 0:
        print("set_liveness_param成功")
    else:
        print("set_liveness_param 失敗:", ret)

    temp_face_info = ASFMultiFaceInfo()
    temp_face_info.faceNum = 1
    LP_MRECT = POINTER(MRECT)
    temp_face_info.faceRect = LP_MRECT(MRECT(malloc(sizeof(MRECT))))
    LP_c_long = POINTER(c_long)
    temp_face_info.faceOrient = LP_c_long(c_long(malloc(sizeof(c_long))))

    for i in range(detect_faces.faceNum):
        temp_face_info.faceRect[0] = detect_faces.faceRect[i]
        temp_face_info.faceOrient[0] = detect_faces.faceOrient[i]

        ret = arcsoft_face_func.process(
            engine,
            image1.width,
            image1.height,
            arcsoft_face_func.ASVL_PAF_RGB24_B8G8R8,
            image_ubytes,
            byref(temp_face_info),
            c_int32(arcsoft_face_func.ASF_LIVENESS)
        )

        if ret == 0:
            print("process成功")
        else:
            print("process失敗:", ret)
        ## RGB活體檢測
        ret = arcsoft_face_func.process(
            engine,
            image1.width,
            image1.height,
            arcsoft_face_func.ASVL_PAF_RGB24_B8G8R8,
            image_ubytes,
            byref(temp_face_info),
            c_int32(arcsoft_face_func.ASF_LIVENESS)
        )

        if ret == 0:
            print("process成功")
        else:
            print("process失敗:", ret)

        liveness_info = ASFLivenessInfo()
        ret = arcsoft_face_func.get_liveness_info(engine, byref(liveness_info))

        if ret == 0:
            print("get_liveness_info 成功")
            liveness_ptr = cast(liveness_info.isLive, POINTER(c_int))
            print("face", i, "liveness:",
                  "非真人" if (liveness_ptr[0] == 0) else (
                      "真人" if (liveness_ptr[0] == 1) else (
                          "不肯定" if (liveness_ptr[0] == -1) else (
                              "傳入人臉數>1" if (liveness_ptr[0] == -2) else
                              (liveness_ptr[0])
                          )
                      )
                  ))
        else:
            print("get_liveness_info 失敗:", ret)複製代碼

最後,歡迎你們指教哦~

推薦大家瞭解虹軟人臉識別SDK~

ai.arcsoft.com.cn/ucenter/use…

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