python3调用旷视人脸识别

python3调用旷视人脸识别

1.到旷视官网上注册申请key和secret

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2.人脸库图像准备，我的人脸库用图片如下：(图片文件名不能有中文，否则会调用错误)

3.根据官方api文档写几个post相关的函数

def detect_face(filepath):#检测图片里人脸信息http_url =""files = {"image_file": open(filepath, "rb")}data = {"api_key":key, "api_secret": secret}response = requests.post(http_url, data=data, files=files)req_dict = response.json()print(req_dict)return req_dictdef set_face(outer_id):#创建face_set人脸库url = ''params = {'api_key':key,'api_secret':secret,'outer_id':outer_id}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef addface(outer_id,facetokens):#将face加入到faceseturl = ''params = {'api_key':key,'api_secret':secret,#'faceset_token':faceset,'outer_id':outer_id,'face_tokens':facetokens}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dictdef face_search(image_file1,outer_id):#查找face库里有无对应人脸，默认返回result是最大脸结果url = ''files = {"image_file": open(image_file1, "rb")}params = {'api_key':key,'api_secret':secret,#'faceset_token':faceset_token,'outer_id':outer_id}r = requests.post(url,files = files,data = params)req_dict = r.json()print(req_dict)return req_dictdef face_search2(facetoken,outer_id):#根据facetoken来返回结果url = ''params = {'api_key':key,'api_secret':secret,'face_token':facetoken,'outer_id':outer_id}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dictdef getfaceset():#获取faceset信息url = ''params = {'api_key':key,'api_secret':secret,}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef deletefaceset(outer_id):#删除faceseturl = ''params = {'api_key':key,'api_secret':secret,'outer_id':outer_id,'check_empty':0}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef face_SetUserID(face_token,user_id):#为检测出的某一个人脸添加标识信息，该信息会在Search接口结果中返回，用来确定用户身份。url = ''params = {'api_key':key,'api_secret':secret,'face_token':face_token,'user_id':user_id}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dict

4.调用旷视api

1）创建人脸库faceset：创建faceset要用到Faceset的Face detect的api，

   首先，使用FaceSet Create API创建人脸库，然后使用Detect API历遍人脸图片目录，并把对应的facetoken保存在人脸库里并附加1个对应的‘userid’方便后续调用。

def makedataset(dataset_path='./database',outer_id='人脸库'):img_paths=os.listdir(dataset_path)user_ids=[img_path.split('.')[0] for img_path in img_paths] #解析人名img_paths=[os.path.join(dataset_path,img_path) for img_path in img_paths]#解析图片地址#1.创建Faceset,outerid为’人脸库‘set_face(outer_id)#创建人脸库faceset#2.人脸库中加入人脸tokenfor (user_id,img_path) in zip(user_ids,img_paths):face_json = detect_face(img_path)#检测图片中人脸face_token= face_json['faces'][0]['face_token']#获取人脸face_tokenaddface(outer_id,face_token)#把face_token追加到人脸库facesetface_SetUserID(face_token,user_id)#给face_token绑定1个user_id

2）人脸检测和识别 ：原face search的api只返回最大脸的识别结果，如果图片中所有的都要识别，则需要把图片里所有的检测出的face_token送入search api

def find_all_faces(img_path,outer_id='人脸库'):#找到图片里所有脸并标出face_json=detect_face(img_path)faces=face_json['faces']for face in faces:face['result']=face_search2(face['face_token'],outer_id)['results'][0]return facesdef find_biggest_face(img_path,outer_id='人脸库'):#找到图片里脸最大的并标出face_json=face_search(img_path,outer_id='人脸库')faces=[face_json['faces'][0]]faces[0]['result']=face_json['results'][0]return faces

3）检测结果绘制：由于opencv不支持中文显示，所以这里要使用pillow的库来处理

def draw_result(img,faces):#绘制结果（PIL库可以显示中文）textSize=20if (isinstance(img, np.ndarray)):  #判断是否OpenCV图片类型img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))draw = ImageDraw.Draw(img)fontText = ImageFont.truetype("/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc", textSize, encoding="utf-8")for face in faces:loc=face['face_rectangle']result=face['result']if loc['width']>35:#只处理宽度大于40的人脸draw.rectangle((loc['left'], loc['top'], loc['left']+loc['width'], loc['top']+loc['height']), None, (0,255,0),width=4)if result['confidence']>60:#根据置信率贴标text_show=name_dict[result['user_id']]+' '+str(result['confidence'])+'%'draw.text((loc['left'], loc['top']-textSize-4), text_show, (0,255,0), font=fontText)else:draw.text((loc['left'], loc['top']-textSize-4), '其他人', (0,255,0), font=fontText)return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)

检测效果图：

完整代码：

#--------------------利用旷视api进行人脸检测和识别---------------------
import requests
from json import JSONDecoder
import os
import cv2
from PIL import Image,ImageDraw,ImageFont
import numpy as np#定义key和sercet，需要到旷视网上申请注册
key = ""
secret = ""
#定义userid和人名的关系
name_dict={"HuangXiaoming":"黄晓明","DengChao":"邓超","HeJiong":"何炅","TongDawei":"佟大为","WangYuan":"王源","YangYing":"杨颖","YiYangqianxi":"易烊千玺","WangJunkai":"王俊凯"}def detect_face(filepath):#传入图片文件http_url =""files = {"image_file": open(filepath, "rb")}data = {"api_key":key, "api_secret": secret}response = requests.post(http_url, data=data, files=files)req_dict = response.json()print(req_dict)return req_dictdef set_face(outer_id):#创建face_seturl = ''params = {'api_key':key,'api_secret':secret,'outer_id':outer_id}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef addface(outer_id,facetokens):#将face加入到faceseturl = ''params = {'api_key':key,'api_secret':secret,#'faceset_token':faceset,'outer_id':outer_id,'face_tokens':facetokens}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dictdef face_search(image_file1,outer_id):#查找face库里有无对应人脸，默认返回result是最大脸结果url = ''files = {"image_file": open(image_file1, "rb")}params = {'api_key':key,'api_secret':secret,#'faceset_token':faceset_token,'outer_id':outer_id}r = requests.post(url,files = files,data = params)req_dict = r.json()print(req_dict)return req_dictdef face_search2(facetoken,outer_id):#根据facetoken来返回结果url = ''params = {'api_key':key,'api_secret':secret,'face_token':facetoken,'outer_id':outer_id}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dictdef getfaceset():#获取faceset信息url = ''params = {'api_key':key,'api_secret':secret,}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef deletefaceset(outer_id):#删除faceseturl = ''params = {'api_key':key,'api_secret':secret,'outer_id':outer_id,'check_empty':0}response = requests.post(url,data = params)req_dict = response.json()print(req_dict)return req_dictdef face_SetUserID(face_token,user_id):#为检测出的某一个人脸添加标识信息，该信息会在Search接口结果中返回，用来确定用户身份。url = ''params = {'api_key':key,'api_secret':secret,'face_token':face_token,'user_id':user_id}r = requests.post(url,data = params)req_dict = r.json()print(req_dict)return req_dictdef makedataset(dataset_path='./database',outer_id='人脸库'):img_paths=os.listdir(dataset_path)user_ids=[img_path.split('.')[0] for img_path in img_paths] #解析人名img_paths=[os.path.join(dataset_path,img_path) for img_path in img_paths]#解析图片地址#1.创建Faceset,outerid为’人脸库‘set_face(outer_id)#2.人脸库中加入人脸tokenfor (user_id,img_path) in zip(user_ids,img_paths):face_json = detect_face(img_path)face_token= face_json['faces'][0]['face_token']addface(outer_id,face_token)face_SetUserID(face_token,user_id)def draw_result(img,faces):#绘制结果（PIL库可以显示中文）textSize=20if (isinstance(img, np.ndarray)):  #判断是否OpenCV图片类型img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))draw = ImageDraw.Draw(img)fontText = ImageFont.truetype("/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc", textSize, encoding="utf-8")for face in faces:loc=face['face_rectangle']result=face['result']if loc['width']>35:#只处理宽度大于40的人脸draw.rectangle((loc['left'], loc['top'], loc['left']+loc['width'], loc['top']+loc['height']), None, (0,255,0),width=4)if result['confidence']>60:#根据置信率贴标text_show=name_dict[result['user_id']]+' '+str(result['confidence'])+'%'draw.text((loc['left'], loc['top']-textSize-4), text_show, (0,255,0), font=fontText)else:draw.text((loc['left'], loc['top']-textSize-4), '其他人', (0,255,0), font=fontText)return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)def find_all_faces(img_path,outer_id='人脸库'):#找到图片里所有脸并标出face_json=detect_face(img_path)faces=face_json['faces']for face in faces:face['result']=face_search2(face['face_token'],outer_id)['results'][0]return facesdef find_biggest_face(img_path,outer_id='人脸库'):#找到图片里脸最大的并标出face_json=face_search(img_path,outer_id='人脸库')faces=[face_json['faces'][0]]faces[0]['result']=face_json['results'][0]return facesif __name__ == "__main__":#makedataset(outer_id='人脸库')#dataset=getfaceset()#deletefaceset('人脸库')img_paths=os.listdir('./face_test')img_paths=[os.path.join('./face_test',img_path) for img_path in img_paths]index=0for img_path in img_paths:faces=find_all_faces(img_path,outer_id='人脸库')#faces=find_biggest_face(img_path,outer_id='人脸库')img=cv2.imread(img_path)img_result=draw_result(img,faces)cv2.imwrite('./result/'+str(index)+'.jpg',img_result)index=index+1#cv2.imshow('',img_result)#cv2.waitKey(0)