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[项目] 虚谷号体验（六) 人工智能案例体验：人脸识别

本帖最后由 szjuliet 于 2020-7-5 08:59 编辑

虚谷号体验（一）开箱及基本功能体验
虚谷号体验（二）安装远程桌面及蓝牙设备
虚谷号体验（三）主机模式体验
虚谷号体验（四）人工智能案例体验：文字识别
虚谷号体验（五）人工智能案例体验：动植物识别
虚谷号体验（六) 人工智能案例体验：人脸识别

摄像头获取图像来识别人脸，并输出人脸的属性：年龄、性别、表情、是否佩戴眼镜、情绪、人种、相貌、脸型等。

1.设备连接：
虚谷号连接高清电视、摄像头，通电：
虚谷号体验（六) 人工智能案例体验：人脸识别图1

2. 百度云中创建应用（如使用体验文档的KEY，则可以跳过这步）

登录百度云，选择需要使用的服务

点击创建应用，输入相应的信息（应用名称、应用类型、应用描述等），拖到窗口最底部，点击“立即创建”

创建成功后记录下应用的API_KEY和SECRET_KEY，并填写到第3步的程序中

3. 修改程序：
虚谷号U盘模式\vvBoard\Python\01.example\03.人工智能目录下复制程序face_info.py到电脑上进行编辑：
[mw_shl_code=python,true]#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 18 13:02:42 2018

@author: james
"""

import cv2
import requests
import json
import threading
import time
import base64
import numpy as np
import xugu

# servo=xugu.Servo(12)
# access_token="24.42017d996da0a23f3c4567b8dfd16a21.2592000.1550220300.282335-14563606"
access_token =""
# API_KEY="ijoqlG1PdSsdxtXc7DNn68jh"
API_KEY = "" # 输入自己的API_KEY
# SECRET_KEY = "Erpr184wiWCG7ZZglFKKG3Zm3up6xUmi"
SECRET_KEY = "" # 输入自己的SECRET_KEY
face_num = 0
frame=None
now_time=0
face_info={}

def cvimg_to_b64(img):
try:
      image = cv2.imencode('.jpg', img)[1]
      base64_data = str(base64.b64encode(image))[2:-1]
      return base64_data
except Exception as e:
      return "error"

def face_search(img64):
url="https://aip.baidubce.com/rest/2.0/face/v3/search"
url=url+"?access_token="+access_token
data={
         "image":img64,
         "image_type":"BASE64",
         "group_id_list":"test_group"}
try:
      response=requests.post(url,files=None,data=data)
      res_text=response.text
      res_json=json.loads(res_text)
      return res_json
except Exception:
      return "error"

def get_ai_access_token():
url="https://aip.baidubce.com/oauth/2.0/token?grant_type=" +\
"client_credentials&client_id=%s&client_secret=%s" %(API_KEY,SECRET_KEY)
try:
      response=requests.get(url)
      res_text=response.text
      res_json=json.loads(res_text)
      return str(res_json["access_token"])
except Exception:
      return "error"

def get_face_info(img64):
url="https://aip.baidubce.com/rest/2.0/face/v3/detect"
url = url + "?access_token=" + access_token
data = {"face_field": "age,beauty,emotion,face_shape,gender,glasses,race,qualities,expression",
         "image_type": "BASE64", "image": img64, "max_face_num": 5}
try:
      response = requests.post(url,data=data)
      res_text=response.text
      res_json=json.loads(res_text)
      return res_json
except Exception:
      return "error"

def post_request(frame,face_num,nt):
global face_info
if(face_num>0) and (time.time()-nt>3):
      global now_time
      now_time=time.time()
      img64=cvimg_to_b64(frame)
      res=get_face_info(img64)
      print(res)
      try:
         status=res['error_msg']
      except Exception:
         status=""
      if(status=="SUCCESS"):
         face_info['gender']= res['result']['face_list'][0]['gender']['type']
         face_info['age']=res['result']['face_list'][0]['age']
         face_info['beauty']=res['result']['face_list'][0]['beauty']
         face_info['emotion'] = res['result']['face_list'][0]['emotion']['type']
         face_info['faceshape'] = res['result']['face_list'][0]['face_shape']['type']
         face_info['glasses'] = res['result']['face_list'][0]['glasses']['type']
         face_info['expression'] = res['result']['face_list'][0]['expression']['type']
         face_info['race'] = res['result']['face_list'][0]['race']['type']
         # face_info['qualities'] = res['result']['face_list'][0]['qualities']
         return
      else:
         face_info={}

def faceDetect(img,face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')):
size=img.shape[:2]
divisor = 8
h,w=size
minSize=(w//divisor,h//divisor)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.2, 1,cv2.CASCADE_SCALE_IMAGE,minSize)
for (x,y,w,h) in faces:
      cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
return img,len(faces)

def put_Text(cvimg,text,location,size=1):
cvimg=cv2.putText(cvimg, text, location,cv2.FONT_HERSHEY_SIMPLEX, size, (51, 102, 255), 3)
return cvimg

def check_token():
print(int(time.time()) - 1547628298)
if int(time.time()) - 1547628298 >= 2592000:
      global access_token
      token = get_ai_access_token()
      if token != "error":
         access_token = get_ai_access_token()

def main():
check_token()
cap = cv2.VideoCapture(0)
global now_time
now_time=time.time()
while(True):
      global face_info
      global servo
      ret, frame = cap.read()
      if ret == True:
         frame1,face_num = faceDetect(frame)
         frame1=cv2.flip(frame1,1,dst=None)
         frame1=cv2.resize(frame1,(1280,800),interpolation=cv2.INTER_LINEAR)
         t = threading.Thread(target=post_request, args=(
            frame, face_num, now_time,), name='POST_REQUEST')
         t.start()
         print(face_info)
         if face_info=={} :
            frame1=put_Text(frame1,"Waiting...",(50,50))
         else:
            try:
                  frame1=put_Text(frame1,str(int(face_info['age'])),(300,50))
                  frame1=put_Text(frame1,str(face_info['gender']),(300,120))
                  frame1=put_Text(frame1,str(int(face_info['beauty'])),(300,190))
                  frame1=put_Text(frame1,"Age:",(50,50))
                  frame1=put_Text(frame1,"Gender:",(50,120))
                  frame1=put_Text(frame1,"Beauty:",(50,190))
                  frame1 = put_Text(frame1, str((face_info['expression'])), (300, 260))
                  frame1 = put_Text(frame1, str(face_info['faceshape']), (300, 330))
                  frame1 = put_Text(frame1, str((face_info['glasses'])), (300, 400))
                  frame1 = put_Text(frame1, "Expression:", (50, 260))
                  frame1 = put_Text(frame1, "Faceshape:", (50, 330))
                  frame1 = put_Text(frame1, "Glasses:", (50, 400))
                  frame1 = put_Text(frame1, str((face_info['emotion'])), (300, 470))
                  frame1 = put_Text(frame1, str(face_info['race']), (300, 540))
                  # frame1 = put_Text(frame1, str(int(face_info['qualities'])), (300, 610))
                  frame1 = put_Text(frame1, "Emotion:", (50, 470))
                  frame1 = put_Text(frame1, "Race:", (50, 540))
                  # frame1 = put_Text(frame1, "Qualities:", (50, 610))
                  # servo.angle(int(face_info['beauty']*3))
            except Exception:
                  pass

         cv2.imshow('Magic Image',frame1)
      if cv2.waitKey(1) & 0xFF == ord('q'):
         break
cap.release()
cv2.destroyAllWindows()

main()[/mw_shl_code]

4. 将程序face_info上传到虚谷号桌面，同时将/home/scope/vvBoard/Python/01.example/03.人工智能/人脸识别目录下的依赖包也拖动到桌面
虚谷号体验（六) 人工智能案例体验：人脸识别图7

5. 在文件管理器中进入Desktop目录，运行LX终端
虚谷号体验（六) 人工智能案例体验：人脸识别图13

6. 输入命令python3 face_info.py，在当前目录下运行文字识别脚本
虚谷号体验（六) 人工智能案例体验：人脸识别图8

7. 很快会新建一个窗口，标题为Magic Image，用于显示采集的摄像头图像。
虚谷号体验（六) 人工智能案例体验：人脸识别图14

8. 输出结果
虚谷号体验（六) 人工智能案例体验：人脸识别图12

（不清楚为什么最后两行Emotion和Race为什么没有显示出来，检查了代码没发现问题）

人脸属性返回值：

参考资料：
https://ai.baidu.com/download?sdkId=3，SDK下载地址

http://ai.baidu.com/docs#/Face-Python-SDK/top，SDK使用说明

至此，体验文档里要求的内容已经全部完成。

在体验过程中对虚谷好的好感和认同度不断增加。这几天也把虚谷号公众号里几篇访谈文章认认真真的读完，觉得谢作如、管雪枫等一大批中国创客教育的先行者做了许多了不起事情。由衷的感动，钦佩！！

虚谷号, 人工智能, 人脸识别