Python2.7 和3.7 调用百度api识别人脸_image 027d8308a2ec665acb1bdf63e513bcb9-优快云博客

本文介绍了一种使用Python编程语言调用百度AI开放平台API的方法，实现从本地图片中识别面部表情。文章详细展示了如何读取图片、转换为Base64编码，以及如何设置必要的API参数来获取面部表情分析结果。

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废话不多说，参考文档里是使用

params = "{\"image\":\"027d8308a2ec665acb1bdf63e513bcb9\",\"image_type\":\"FACE_TOKEN\",\"face_field\":\"faceshape,facetype\"}"

但实际中我们要自己选择图片的路径，因此：

//获取文件的路径

filePath = r"C:\Users\abc\Desktop\text.jpg"
//定义一个读取函数，将api接口转成对应格式
def get_file_content(filePath):
    with open(filePath, 'rb') as fp:
        pic = base64.b64encode(fp.read())
        return pic
//image标签和image_type标签页是必传的参数，我这里在加入一个识别情绪的参数
params = {"image":''+get_file_content(filePath)+'', "image_type": "BASE64", "face_field": "expression"}
//这个挺关键
params = urllib.urlencode(params)

access_token = get_token()//这里是获取access_token的函数，我是动态获得
//接下来基本与百度文档一致，即可识别
request_url = request_url + "?access_token=" + access_token
request = urllib2.Request(url=request_url, data=params)
request.add_header('Content-Type', 'application/json')
response = urllib2.urlopen(request)
content = response.read()
if content:
    print content

附加上一下源码，这个是我在python3.7下识别的源码

#encoding:utf-8
import urllib, urllib3, base64,json,sys,ssl
import re
import cv2
from urllib import parse,request
#涉及图片路径的自己改
photopaths = r"C:\Users\abc\Desktop\image/"
APP_ID = '自己填'
API_KEY = '自己的'
SECRET_KEY = '自己的'
filePath = r"C:\Users\abc\Desktop\image\1.jpg"

def opencamere():
    camera = cv2.VideoCapture(0)
    cv2.namedWindow('MyCamera')
    c = 1
    while True:
        success, frame = camera.read()
        cv2.imshow('MyCamera', frame)
        if (c):
            c = c + 1
        if (c % 5 == 0):  # 每隔timeF帧进行存储操作
            cv2.imwrite(photopaths+str(1)+'.jpg',frame)
            print(recognize())
        if cv2.waitKey(1) & 0xff == ord('q'):
            break
    cv2.destroyWindow('MyCamera')
    camera.release()


def get_token():
    host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id='+API_KEY+'&client_secret='+SECRET_KEY
    re = request.Request(host)
    re.add_header('Content-Type', 'application/json; charset=UTF-8')
    response = request.urlopen(re)
    content = response.read()
    content = bytes.decode(content)
    content = eval(content[:-1])
    return content['access_token']



def get_file_content(filePath):
    with open(filePath, 'rb') as fp:
        pic = base64.b64encode(fp.read())
        return pic
#params = "{\"image\":\"027d8308a2ec665acb1bdf63e513bcb9\",\"image_type\":\"FACE_TOKEN\",\"face_field\":\"faceshape,facetype\"}"

def recognize():
    params = {"image": '' + str(get_file_content(filePath), 'utf-8') + '', "image_type": "BASE64",
              "face_field": "emotion"}
    params = parse.urlencode(params).encode('utf-8')
    access_token = get_token()
    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
    request_url = request_url + "?access_token=" + access_token
    message = request.Request(url=request_url, data=params)
    message.add_header('Content-Type', 'application/json')
    response = request.urlopen(message)
    content = response.read()
    #pat_emotion = re.compile('angry'|'happy'|'fear'|'sad',re.S)
    pat_emotion = re.compile('(angry|happy|fear|sad)')
    content = pat_emotion.findall(str(content))
    if content:
        print(content)
    return content
opencamere()