[日常] Python3 调用 Baidu/Face++ 人脸检测 API 进行表情识别

目录

1. Baidu 人脸检测与属性分析 API
2. Face++ Detect API

1. Baidu 人脸检测与属性分析 API

相关文档：https://ai.baidu.com/docs#/Face-Detect-V3/b7203cd6

# 本份代码用于利用 Baidu 的人脸检测 API 进行表情检测
# 相关文档地址：https://ai.baidu.com/docs#/Face-Detect-V3/b7203cd6

# 作者：蒲韬，[email protected]
#　所需依赖：Python 3 
# 最后更新时间：2019.07.22

import os
import time
import json
import base64

import urllib
import urllib.request

class AverageMeter(object):
    '''Computes and stores the sum, count and average'''
    def __init__(self):
        self.reset()

    def reset(self):    
        self.val = 0
        self.avg = 0
        self.sum = 0
        self.count = 0

    def update(self, val, count=1):
        self.val = val
        self.sum += val 
        self.count += count
        if self.count==0:
            self.avg = 0
        else:
            self.avg = float(self.sum) / self.count

# 获取　Access_token
def getAcessToken():
    request = urllib.request.Request('https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=xV1lFbF4m4vIoy1sLpRfpR1f&client_secret=8Q3nLI1dQNOx8RSjeUPQh26VfAvc4scq') # client_id 为官网获取的AK， client_secret 为官网获取的SK
    request.add_header('Content-Type', 'application/json; charset=UTF-8')
    response = urllib.request.urlopen(request)
    content = json.loads(response.read().decode('utf-8')) # bytes 转　string
    return content['access_token']


# 读取目标图像并进行 Base64　编码
def getImage(imgPath):
    with open(imgPath, 'rb') as f:  # 以二进制读取图片
        data = f.read()
        encode = base64.b64encode(data) # 得到 byte 编码的数据
        encode = str(encode,'utf-8') # bytes 转　string

    return encode

# 调用　API　进行人脸检测与属性分析
def useAPI(imgPath,access_token):
    request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
    params = bytes("{\"image\":\""+ getImage(imgPath) +"\",\"image_type\":\"BASE64\",\"face_field\":\"emotion\"}", 'utf-8') # string 转 bytes
    
    request_url = request_url + "?access_token=" + access_token
    request = urllib.request.Request(url=request_url, data=params)
    request.add_header('Content-Type', 'application/json')

    response = urllib.request.urlopen(request)
    content = json.loads(response.read().decode('utf-8'))

    return content

if __name__=='__main__':

    access_token = getAcessToken()

    # 七类基本表情 -> angry:愤怒 disgust:厌恶 fear:恐惧 happy:高兴 sad:伤心 surprise:惊讶 neutral:无情绪
    Label = {'surprise':0, 'fear':1, 'disgust':2, 'happy':3, 'sad':4, 'angry':5, 'neutral':6}

    acc, prec, recall = AverageMeter(), [AverageMeter() for i in range(7)], [AverageMeter() for i in range(7)]

    pathName = ['surprised','fear','disgust','happy','sad','angry','neutral']
    for i in range(7):
        Dirs = os.listdir('/media/dm/新加卷/自建数据集/Asian_FacialExpression/data_6/val_filter/'+pathName[i])
        for imgFile in Dirs:
            imgPath = '/media/dm/新加卷/自建数据集/Asian_FacialExpression/data_6/val_filter/'+pathName[i]+'/'+imgFile
            content = useAPI(imgPath,access_token)

            if 'result' not in content.keys() or content['result'] is None:
                continue

            for result in content['result']['face_list']:
                pred = Label[result['emotion']['type']]

                if pred==i:
                    acc.update(1,1)
                    prec[i].update(1,1)
                    recall[i].update(1,1)
                else:
                    acc.update(0,1)
                    prec[pred].update(0,1)
                    recall[i].update(0,1)

            # 免费账号的　QPS 为 ２。（QPS（query per second）指每秒向服务发送的请求数量峰值，相当于每个API每秒可以允许请求的最大上限数量。）
            time.sleep(0.6)
                            
    print('''
    Sample {recall[0].count:d} {recall[1].count:d} {recall[2].count:d} {recall[3].count:d} {recall[4].count:d} {recall[5].count:d} {recall[6].count:d}\t
    Accuracy {acc.avg:.4f}\t
    Precision {prec[0].avg:.4f} {prec[1].avg:.4f} {prec[2].avg:.4f} {prec[3].avg:.4f} {prec[4].avg:.4f} {prec[5].avg:.4f} {prec[6].avg:.4f}\t
    Recall {recall[0].avg:.4f} {recall[1].avg:.4f} {recall[2].avg:.4f} {recall[3].avg:.4f} {recall[4].avg:.4f} {recall[5].avg:.4f} {recall[6].avg:.4f}\t
    '''.format(acc=acc,prec=prec,recall=recall))

2. Face++ Detect API

相关文档：https://console.faceplusplus.com.cn/documents/4888373

# 本份代码用于利用 Face++ 的人脸检测 API 进行表情检测
# 相关文档地址：https://console.faceplusplus.com.cn/documents/4888373

# 作者：蒲韬，[email protected]
#　所需依赖：Python 3 
# 最后更新时间：2019.07.22

import os
import time
import json
import base64
import requests
import numpy as np

import urllib
import urllib.request

class AverageMeter(object):
    '''Computes and stores the sum, count and average'''
    def __init__(self):
        self.reset()

    def reset(self):    
        self.val = 0
        self.avg = 0
        self.sum = 0
        self.count = 0

    def update(self, val, count=1):
        self.val = val
        self.sum += val 
        self.count += count
        if self.count==0:
            self.avg = 0
        else:
            self.avg = float(self.sum) / self.count

# 调用　API　进行人脸检测与属性分析
def useAPI(imgPath):
    request_url = "https://api-cn.faceplusplus.com/facepp/v3/detect"

    data = {
        "api_key" : "wM0qs88_n5Fcyb7LOhYiP-K_Y7Q8P7w4",
        "api_secret" : "7MNq0wPjjVT-Fg4-0uQQLu-4tnzlnzF7",
        "return_attributes" : "emotion",
    }
    files = {"image_file": open(imgPath, "rb")}

    response = requests.post(request_url, data=data, files=files)
    content = response.content.decode('utf-8')
    content = json.loads(content)

    return content

if __name__=='__main__':
    # 七类基本表情 -> angry:愤怒 disgust:厌恶 fear:恐惧 happy:高兴 sad:伤心 surprise:惊讶 neutral:无情绪
    Label = {'surprise':0, 'fear':1, 'disgust':2, 'happy':3, 'sad':4, 'angry':5, 'neutral':6}

    acc, prec, recall = AverageMeter(), [AverageMeter() for i in range(7)], [AverageMeter() for i in range(7)]

    pathName = ['surprised','fear','disgust','happy','sad','angry','neutral']
    for i in range(7):
        Dirs = os.listdir('/media/dm/新加卷/自建数据集/Asian_FacialExpression/data_6/val_filter/'+pathName[i])
        for imgFile in Dirs:
            imgPath = '/media/dm/新加卷/自建数据集/Asian_FacialExpression/data_6/val_filter/'+pathName[i]+'/'+imgFile
            content = useAPI(imgPath)

            if 'faces' not in content.keys() or content['faces'] is None:
                continue

            for face in content['faces']:
                result = face['attributes']['emotion']
                pred = np.array([result['surprise'],result['fear'],result['disgust'],result['happiness'],result['sadness'],result['anger'],result['neutral']])
                pred = np.argmax(pred)

                if pred==i:
                    acc.update(1,1)
                    prec[i].update(1,1)
                    recall[i].update(1,1)
                else:
                    acc.update(0,1)
                    prec[pred].update(0,1)
                    recall[i].update(0,1)

            # 免费账号的　QPS 为 10。（QPS（query per second）指每秒向服务发送的请求数量峰值，相当于每个API每秒可以允许请求的最大上限数量。）
            time.sleep(0.11)

    print('''
    Sample {recall[0].count:d} {recall[1].count:d} {recall[2].count:d} {recall[3].count:d} {recall[4].count:d} {recall[5].count:d} {recall[6].count:d}\t
    Accuracy {acc.avg:.4f}\t
    Precision {prec[0].avg:.4f} {prec[1].avg:.4f} {prec[2].avg:.4f} {prec[3].avg:.4f} {prec[4].avg:.4f} {prec[5].avg:.4f} {prec[6].avg:.4f}\t
    Recall {recall[0].avg:.4f} {recall[1].avg:.4f} {recall[2].avg:.4f} {recall[3].avg:.4f} {recall[4].avg:.4f} {recall[5].avg:.4f} {recall[6].avg:.4f}\t
    '''.format(acc=acc,prec=prec,recall=recall))

参考资料：

• PYTHON 3 调用face++API代码（简单易懂）

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