2021百度人脸对比（附代码）

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我是靠谱客的博主迷人刺猬，这篇文章主要介绍2021百度人脸对比（附代码），现在分享给大家，希望可以做个参考。

百度API的各种接口非常方便易用，可以直接调用。

其实小白遇到最多的就是百度人脸识别和对比这块！！！

今天简单把最新的跑坑流程说明一下，希望咱们小白们少走坑。。。。

需要建立一个百度账号........不再多言了
依次点击个人头像---控制台总览--左上角蓝色方块下拉的人脸识别---创建应用-进入创建应用

点击2处进入应用列表可以看到key 可通过后台的API Key和Secret Key 获得参数access_token

复制代码

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def get_Token(self):
        self.client_id="API key"
        self.client_secret="secret key"
        host = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.client_id}&client_secret={self.client_secret}'
        response = requests.get(host)
        access_token=response.json()['access_token']
        return access_token

生成获得post的url
复制代码def get_API(self): self.access_token=self.get_Token() self.request_url='https://aip.baidubce.com/rest/2.0/face/v3/match' API_url = self.request_url + "?access_token=" + self.access_token return API_url
```
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def get_API(self):
        self.access_token=self.get_Token() 
        self.request_url='https://aip.baidubce.com/rest/2.0/face/v3/match'
        API_url = self.request_url + "?access_token=" + self.access_token  
        return API_url
```

生成post的params 是json格式注意str(pic1,'utf8')

复制代码

def get_Param(self):
        with open(r'%s' % self.img1,'rb') as f:     
            pic1=base64.b64encode(f.read())
        
        with open(r'%s' % self.img2,'rb') as f:     
            pic2=base64.b64encode(f.read())    
        
        params=[
                            {
                                "image": str(pic1,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "LIVE",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            },
                            {
                                "image": str(pic2,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "IDCARD",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            }
                        ]

return params

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    def get_Param(self):
        with open(r'%s' % self.img1,'rb') as f:     
            pic1=base64.b64encode(f.read())
        
        with open(r'%s' % self.img2,'rb') as f:     
            pic2=base64.b64encode(f.read())    
        
        params=[
                            {
                                "image": str(pic1,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "LIVE",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            },
                            {
                                "image": str(pic2,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "IDCARD",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            }
                        ]
       

        return params

向API-url post并获得数据对比
复制代码 def face_recogn(self): API_url=self.get_API() #pprint(API_url) params=self.get_Param() # pprint(params) headers = {'content-type': 'application/json'} response = requests.post(API_url, json=params, headers=headers) # pprint(response.json()) score=eval(response.text)['result']['score'] if score>=60: print('二人相似度得分为 %s, 是同一人的可能性极大'%str(score)) else: print('二人相似度得分为 %s, 不是同一人的可能性极大'%str(score))
```
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    def face_recogn(self):
        API_url=self.get_API()
        #pprint(API_url)
        params=self.get_Param() 
        # pprint(params)
        headers = {'content-type': 'application/json'}
        response = requests.post(API_url, json=params, headers=headers)
        # pprint(response.json())
        score=eval(response.text)['result']['score'] 
        if score>=60:  
            print('二人相似度得分为 %s, 是同一人的可能性极大'%str(score))
        else:
            print('二人相似度得分为 %s, 不是同一人的可能性极大'%str(score))
```
获得的json格式

完整代码

复制代码

import requests
import base64
from pprint import pprint
import json
# client_id 为官网获取的AK， client_secret 为官网获取的SK

class FaceContrast():
    def __init__(self, img1,img2):
        self.img1 = img1
        self.img2 = img2

def get_Token(self):
        self.client_id="fbGlSTRw9RsqnzpCChrwYDba"
        self.client_secret="rv9ZithXkFPIpXVVAr07ldlmLQUaW6jt"
        host = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.client_id}&client_secret={self.client_secret}'
        response = requests.get(host)
        access_token=response.json()['access_token']
        return access_token
        
    
    
    def get_API(self):
        self.access_token=self.get_Token() 
        self.request_url='https://aip.baidubce.com/rest/2.0/face/v3/match'
        API_url = self.request_url + "?access_token=" + self.access_token  
        return API_url

return params

def face_Recogn(self):
        API_url=self.get_API()
        pprint(API_url)
        params=self.get_Param() 
        # pprint(params)
        headers = {'content-type': 'application/json'}
        response = requests.post(API_url, json=params, headers=headers)
        # pprint(response.json())
        score=eval(response.text)['result']['score'] 
        if score>=60:  
            print('二人相似度得分为 %s, 是同一人的可能性极大'%str(score))
        else:
            print('二人相似度得分为 %s, 不是同一人的可能性极大'%str(score))

if __name__ == '__main__':
    img1="333.jpg"
    img2="444.jpg"
    face_contrast=FaceContrast(img1,img2)
    face_contrast.face_Recogn()

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import requests
import base64
from pprint import pprint
import json
# client_id 为官网获取的AK， client_secret 为官网获取的SK

class FaceContrast():
    def __init__(self, img1,img2):
        self.img1 = img1
        self.img2 = img2

    def get_Token(self):
        self.client_id="fbGlSTRw9RsqnzpCChrwYDba"
        self.client_secret="rv9ZithXkFPIpXVVAr07ldlmLQUaW6jt"
        host = f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={self.client_id}&client_secret={self.client_secret}'
        response = requests.get(host)
        access_token=response.json()['access_token']
        return access_token
        
    
    
    def get_API(self):
        self.access_token=self.get_Token() 
        self.request_url='https://aip.baidubce.com/rest/2.0/face/v3/match'
        API_url = self.request_url + "?access_token=" + self.access_token  
        return API_url

    def get_Param(self):
        with open(r'%s' % self.img1,'rb') as f:     
            pic1=base64.b64encode(f.read())
        
        with open(r'%s' % self.img2,'rb') as f:     
            pic2=base64.b64encode(f.read())    
        
        params=[
                            {
                                "image": str(pic1,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "LIVE",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            },
                            {
                                "image": str(pic2,'utf8'),
                                "image_type": "BASE64",
                                "face_type": "IDCARD",
                                "quality_control": "LOW",
                                "liveness_control": "HIGH"
                            }
                        ]
       

        return params


    def face_Recogn(self):
        API_url=self.get_API()
        pprint(API_url)
        params=self.get_Param() 
        # pprint(params)
        headers = {'content-type': 'application/json'}
        response = requests.post(API_url, json=params, headers=headers)
        # pprint(response.json())
        score=eval(response.text)['result']['score'] 
        if score>=60:  
            print('二人相似度得分为 %s, 是同一人的可能性极大'%str(score))
        else:
            print('二人相似度得分为 %s, 不是同一人的可能性极大'%str(score))



if __name__ == '__main__':
    img1="333.jpg"
    img2="444.jpg"
    face_contrast=FaceContrast(img1,img2)
    face_contrast.face_Recogn()