这篇文章主要介绍了python实现百度OCR图片识别过程解析,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
代码如下
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
|
import base64
import requests
class CodeDemo:
def __init__( self ,AK,SK,code_url,img_path):
self .AK = AK
self .SK = SK
self .code_url = code_url
self .img_path = img_path
self .access_token = self .get_access_token()
def get_access_token( self ):
token_host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={ak}&client_secret={sk}' . format (ak = self .AK,sk = self .SK)
header = { 'Content-Type' : 'application/json; charset=UTF-8' }
response = requests.post(url = token_host,headers = header)
content = response.json()
access_token = content.get( "access_token" )
return access_token
def getCode( self ):
header = {
"Content-Type" : "application/x-www-form-urlencoded"
}
def read_img():
with open ( self .img_path, "rb" )as f:
return base64.b64encode(f.read()).decode()
image = read_img()
response = requests.post(url = self .code_url,data = { "image" :image, "access_token" : self .access_token},headers = header)
return response.json()
if __name__ = = '__main__' :
AK = "" # 官网获取的AK
SK = "" # 官网获取的SK
code_url = "https://aip.baidubce.com/rest/2.0/ocr/v1/accurate" # 百度图片识别接口地址
img_path = r"" # 识别图片的地址
code_obj = CodeDemo(AK = AK,SK = SK,code_url = code_url,img_path = img_path)
res = code_obj.getCode()
code = res.get( "words_result" )[ 0 ].get( "words" )
print (res)
print (code)
|
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:https://www.cnblogs.com/angelyan/p/11512450.html