Python simply handles the verification code, three minutes, no more

preface

Hello, everyone , It's my little panda again

When we collect data , Too fast or frequently visited , Or you can pop up the verification code as soon as you visit , And then the clam bead ~

Today, I will give you a simple method to deal with the verification code

Environment module

Python and pycharm If there are still some friends who haven't installed it , You can scan the code at the bottom of the article to get the installation package .

There needs to be a ddddocr modular , This is something that someone else has written open source , Simple and easy to use , But the accuracy is a little poor , But it is still very easy to use .

If you want precision , You can call some written by others API .

Let's just win+r Enter... After the search box pops up cmd , Click OK to pop up the command prompt window , Input pip install ddddocr You can install .

If not, please refer to my top article for detailed explanation .

Code display https://jq.qq.com/?_wv=1027&k=3uTc6UFb

Not much code , It's simple .

After the module is installed, let's import it

import ddddocr

Then instantiate , Use one cor Receive this data .

ocr = ddddocr.DdddOcr()

I have prepared four verification codes here




Blog watermark seems to be blocked , But I won't turn it off , Hey ~

Back to the point , Implement the verification code respectively .

First of all, we use with open To read this file , The read mode uses rb , If it is a picture, read its binary data

with open('img_3.png', 'rb') as f:

Use f.read() Read the data out , Then customize a variable to receive .

img_bytes = f.read()

And then we passed classification Pass it in , Just print out the results .

result = ocr.classification(img_bytes)
print(result)

Realization effect (https://jq.qq.com/?_wv=1027&k=3uTc6UFb)

Pure digital


Letter + Digital


You can see that they are completely identified , Even if there are some fancy horizontal lines on it .

Complete code (https://jq.qq.com/?_wv=1027&k=3uTc6UFb)

import ddddocr
ocr = ddddocr.DdddOcr()
with open('img_3.png', 'rb') as f:
img_bytes = f.read()
result = ocr.classification(img_bytes)
print(result)
(https://jq.qq.com/?_wv=1027&k=3uTc6UFb)

You can try it yourself , It can also be directly applied to the practice of data collection ~

It's not easy to create , Let's help you to order a collection ~

I'm a panda , I'll see you in the next article (*◡‿◡)