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TensorFlow.js Captcha Recognition

This project aims to train and use TensorFlow.js to perform captcha recognition in the browser.

Table of Contents

Introduction

In this project, we leverage the power of TensorFlow to train a machine learning model for captcha recognition. By using TensorFlow.js, we can perform captcha recognition directly in the browser without the need for server-side processing.

Usage

Note: In this project, all captcha images are located in the data folder and are labeled by their filenames, with the following deformation characteristics:

  1. The characters are surrounded by a lot of noise
  2. The individual characters themselves are slightly distorted.

captcha example

To implement the captcha recognition functionality in your browser, follow these steps:

  1. prepare and label the captcha images for training
  2. run 0-preprocess.py to preprocess the captcha images
  3. run 1-generate_dataset.py to generate the dataset
  4. run 2-train_model.py to train the model
  5. run 3-test_model.py to test the model
  6. run 4-convert_tfjs_model.py to convert model for tensorflow.js

Now you have the model in the web/tfjs_model folder, start a server under the web directory, you can now perform captcha recognition in the browser.

License

Distributed under the GPLv3+ License. See LICENSE for more information.