CAPTCHA Recognition with Deep Learning

Crack the Code: CAPTCHA Recognition with Deep Learning and Python!

This blog post unveils a powerful Python project that tackles the challenge of CAPTCHA recognition using deep learning!  Ever felt frustrated by those distorted characters that stand between you and valuable online content? This project empowers you to fight back! (Watch the project in action here: https://www.youtube.com/watch?v=TlhbUL5b1B8 [invalid URL removed])

Outsmart CAPTCHAs with Deep Learning

CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart) are a common hurdle encountered on websites. They aim to distinguish between humans and automated bots. This project tackles this challenge by leveraging the power of deep learning.  A pre-trained deep learning model analyzes the CAPTCHA image and predicts the underlying text, effectively bypassing the CAPTCHA challenge.

A User-Friendly Solution: Web Interface

This project goes beyond just the technical aspects – it prioritizes user experience! It boasts a user-friendly web interface built with Flask, a popular Python web framework. Here's what you can expect:

• Effortless CAPTCHA Uploads:  Simply upload the CAPTCHA image you encounter, and the project takes care of the rest.

• Clear Text Recognition:  The predicted text from the CAPTCHA image is displayed prominently on the web interface, providing you with the key to access the desired content.

Setting Up Your CAPTCHA Slayer:

Here's a step-by-step guide to get you started with this CAPTCHA-crushing project:

1. Clone the Codebase: Grab the project's code using git clone:

Bash

git clone https://github.com/sairam-penjarla/cAPTCHA-identification.git
cd cAPTCHA-identification

1. Install Dependencies: The project relies on external libraries. Install them using pip:

Bash

pip install -r requirements.txt

1. Pre-Trained Model Download: The project relies on a pre-trained deep learning model. Download it and place it in the model directory as specified in the main.py file.

2. Launch the Application: Now that everything is set up, run the project using two commands:

Bash

python main.py

Bash

python app.py

The first command (main.py) prepares the model for prediction, while the second command (app.py) launches the Flask web application.

1. Access the Web Interface: Open your web browser and navigate to http://127.0.0.1:5000/ to access the user-friendly interface for CAPTCHA text recognition.

Utilizing the Web Interface:

The web interface is straightforward:

1. Visit the provided web address in your browser.

2. Locate the file upload section and select the CAPTCHA image you want to decipher.

3. Click the upload button and witness the magic! The predicted text from the CAPTCHA image will be displayed on the screen.

This CAPTCHA recognition project equips you with a valuable tool to navigate the web with more ease.  Remember, responsible use is key!

Happy Coding and Happy Decoding!