Whiteboard of Thought is a Python-based project based on the good work done here:https://whiteboard.cs.columbia.edu/. This project is designed to leverage advanced image processing and machine learning techniques to identify and analyze visual data. I'm not associated with Columbia University and have probably not done the project justice. But I found the experience fun and elightening. This project is particularly focused on identifying specific characters or symbols from images, which can be useful in various applications such as digital document analysis and educational tools.
- Image Processing: Utilize Python libraries to process and analyze image data.
- Character Recognition: Special focus on identifying the letter 'q' from images using machine learning models.
- Extensible Framework: Easily extendable to include more characters or symbols.
Ensure you have Python installed on your machine. This project uses Python 3.8 or above. You will also need pip to install the dependencies.
Clone the repository to your local machine: git clone https://github.com/yourusername/whiteboard-of-thought.git cd whiteboard-of-thought
Set up a virtual environment and activate it:
bash python -m venv venv source venv/bin/activate # On Windows use venv\Scripts\activate
Install the required dependencies: bash pip install -r requirements.txt
Run the main script to start the application: bash python main.py
Contributions are welcome! If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
- Thanks to the Python community for maintaining such robust libraries that make projects like this possible. And to the team at: https://whiteboard.cs.columbia.edu/