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An innovative application that transforms your simple sketches into stunning art pieces using advanced machine learning algorithms

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Sketch2Art

Sketch2Art is an innovative application that transforms your simple sketches into stunning art pieces using advanced machine learning algorithms. It's designed for artists, designers, and anyone who loves to create.

Getting Started

These instructions will guide you through setting up Sketch2Art on your local machine for development and testing purposes.

Prerequisites

Before you begin, make sure you have the following installed:

  • Python 3.8 or higher
  • pip (Python package installer)

Installation

  1. Clone the Repository

    Get a copy of the source code on your local machine:

    git clone https://github.com/SwapnilK0/Sketch2Art.git
    cd Sketch2Art
  2. Set Up a Virtual Environment

    Isolate your project by creating a virtual environment:

    For Windows:

    python -m venv venv
    .\venv\Scripts\activate

    For macOS and Linux:

    python3 -m venv venv
    source venv/bin/activate
  3. Install Dependencies

    Install all the required packages using pip:

    pip install -r requirements.txt
  4. Environment Variables

    Create a .env file in the project's root directory. Use the env.example file as a template to add the necessary environment variables.

  5. Launch the Application

    Start the app with Streamlit:

    streamlit run ui.py

    Access the app through your web browser at http://localhost:8501.

Usage

After installation, you can start turning your sketches into art! Simply upload a sketch and let Sketch2Art work its magic.

Contributing

We welcome contributions to Sketch2Art! If you have suggestions or improvements, please follow these steps:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature-branch).
  3. Make your changes.
  4. Commit your updates (git commit -m 'Add some feature').
  5. Push to the branch (git push origin feature-branch).
  6. Open a pull request.

License

Sketch2Art is released under the MIT License. Feel free to use, modify, and distribute it as per the license terms.

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