Youtube Video -https://youtu.be/XP3L7xlHpqw?si=HULy3QbPYh1lZxUu
This repository contains the implementation of class-conditional image generation models for two diverse datasets: alphanumeric characters and animal images across ten distinct classes. These models were developed as part of a 24-hour hackathon, trained on proprietary datasets, and deployed on a Django web server environment. Users can input prompts to generate corresponding images, showcasing the seamless integration of deep learning and web development technologies.
- Python
- Django
- Deep Learning
- Diffusion Models
- Link to download - https://drive.google.com/drive/folders/17nhOv5Egc-csYKkehPY0nhZhs06L4KC0?usp=sharing
- Store this weights inside - diffusion/home/
- Clone the repository to your local machine.
- Ensure you have Python and Django installed.
- Navigate to the project directory.
- Run the Django server using the command:
python manage.py runserver - Access the web server from your browser.
- Input prompts to generate images from the specified datasets.
Pull requests and contributions are welcome. For major changes, please open an issue first to discuss what you would like to change.