DiffusionModel
The application uses a Deep Learning model to generate new car images from scratch. It employs a diffusion process to progressively refine random noise into realistic car images. Based on state-of-the-art techniques from recent research, the model ensures high-quality and diverse image generation.
Install / Use
/learn @CogitoNTNU/DiffusionModelREADME
Diffusion Model
<div id="top"></div> <!--INSERT PICTURE REPRESENTATIVE OF PROJECT--> <div align="center"> <img src="docs/images/DiffusionModelGIF.gif" width="30%"></img> </div> <p align="center"> <a href="https://github.com/CogitoNTNU/README-template/blob/main/LICENSE" alt="LICENSE"> <img src="https://img.shields.io/badge/license-MIT-green"></img></a> <a href="" alt="platform"> <img src="https://img.shields.io/badge/platform-linux%7Cwindows%7CmacOS-lightgrey"></img></a> <a href="" alt="version"> <img src="https://img.shields.io/badge/version-1.0.0-blue"></img></a> </p> <details> <summary><b>📋 Table of contents </b></summary> </details>Description
The aim of this project is to create our own Deep Learning model that generates brand new car images. We develop our home-made unconditional image generation model based on the paper Denoising Diffusion Probabilistic Models from Jonathan Ho, Ajay Jain, Pieter Abbeel in 2020. We followed the structure of the article and implemented main function to recreate an unconditional image generator, based on the diffusion process.
Quick Start
Prerequisites
- Ensure that git is installed on your machine. Download Git
- Docker is used for the backend and database setup. Download Docker
Clone the repository
git clone https://github.com/CogitoNTNU/DiffusionModel.git
cd DiffusionModel
Usage
docker compose up --build
Then navigate to http://localhost:8501 in your browser to access the UI of the frontend.
Done! You are now ready to generate cars!
Team
The team behind this project is a group of students at NTNU in Trondheim, Norway, developed during the spring semester of 2024.
<table align="center"> <tr> <td align="center"> <a href="https://github.com/soricm"> <img src="https://github.com/soricm.png?size=100" width="100px;"/><br /> <sub><b>Marijan Soric</b></sub> </a> </td> <td align="center"> <a href="https://github.com/ThomasHWik"> <img src="https://github.com/ThomasHWik.png?size=100" width="100px;"/><br /> <sub><b>Thomas Haslund Wik</b></sub> </a> </td> <td align="center"> <a href="https://github.com/Mauritzskog"> <img src="https://github.com/Mauritzskog.png?size=100" width="100px;"/><br /> <sub><b>Mauritz Skogøy</b></sub> </a> </td> <td align="center"> <a href="https://github.com/amandathunes"> <img src="https://github.com/amandathunes.png?size=100" width="100px;"/><br /> <sub><b>Amanda Truyen</b></sub> </a> </td> <td align="center"> <a href="https://github.com/BarisBatur"> <img src="https://github.com/BarisBatur.png?size=100" width="100px;"/><br /> <sub><b>Baris Batur</b></sub> </a> </td> </tr> </table>This project would not have been possible without the hard work and dedication of all of the contributors. Thank you for the time and effort you have put into making DiffusionModel a reality.
<div align="center"> <img src="docs/images/cogito-team.jpg" width="70%" alt="Cogito Team Image" style="display: block; margin-left: auto; margin-right: auto;"> </div>Left to right: @BarisBatur, @soricm (Team leader), @amandathunes, @Mauritzskog. (@ThomasHWik isn't in the picture)
License
Distributed under the MIT License. See LICENSE for more information.
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