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Different PyTorch implementations of diffusion models to perform image denoising

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Denoising Diffusion Models

Project for Machine Learning for Computer Vision.

In this project we use different PyTorch implementations of diffusion models to perform image denoising. For training we use the Flowers102 dataset.

The concepts behind this project are explained in Ho et al. 2020.

Dependencies

Repository structure

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├── images    # It contains the images in the notebook     
├── models   # It contains the models    
├── test_pictures   # It contains some test pictures                  
├── utils    # It contains the python files with useful functions (e.g. training utilities)
├── denoising_diffusion_models.ipynb    # Notebook file
├── .gitignore
├── LICENSE
└── README.md

Group members

Name Surname Email Username
Enrico Pittini [email protected] EnricoPittini
Michele Calvanese [email protected] michele98

License

This project is licensed under the MIT License - see the LICENSE file for details.

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