Welcome to the pytorch-beta-vae-fashion-mnist project! This software allows you to generate and manipulate images from the Fashion-MNIST dataset using a β-Variational Autoencoder. With this tool, you can explore image generation and learn about how models can understand and represent various clothing items.
To get started, visit the page below to download the latest version of the software.
- Operating System: Windows 10, macOS, or Linux
- RAM: At least 4 GB
- Disk Space: Minimum of 500 MB free space
- Python: Version 3.6 or higher
- Required Packages: PyTorch and other dependencies, which will be installed automatically during setup
- Disentangled representation learning: Understand how to separate features in images.
- Image generation: Create new images based on the trained model.
- Latent space exploration: Interact with image representations in a controlled manner.
- Easy visualization of generated and reconstructed images.
- Click on the download button above or visit the Releases page.
- Download the latest release suitable for your operating system.
- Once downloaded, locate the file on your computer, typically in your Downloads folder.
- Double-click on the installer file to begin the installation process.
- Follow the on-screen instructions to complete the installation.
- After installation, open the application from your Start menu or Applications folder.
Once you have installed the software, you can start using it to explore the Fashion-MNIST dataset.
- Launch the application.
- Choose the dataset you want to work with. The included dataset is preloaded for convenience.
- Select options to generate or explore images.
- The interface will guide you through the different functions available.
- Generate Images: Click the "Generate" button to create new images based on the trained model.
- View Latent Space: Use the "Latent Space" feature to visualize how images are represented in the model.
- Reconstruct Images: Load an existing image and use the model to reconstruct it.
If you run into issues, here are some common troubleshooting steps:
- Ensure you have the correct version of Python installed.
- Make sure your system meets the minimum requirements listed above.
- Check that all required packages are installed correctly.
For additional help, you can refer to the GitHub Issues page or contact support via our Discord channel.
If you want to contribute to the project, we welcome your input! Check the repository for guidelines on how to start contributing.
Want to understand the technology behind this software? Explore more about:
- Variational Autoencoders
- Disentangled Representations
- Generative Models
For an academic deep dive, consider reading related research papers.
This project covers a variety of concepts, including:
- beta-vae
- convolutional-neural-networks
- disentangled-representations
- image-generation
- latent-space-exploration
Feel free to explore these topics to enhance your understanding of the methods used.
And that’s it! Enjoy your journey into the world of AI and image generation with pytorch-beta-vae-fashion-mnist.