MahanVeisi8/Latent-Diffusion-MNIST-DDPM-using-Autoencoder

Unlock the potential of latent diffusion models with MNIST! 🚀 Dive into reconstructing and generating digits using cutting-edge techniques like Autoencoders with Channel Attention Blocks and DDPMs. Perfect for enthusiasts of computer vision, deep learning, and generative modeling! 🌌✨

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This project helps computer vision and deep learning enthusiasts reconstruct and generate handwritten digits. By taking an image of a handwritten digit, it processes it through an autoencoder and a denoising diffusion model to produce a clear, reconstructed digit or a newly generated one. It's designed for those interested in understanding how advanced AI models like diffusion models work with image data.

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Use this if you are a computer vision or deep learning practitioner looking to experiment with and visualize the inner workings of latent diffusion models for image generation and reconstruction.

Not ideal if you are looking for a pre-trained model for real-world document processing or a tool to generate complex, high-resolution images beyond simple digits.

handwriting-recognition image-generation image-reconstruction generative-ai computer-vision
No License Stale 6m No Package No Dependents
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Last pushed

Jan 06, 2025

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