andylolu2/jax-diffusion

Implementation of Denoising Diffusion Probabilistic Models (DDPM) in JAX and Flax.

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Experimental

This project helps machine learning engineers and researchers generate new, realistic images based on existing datasets. You provide a collection of images, and it produces a diverse set of brand-new images that share similar characteristics but are not exact copies. This is useful for expanding datasets or exploring novel image generation techniques.

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Use this if you need to create synthetic images for dataset augmentation, artistic generation, or research into generative models.

Not ideal if you need to perform image classification, object detection, or any task that requires analyzing existing images rather than creating new ones.

generative-modeling image-synthesis deep-learning-research dataset-expansion synthetic-data
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
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Python

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Last pushed

Oct 12, 2023

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