berlin0308/Conditional-DDPM-DDIM
DDPM (Denoising Diffusion Probabilistic Models) and DDIM (Denoising Diffusion Implicit Models) for conditional image generation
This project helps machine learning engineers and researchers generate high-quality images conditionally, meaning you can specify characteristics like a digit (0-9) or generate realistic human faces. You input training data or a pre-trained model and generate new, diverse images based on your conditions. It's designed for those working with image synthesis and generative models.
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Use this if you need to generate images of specific categories or types, such as particular digits or realistic human faces, and want to explore advanced diffusion models for this task.
Not ideal if you are looking for a simple, no-code image generation tool or if your primary goal is not related to exploring or implementing advanced diffusion models.
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Python
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Last pushed
Jan 17, 2025
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