louisc-s/Conditional-Diffusion-Model
Code for implemeting a conditional DDPM trained on CIFAR10
This tool helps researchers and AI artists generate diverse synthetic images based on specific categories. By inputting desired labels, it produces new, distinct images that combine those attributes. It's ideal for those exploring data augmentation or creative image synthesis.
No commits in the last 6 months.
Use this if you need to create novel images that blend features from different categories, like generating an image that's a mix of 'cat' and 'automobile'.
Not ideal if you're looking to generate photorealistic images or if your needs extend beyond the specific image types it's trained on.
Stars
13
Forks
1
Language
Python
License
—
Category
Last pushed
Jan 15, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/louisc-s/Conditional-Diffusion-Model"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
bghira/SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion models.
mcmonkeyprojects/SwarmUI
SwarmUI (formerly StableSwarmUI), A Modular Stable Diffusion Web-User-Interface, with an...
nateraw/stable-diffusion-videos
Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
TheDesignFounder/DreamLayer
Benchmark diffusion models faster. Automate evals, seeds, and metrics for reproducible results.