kevinMEH/simple-stylegan
A simple implementation of the StyleGAN.
This project helps machine learning practitioners easily generate synthetic images, particularly human faces, using the StyleGAN architecture. You provide a dataset of images, and it outputs a trained model capable of creating new, never-before-seen images that resemble your input data. This is ideal for researchers, artists, or anyone needing to generate diverse image content for experimentation or creative projects.
No commits in the last 6 months.
Use this if you want a straightforward way to train a StyleGAN model to generate realistic images from your own datasets.
Not ideal if you need a production-ready image generation system that produces extremely high-fidelity, photorealistic results without further parameter tuning and extensive training.
Stars
6
Forks
—
Language
Python
License
—
Category
Last pushed
Oct 10, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/kevinMEH/simple-stylegan"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PrasannaPulakurthi/MMD-AdversarialNAS-GAN
Enhancing GAN Performance Through Neural Architecture Search and Tensor Decomposition
aakashjhawar/AvatarGAN
Generate Cartoon Images using Generative Adversarial Network
samresume/SeriesGAN
We introduce an advanced framework that integrates the advantages of an autoencoder-generated...
davide-abbattista/outGANfit
outGANfit - a cDCGANs-based architecture
veith4f/kubeflow-evaluation
This is an evaluation of various ai techniques geared around kubeflow and tensorflow. Creates...