jolibrain/joliGEN
Generative AI Image and Video Toolset with GANs and Diffusion for Real-World Applications
This tool helps you modify images and videos by changing their style, inserting or removing objects, or generating new images for specific purposes. You provide existing image or video data, and it outputs new visual content, transforming it while preserving important details like object labels. This is ideal for professionals in augmented reality, content creation, or anyone needing realistic synthetic data.
280 stars.
Use this if you need to create realistic synthetic images and videos for tasks like augmented reality, virtual try-ons, dataset expansion, or converting simulated visuals to look real.
Not ideal if you're looking for a simple, out-of-the-box photo editor for personal use without the need for custom model training.
Stars
280
Forks
41
Language
Python
License
—
Category
Last pushed
Mar 17, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/jolibrain/joliGEN"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related models
zhangmozhe/Deep-Exemplar-based-Video-Colorization
The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
naver-ai/StyleKeeper
Official Pytorch implementation of "StyleKeeper: Prevent Content Leakage using Negative Visual...
un1tz3r0/finetunepixelartdiffusion
Fine tune a pixelart diffusion model with isometric dataset.
lixiaowen-xw/DiffuEraser
DiffuEraser is a diffusion model for video inpainting, which performs great content completeness...
ironjr/semantic-draw
Official code for the CVPR 2025 paper "SemanticDraw: Towards Real-Time Interactive Content...