Stars
A Chrome extension that enables virtual fashion try-on using FASHN AI technology. Simply hover over clothing images on any website to try them on virtually with your uploaded model image.
The ultimate training toolkit for finetuning diffusion models
[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation
ComfyUI node for the FASHN AI Virtual Try-On API.
Nightly release of ControlNet 1.1
Implementation of rectified flow and some of its followup research / improvements in Pytorch
High-resolution models for human tasks.
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
OneTrainer is a one-stop solution for all your stable diffusion training needs.
Official inference repo for FLUX.1 models
Visual AI development framework for training and inference of ML models, scaling pipelines, and automating workflows with Python.⭐ Leave a star to support us!
Official repository for our work on micro-budget training of large-scale diffusion models.
Minimal implementation of scalable rectified flow transformers, based on SD3's approach
FashionCLIP is a CLIP-like model fine-tuned for the fashion domain.
🛡 Allows users to more easily use Octicons and their own icons and logos on shields.io badges
Badges for your personal developer branding, profile, and projects.
[SIGGRAPH Asia 2024, Journal Track] ToonCrafter: Generative Cartoon Interpolation
Discrete wavelet transform (DWT) vis lifting in PyTorch
EDM2 and Autoguidance -- Official PyTorch implementation
SpeeD: A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training
Cog based workers to RunPod serverless workers.
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
Israeli companies which create Open Source projects
PyTorch implementation of "TryOnDiffusion: A Tale of Two UNets", a virtual try-on diffusion-based network by Google
Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch