OpenMMLab Computer Vision Foundation

OpenMMLab Foundational Library for Training Deep Learning Models

[CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation

Open Source Computer Vision Library

The minimal opencv for Android, iOS, ARM Linux, Windows, Linux, MacOS, HarmonyOS, WebAssembly, watchOS, tvOS, visionOS

OpenMMLab Model Deployment Framework

Next generation face swapper and enhancer

[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

[ICCV 2023] PyTorch Implementation of "MotionBERT: A Unified Perspective on Learning Human Motion Representations"

Official repo of our paper "SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions"

Create Magic Story!

Google Research

One-click Face Swapper and Restoration powered by insightface 🔥

InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation 🔥

利用HuggingFace的官方下载工具从镜像网站进行高速下载。

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

Building a quick conversation-based search demo with Lepton AI.

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Python Package to write SVG files (UNMAINTAINED)

Huggingface cloth segmentation using U2NET

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs

To convert sdxl checkpoint to diffusers, need kohya-ss/sd-scripts as a core to make it work.

A 13B large language model developed by Baichuan Intelligent Technology

Just a helper script for invoking kohya converter (and maybe a cheeky inferencer to check it worked okay)