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Super Optimized Gradio UI for AI video creation for GPU poor machines (6GB+ VRAM). Supports Wan 2.1/2.2, Qwen, Hunyuan Video, LTX Video and Flux. https://github.com/deepbeepmeep/Wan2GP

The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. https://github.com/comfyanonymous/ComfyUI

The Gen AI Platform for Pro Studios https://github.com/invoke-ai/InvokeAI

An intelligent, interactive Image Editing System. Easily erase and add objects on a user-friendly interface.

An enhanced local port of finegrain-image-enhancer powered by Refiners (https://huggingface.co/spaces/finegrain/finegrain-image-enhancer), which was adapted from philz1337x's Clarity Upscaler (https://github.com/philz1337x/clarity-upscaler)

restore low-res images, restore broken images, recreate a new version of the image with a prompt https://huggingface.co/spaces/fffiloni/InstantIR

Enhanced background remove and replace app built around BRIA-RMBG-2.0 https://huggingface.co/briaai/RMBG-2.0

Artist is a training-free text-driven image stylization method. You give an image and input a prompt describing the desired style, Artist give you the stylized image in that style. The detail of the original image and the style you provide is harmonically integrated https://huggingface.co/spaces/fffiloni/Artist

A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion https://huggingface.co/spaces/TencentARC/BrushNet

Remove objects from an image https://huggingface.co/spaces/OzzyGT/diffusers-image-fill

Background removal model developed by BRIA.AI, trained on a carefully selected dataset and is available as an open-source model for non-commercial use https://huggingface.co/spaces/briaai/BRIA-RMBG-1.4

Differential Diffusion modifies an image according to a text prompt, and according to a map that specifies the amount of change in each region https://differential-diffusion.github.io/

ZeST: Zero-Shot Material Transfer from a Single Image. Local port of https://huggingface.co/spaces/fffiloni/ZeST (Project: https://ttchengab.github.io/zest/)