Open Source Linux Inpainting Tools

IOPaint is a powerful open-source image editing tool focused on inpainting, outpainting, object removal, and general image manipulation driven by state-of-the-art AI models, delivering these capabilities through both local and hosted workflows. Designed to be fully self-hosted and flexible, IOPaint supports a variety of underlying generators and inpaint models — from LaMa erase networks to Stable Diffusion-based replace/object generation — giving users multiple ways to refine or reconstruct images by removing unwanted elements or expanding artwork beyond its original boundaries. Its feature set includes erasing people, watermarks, or defects, adding or replacing objects, applying text-aware edits, and extending images outward (outpainting) to fill contours or expand compositions.

Lightweight Stable Diffusion v 2.1 web UI: txt2img, img2img, depth2img, in paint and upscale4x. Gradio app for Stable Diffusion 2 by Stability AI. It uses Hugging Face Diffusers implementation. Currently supported pipelines are text-to-image, image-to-image, inpainting, upscaling and depth-to-image.

Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. Outpaint to increase the size of an image by extending it in any direction. Perform style transfer and create novel animations with Stable Diffusion as a post processing step. Dream Textures has been tested with CUDA and Apple Silicon GPUs. Over 4GB of VRAM is recommended.

Video Object Remover – Frame Accurate Edition is a free and open-source desktop application that helps you remove unwanted objects, logos, or watermarks from videos using brush-based masking and AI inpainting. The tool extracts video frames using FFmpeg, lets you mask objects frame-by-frame, and removes them using OpenCV. Built with Python and Tkinter, it features a modern dark-themed GUI, adjustable brush tool, zoom control, and real-time logging. The cleaned video is rebuilt and exported with original quality. Includes a precompiled Windows EXE for normal users (no Python required) and full source code for developers or students. Perfect for YouTubers, video editors, educators, and open-source enthusiasts. 🖥️ Website: https://projectworlds.in 📺 YouTube: https://youtube.com/@projectworlds 📬 Support: https://projectworlds.in/contact-us

GREYCstoration is a GIMP plugin for restoring pictures : Denoising, inpainting and resize.

Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch. The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the text embedding from CLIP. Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as the denoising network) To train DALLE-2 is a 3 step process, with the training of CLIP being the most important. To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP.

Image Inpainting is the art of filling in missing data in an image. The purpose of inpainting is to reconstruct missing regions in a visually plausible manner so that it seems reasonable to the human eye.

Introduction: ZoomFX is a free tool to help in image batch process thanks to an helpful visual interface and powerful filters. Just use drag & drop to apply some filters to a bunch of images. Author: Eloi Du Bois.

A fully featured audio diffusion library, for PyTorch. Includes models for unconditional audio generation, text-conditional audio generation, diffusion autoencoding, upsampling, and vocoding. The provided models are waveform-based, however, the U-Net (built using a-unet), DiffusionModel, diffusion method, and diffusion samplers are both generic to any dimension and highly customizable to work on other formats. Note: no pre-trained models are provided here, this library is meant for research purposes.

Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: documentation on the SourceForge page is outdated and not updated anymore, please visit http://cocolib.net ***

Code to fill missing holes in a depth map using a second-order smoothness prior. Implemented in matlab using graph cuts. Accompanies the paper "Herrera C., D., Kannala, J., Ladicky, L., Heikkila, J., Depth map inpainting under a second-order smoothness prior, SCIA, 2013"