#image editing

IOPaint is a free, open-source tool for seamless inpainting and outpainting using cutting-edge AI models. Compatible with various OS including Windows and macOS, it features object erasure, text overlay, and object replacement. Utilize plugins for super-resolution and image segmentation. Ideal for any user looking to enhance images effortlessly.

Smooth Diffusion optimizes latent space in diffusion models to enhance image interpolation, reduce errors in inversion, and maintain content integrity during editing. This Pytorch implementation includes a Gradio demo and supports training and inference, now utilizing Realistic Vision V2.0 as its default model. Its acceptance at CVPR 2024 underscores its innovative contribution to the field.

An advanced comic translator and editor utilizing AI to facilitate translation and editing of images and text. Supports one-click translations with layout accuracy and multi-language options, including manga enhancements. Offers sophisticated text and image editing capabilities like masking and repair tools. Usability across platforms with file management and diverse OCR features. Leverage its open-source nature and community input for a comprehensive comic handling tool.

Discover a method for fast and accurate local text-driven image editing using Blended Latent Diffusion. This approach enhances image modification within user-defined masks by reducing inference time and minimizing artifacts, outperforming traditional GANs. Suitable for varied applications such as altering backgrounds and objects or generating text.

Discover a novel method that improves the accuracy of real image inversion using iterative noising. This technique optimizes the inversion process by refining predictions with pretrained diffusion models along the diffusion path, without increasing operational complexity. It supports advanced diffusion models and maintains image editability, suitable for applications in text-guided image modification and diffusion model refinement.

The Spatially Incremental Generative Engine (SIGE) optimizes image editing by focusing computation on edited regions, thus decreasing computational workload for models like DDPM, Stable Diffusion, and GauGAN without compromising image quality. Featuring significant performance gains on NVIDIA RTX 3090 and Apple M1 hardware, SIGE leverages GAN Compression among other techniques. It offers broad application support, including Stable Diffusion compatibility and Mac MPS backend optimization, particularly benefiting the M1 MacBook Pro. The project provides accessible resources, enabling comprehensive experimentation and benchmarking on widely used platforms.

SEED-X, a unified foundation model, serves multimodal AI needs with advanced comprehension and generation, from image design to personal assistance. Features include SEED-Story for story creation and SEED-Data-Edit for precise image editing. Experience enhanced models and fast demos.