Downcodes editor reports: Alibaba’s creative team has open sourced a powerful AI image repair model - FLUX-Controlnet-Inpainting. This model is based on the FLUX.1-dev architecture and uses massive data sets for training, with a resolution of up to 768x768, and has high-quality image generation and precise repair capabilities. It can not only repair the missing parts of the image, but also add, remove objects and even change the image style based on the text description provided by the user, showing amazing AI image processing capabilities. The model has been open sourced on the Hugging Face platform, and detailed tutorials and sample codes are provided to facilitate users to quickly get started.
Recently, Alimama’s creative team has open sourced an AI image repair model called FLUX-Controlnet-Inpainting. The model is based on the FLUX.1-dev model architecture and was trained on 12 million laion2B images and Alibaba's internal data sets, with a resolution of up to 768x768, capable of high-quality image repair.
This tool not only inherits the high-quality image generation capabilities of the FLUX.1-dev model, but also cleverly integrates the advantages of ControlNet. It can accurately repair images based on information such as edges, line drawings, and depth maps, and generate content in designated areas that is consistent with the surrounding environment, bringing new life to damaged or missing image parts.
One of the highlights of this model is that it can understand the user's verbal description and accurately repair the image based on the description, such as adding or removing objects from the image based on the text description provided by the user, and even changing the style of the image.
The FLUX-Controlnet-Inpainting model is now open source on the Hugging Face platform, and provides detailed usage tutorials and sample codes. Users can install the diffusers library through pip and clone the project code from GitHub to quickly experience the powerful functions of the model.
Alimama’s creative team stated that the currently released FLUX-Controlnet-Inpainting model is still in the alpha testing stage, and will continue to optimize model performance in the future and plans to release an updated version in the future.
Project address: https://github.com/alimama-creative/FLUX-Controlnet-Inpainting
Workflow download address: https://huggingface.co/alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha/resolve/main/images/alimama-flux-controlnet-inpaint.json
All in all, the open source of the FLUX-Controlnet-Inpainting model has brought new breakthroughs to the field of AI image restoration. We look forward to more surprises in future versions! The editor of Downcodes will continue to pay attention to its subsequent development.