FLUX-Controlnet-Inpainting

An image restoration tool based on the FLUX.1-dev model.

CommonProductImageImage RestorationDeep Learning

FLUX-Controlnet-Inpainting is an image restoration tool released by the Alibaba Mama Creative Team, based on the FLUX.1-dev model. This tool utilizes deep learning technology to restore images, filling in missing sections and suitable for image editing and enhancement. It performs best at a resolution of 768x768, providing high-quality image restoration results. Currently, the tool is in the alpha testing phase, with future updates planned.

Supports high-resolution image restoration; using a resolution of 768x768 is recommended.
Provides control net condition adjustment functionality
with a recommended control net condition ratio of 0.9-0.95.
Uses the Hugging Face platform to upload model weights
making it easy for users to download and use.
Compatible with the Diffusers library to streamline the image restoration process.
Offers detailed usage instructions and examples to help users get started quickly.
Currently in the alpha testing phase
with plans for more comprehensive features and performance improvements in the future.

\FLUX-Controlnet-Inpainting is ideal for image processing professionals
designers
and enthusiasts interested in image restoration. It helps users repair damaged or incomplete images
enhances image quality
and facilitates creative work.\

Restore old photos by filling in missing parts to recover historical images.
Quickly repair small flaws in images during design work to improve efficiency.
Create unique art pieces in digital art projects using image restoration techniques.

1. Install the Diffusers library.
2. Clone the FLUX-Controlnet-Inpainting repository from GitHub.
3. Modify the image path
mask path
and prompts

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5.7

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00:06:44

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