Introducing FLUX.1 Tools – Black Forest Labs
Black Forest Labs has recently announced the release of FLUX.1 Tools, a suite of models designed to enhance their base text-to-image model FLUX.1. These tools aim to provide users with more control and steerability when modifying and recreating real and generated images.
Features of FLUX.1 Tools
- FLUX.1 Fill: This feature offers state-of-the-art inpainting and outpainting capabilities, allowing for seamless editing and expansion of images based on a text description and a binary mask.
- FLUX.1 Depth: Models in this category provide structural guidance based on a depth map extracted from an input image and a text prompt.
- FLUX.1 Canny: These models enable structural guidance based on canny edges extracted from an input image and a text prompt.
- FLUX.1 Redux: An adapter that facilitates mixing and recreating input images and text prompts.
These tools are available as open-access models within the FLUX.1 [dev] series and in the BFL API supplementing FLUX.1 [pro]. The company’s commitment to delivering cutting-edge models for the research community is evident in this release.
FLUX.1 Fill, in particular, stands out for its advanced inpainting capabilities, surpassing existing tools and open-source variants. It supports both inpainting and outpainting, allowing users to seamlessly edit and extend images beyond their original borders. Benchmark results show that FLUX.1 Fill [pro] outperforms all competing methods, making it the state-of-the-art inpainting model.
Structural conditioning with FLUX.1 Canny/Depth utilizes canny edge or depth detection to maintain precise control during image transformations. By preserving the original image’s structure, these models offer users enhanced control and guidance.
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