Image generation that preserves structure and composition
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Flux Canny Result 1
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Flux Canny Result 2
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FLUX Canny is a model designed to provide structural guidance for image transformations using canny edges extracted from input images and text prompts. It enables precise control over the modification and recreation of images.
FLUX Canny utilizes canny edge detection to maintain the structural integrity of an image during transformations. By using edge maps and text prompts, it allows for text-guided edits while preserving the core composition of the original image.
Key features include structural conditioning through canny edges, integration with FLUX.1 Pro Ultra for high-quality outputs, and the ability to perform text-guided image transformations while maintaining structural fidelity.
FLUX Canny stands out for its ability to provide state-of-the-art structural guidance in image transformations, ensuring high fidelity to the original image structure. It supports complex workflows and precise image restyling.
FLUX Canny is available in two versions: FLUX Canny [dev], which is open source under the Flux Dev License, and FLUX Canny [pro], accessible through the BFL API with support for FLUX.1 Pro Ultra.
Typical use cases include retexturing images, performing precise image edits guided by text prompts, and maintaining structural integrity during image transformations.