Flux.1 Canny AI Image Generator

Image generation that preserves structure and composition

Flux Canny

Upload images and describe variant images

Upload an image or provide a URL to the image.

Image file is required

Describe the prompt for the image transformation

Random Seed, useful for generating the same style image

Flux Canny Result

Your generated variant images will appear here

Result Time30s - 1min

Variant images will appear here

Flux Canny Example

Example image 1

Original Image 1

Example image 1

Flux Canny Result 1

Example image 2

Original Image 2

Example image 2

Flux Canny Result 2

Flux Canny FAQ

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What is FLUX Canny?

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.

How does FLUX Canny work?

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.

What are the key features of FLUX Canny?

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.

What makes FLUX Canny unique?

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.

How can I access FLUX Canny?

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.

What are the typical use cases for FLUX Canny?

Typical use cases include retexturing images, performing precise image edits guided by text prompts, and maintaining structural integrity during image transformations.