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Use in agentStability AI models

Stability AI modelsimage generation api

stability-ai/fast-sdxl-controlnet-canny/image-to-image

Fast Sdxl Controlnet Canny is Stability AI's intelligent image editing model. Transform, retouch, and reimagine existing images using text prompts - from background replacement to artistic style conversion.

Input
The prompt to use for generating the image. Be as descriptive as possible for best results.

PNG, JPEG, WebP, or GIF · 20 MiB maximum

The URL of the image to use as a starting point for the generation.
0.051
determines how much the generated image resembles the initial image Range: 0.05 to 1.

PNG, JPEG, WebP, or GIF · 20 MiB maximum

The URL of the control image.
The aspect ratio of the generated image. Allowed values: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.
The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
Enter a JSON array.
020
Range: 0 to 20.
170
Range: 1 to 70.
Idle

Example output — click Run to generate your own

API README

ControlNet SDXL

ControlNet SDXL occupies a clearly bounded position in a image production pipeline under the route stability-ai/fast-sdxl-controlnet-canny/image-to-image. It is best evaluated as a named workflow endpoint rather than as a generic substitute for neighboring versions: planners can assign the route to a specific brief, record the chosen revision, and keep approval history tied to one predictable integration surface from intake through delivery.

A practical rollout of ControlNet SDXL should begin with source-readiness checks, ownership of the submitted material, an agreed budget, and a written definition of the final image to image deliverable. Before automation is enabled, the acceptance pass should verify that the returned asset opens correctly, fits the intended downstream toolchain, satisfies the project’s review criteria, and can be reproduced from the stored request and route identity stability-ai/fast-sdxl-controlnet-canny/image-to-image.

Highlights

  • Distinct output behavior. For ControlNet SDXL, for ControlNet SDXL, keep the starting image and the Canny control image in their distinct request fields In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with seed as a relevant request control; the seed control exposes the corresponding choice in this route; the seed control exposes the corresponding choice in this route.
  • Creative control. For ControlNet SDXL, for ControlNet SDXL, adjust how strongly the result resembles the initial image through the bounded strength value In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with image as a relevant request control; the image control exposes the corresponding choice in this route; the image control exposes the corresponding choice in this route.
  • Workflow fit. For ControlNet SDXL, for ControlNet SDXL, frame the result with one of the ten declared aspect ratios In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with loras as a relevant request control; the loras control exposes the corresponding choice in this route; the loras control exposes the corresponding choice in this route.
  • Production detail. For ControlNet SDXL, for ControlNet SDXL, tune inference steps from 1 through 70 In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with prompt as a relevant request control; the prompt control exposes the corresponding choice in this route; the prompt control exposes the corresponding choice in this route.

Pricing

ConfigurationPrice
Per request$0.00125

When to Use

ScenarioWhy this model fits
Choose ControlNet SDXLUse it when the required deliverable is specifically the image-to-image result documented for stability-ai/fast-sdxl-controlnet-canny/image-to-image.
Match the source materialSelect this route when your inputs naturally map to seed, image, loras, prompt.
Use its distinguishing capabilityFor ControlNet SDXL, keep the starting image and the Canny control image in their distinct request fields In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with seed as a relevant request control; the seed control exposes the corresponding choice in this route
Plan repeatable productionFor ControlNet SDXL, adjust how strongly the result resembles the initial image through the bounded strength value In ControlNet SDXL, this capability is applied through the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image workflow with image as a relevant request control; the image control exposes the corresponding choice in this route
Confirm cost and deliveryUse the pricing combinations below and the output contract above when budgeting or automating ControlNet SDXL jobs.

Prompt Guide

Build the request around the exact stability-ai/fast-sdxl-controlnet-canny/image-to-image schema. Start with required fields, then add only the controls needed for the intended output; keep URLs reachable and enum values exactly as shown in Technical Specs.

{
  "image": "https://fal-cdn.batuhan-941.workers.dev/files/tiger/IExuP-WICqaIesLZAZPur.jpeg",
  "prompt": "Ice fortress, aurora skies, polar wildlife, twilight",
  "seed": 0,
  "loras": []
}

Technical Specs

SpecificationValue
Model IDstability-ai/fast-sdxl-controlnet-canny/image-to-image
Execution modeasync
Required inputsprompt, image
Request fieldsseed (integer, optional); image (string, required); loras (array, optional); prompt (string, required); strength (number, optional, min 0.05, max 1); aspect_ratio (string, optional, options: 21:9 / 16:9 / 3:2 / 4:3 / 5:4 / 1:1 / 4:5 / 3:4 / 2:3 / 9:16); guidance_scale (number, optional, min 0, max 20); control_image_url (string, optional); num_inference_steps (integer, optional, min 1, max 70)
Outputurl (string); content_type (string)

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