black-forest-labs/flux-canny-pro 🔢📝🖼️❓✓ → 🖼️
About
Professional edge-guided image generation. Control structure and composition using Canny edge detection

Example Output
Prompt:
"a photo of a car on a city street"
Output

Performance Metrics
16.04s
Prediction Time
16.04s
Total Time
1
Images
All Input Parameters
{ "steps": 28, "prompt": "a photo of a car on a city street", "guidance": 25, "control_image": "https://replicate.delivery/pbxt/M0j11UQhwUWoxUQ9hJCOaALsAHTeoPZcGGtUf6n3BJxtKHul/output-14.webp", "output_format": "jpg", "safety_tolerance": 2, "prompt_upsampling": false }
Input Parameters
- seed
- Random seed. Set for reproducible generation
- steps
- Number of diffusion steps. Higher values yield finer details but increase processing time.
- prompt (required)
- Text prompt for image generation
- guidance
- Controls the balance between adherence to the text as well as image prompt and image quality/diversity. Higher values make the output more closely match the prompt but may reduce overall image quality. Lower values allow for more creative freedom but might produce results less relevant to the prompt.
- control_image (required)
- Image to use as control input. Must be jpeg, png, gif, or webp.
- output_format
- Format of the output images.
- safety_tolerance
- Safety tolerance, 1 is most strict and 6 is most permissive
- prompt_upsampling
- Automatically modify the prompt for more creative generation
Output Schema
Output
Example Execution Logs
Using seed: 53733 Running prediction... Generating image... Generated image in 14.5sec Downloaded image in 1.40sec
Version Details
- Version ID
d042532044840da9fdd8761d2a9e829ebec76662818d0929a035cc3cf14e2661
- Version Created
- September 12, 2025