andreasjansson/illusion 🔢🖼️📝❓ → 🖼️
About
Monster Labs' control_v1p_sd15_qrcode_monster ControlNet on top of SD 1.5

Example Output
Prompt:
"An oil painting of medieval city streets with buildings and trees and people"
Output

Performance Metrics
6.78s
Prediction Time
6.77s
Total Time
All Input Parameters
{ "seed": -1, "image": "https://replicate.delivery/pbxt/Ja3ByHnLrLmMc1uI7z0PZyBdQWdU4eQUoJJvXRMnGQbT9y5o/F6WmkWWacAAcyLe.png", "width": 768, "border": 4, "height": 768, "prompt": "An oil painting of medieval city streets with buildings and trees and people", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw", "qr_code_content": "", "qrcode_background": "white", "num_inference_steps": 40, "controlnet_conditioning_scale": 1 }
Input Parameters
- seed
- Seed
- image
- Input image. If none is provided, a QR code will be generated
- width
- Width out the output image
- border
- QR code border size
- height
- Height out the output image
- prompt (required)
- The prompt to guide QR Code generation.
- num_outputs
- Number of outputs
- guidance_scale
- Scale for classifier-free guidance
- negative_prompt
- The negative prompt to guide image generation.
- qr_code_content (required)
- The website/content your QR Code will point to.
- qrcode_background
- Background color of raw QR code
- num_inference_steps
- Number of diffusion steps
- controlnet_conditioning_scale
- The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added to the residual in the original unet.
Output Schema
Output
Example Execution Logs
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Version Details
- Version ID
75d51a73fce3c00de31ed9ab4358c73e8fc0f627dc8ce975818e653317cb919b
- Version Created
- September 17, 2023