adirik/t2i-adapter-sdxl-canny 🖼️📝❓🔢 → 🖼️

▶️ 139.9K runs 📅 Sep 2023 ⚙️ Cog 0.8.3 🔗 GitHub 📄 Paper ⚖️ License
image-editing image-to-image

About

Modify images using canny edges

Example Output

Prompt:

"Mystical fairy in real, magic, 4k picture, high quality"

Output

Example outputExample output

Performance Metrics

11.96s Prediction Time
98.75s Total Time
All Input Parameters 
{
  "image": "https://replicate.delivery/pbxt/Jbn8dWczMIyZiWFABt3p78K3mSEwR1d7LK6LQ8KqUyKuBPYd/org_canny.jpg",
  "prompt": "Mystical fairy in real, magic, 4k picture, high quality",
  "scheduler": "K_EULER_ANCESTRAL",
  "num_samples": 1,
  "guidance_scale": 7.5,
  "negative_prompt": "extra digit, fewer digits, cropped, worst quality, low quality, glitch, deformed, mutated, ugly, disfigured",
  "num_inference_steps": 30,
  "adapter_conditioning_scale": 0.8,
  "adapter_conditioning_factor": 1
}
Input Parameters
image (required) Type: string
Input image
prompt Type: stringDefault: Mystical fairy in real, magic, 4k picture, high quality
Input prompt
scheduler Default: K_EULER_ANCESTRAL
Which scheduler to use
num_samples Type: integerDefault: 1Range: 1 - 4
Number of outputs to generate
random_seed Type: integer
Random seed for reproducibility, leave blank to randomize output
guidance_scale Type: numberDefault: 7.5Range: 0 - 10
Guidance scale to match the prompt
negative_prompt Type: stringDefault: anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured
Specify things to not see in the output
num_inference_steps Type: integerDefault: 30Range: 0 - 100
Number of diffusion steps
adapter_conditioning_scale Type: numberDefault: 0.8Range: 0 - 5
Conditioning scale
adapter_conditioning_factor Type: numberDefault: 1Range: 0 - 1
Factor to scale image by
Output Schema

Output

Type: array • Items Type: string • Items Format: uri

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Version Details
Version ID
920125481b35694832310ddf4d80dcf2a44616c69fcc4747ebbf899aed3f28a9
Version Created
October 30, 2023
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