dhanushreddy291/photo-background-generation 🔢🖼️📝 → 🖼️

▶️ 587 runs 📅 Jun 2024 ⚙️ Cog 0.9.9 🔗 GitHub ⚖️ License
image-editing image-to-image product-photography

About

Generate Product photography backgrounds using Stable Diffusion

Example Output

Prompt:

"A Shoe on a marble podium, product photography, high resolution"

Output

Example output

Performance Metrics

10.73s Prediction Time
130.47s Total Time
All Input Parameters
{
  "image": "https://unsplash.com/photos/AYIeSFWhEB8/download?force=true&w=640",
  "prompt": "A Shoe on a marble podium, product photography, high resolution",
  "num_outputs": 1,
  "negative_prompt": "3d, cgi, render, bad quality, normal quality",
  "num_inference_steps": 30,
  "controlnet_conditioning_scale": 1
}
Input Parameters
seed Type: integer
Random seed. Leave blank to randomize the seed
image Type: string
Input image for Generating the Background
prompt Type: stringDefault: A Shoe on a marble podium, product photography, high resolution
Input prompt
num_outputs Type: integerDefault: 1Range: 1 - 4
Number of images to output.
negative_prompt Type: stringDefault: 3d, cgi, render, bad quality, normal quality
Input Negative Prompt
num_inference_steps Type: integerDefault: 30Range: 20 - 50
Number of inference steps
controlnet_conditioning_scale Type: numberDefault: 1Range: 1 - 3
Controlnet Conditioning Scale
Output Schema

Output

Type: arrayItems Type: stringItems Format: uri

Example Execution Logs
Using seed: 11152876
/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:3190.)
return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Settings -> Mode=base, Device=cuda:0, Torchscript=disabled
Settings -> Mode=base, Device=cuda:0, Torchscript=disabled
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Version Details
Version ID
965ac3a06130be7d477be7c73164fe972505fd759e7717ed28850f9865c23651
Version Created
June 15, 2024
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