zf-kbot/inpaint-and-guess-prompt 🔢🖼️📝❓ → ❓

▶️ 741.0K runs 📅 Feb 2025 ⚙️ Cog 0.12.0
image-inpainting image-to-text

Performance

4.7sTypical run time
741.0KTotal runs

About

Use a mask to inpaint the image or generate a prompt based on the mask.

Example Output

Prompt:

"white hair"

Output

{"type":"standard","image":"https://replicate.delivery/xezq/o42hNGIUs4YIJBrO6PATqdgIYeGirEEHvHXYkDl0RtzzXMJKA/output.png"}

Performance Metrics

4.65s Prediction Time
4.66s Total Time
All Input Parameters 
{
  "cfg": 5,
  "mask": "https://replicate.delivery/pbxt/MYJY7ENusmrLv2bdygK666ZsxI5xlFTjbIlTx3SEKSlM7oGe/45988b42-c522-4732-a122-cde32497caca-mask.jpg",
  "seed": 0,
  "image": "https://replicate.delivery/pbxt/MYJY7k5z525kc9Ichp76uuU6WX8CwXeQQ3cDiFp9QGLLbK3J/mom_1.jpg",
  "steps": 20,
  "prompt": "white hair",
  "sampler": "euler_ancestral",
  "fine_edge": "disable",
  "grow_size": 1,
  "scheduler": "karras",
  "predict_type": "standard",
  "edge_strength": 0.55,
  "color_strength": 0.55,
  "negative_prompt": "",
  "inpaint_strength": 1
}
Input Parameters
cfg Type: numberDefault: 5Range: 0 - 20
CFG
mask (required) Type: string
Mask Image
seed Type: integerDefault: 0
Random seed
image (required) Type: string
Input Image
steps Type: integerDefault: 20Range: 1 - 50
Steps
prompt Type: stringDefault:
Prompt
sampler Default: euler_ancestral
Sampler
fine_edge Default: disable
Fine Edge
grow_size Type: integerDefault: 1Range: 1 - 4
Grow Size
scheduler Default: karras
Scheduler
predict_type Default: standard
Predict Type
edge_strength Type: numberDefault: 0.55Range: 0 - 5
Edge Strength
color_strength Type: numberDefault: 0.55Range: 0 - 5
Color Strength
negative_prompt Type: stringDefault:
Negative Prompt
inpaint_strength Type: numberDefault: 1Range: 0 - 5
Inpaint Strength
Output Schema

Output

Type: object

Example Execution Logs 
standard mode
Requested to load SD1ClipModel
Loading 1 new model
Apply edge controlnet
Base model type: SD1.5
BrushNet image.shape = torch.Size([1, 1024, 1024, 3]) mask.shape = torch.Size([1, 1024, 1024])
BrushNet CL: image_latents shape = torch.Size([1, 4, 128, 128]) interpolated_mask shape = torch.Size([1, 1, 128, 128])
Requested to load BaseModel
Loading 1 new model
BrushNet inference: do_classifier_free_guidance is True
BrushNet inference, step = 0: image batch = 1, got 2 latents, starting from 0
BrushNet inference: sample torch.Size([2, 4, 128, 128]) , CL torch.Size([2, 5, 128, 128]) dtype torch.float16
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Version Details
Version ID
c3044b0dd1f7abe4f5f095039ab46b85d5e1d55f3837594261a472b2dc311dbb
Version Created
February 19, 2025
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