Type: huggingface.image_to_image.Inpaint
Namespace: huggingface.image_to_image
Description
Performs inpainting on images using AutoPipeline for Inpainting. This node automatically detects the appropriate pipeline class based on the model used. image, inpainting, autopipeline, stable-diffusion, SDXL, kandinsky
Use cases:
- Remove unwanted objects from images with any compatible model
- Fill in missing parts of images using various diffusion models
- Modify specific areas of images while preserving the rest
- Automatic pipeline selection for different model architectures
Properties
| Property | Type | Description | Default |
|---|---|---|---|
| model | hf.image_to_image |
The HuggingFace model to use for inpainting. | {'type': 'hf.image_to_image', 'repo_id': '', 'path': None, 'variant': None, 'allow_patterns': None, 'ignore_patterns': None} |
| prompt | str |
Text prompt describing what should be generated in the masked area. | `` |
| negative_prompt | str |
Text prompt describing what should not appear in the generated content. | `` |
| image | image |
The input image to inpaint | {'type': 'image', 'uri': '', 'asset_id': None, 'data': None} |
| mask_image | image |
The mask image indicating areas to be inpainted (white areas will be inpainted) | {'type': 'image', 'uri': '', 'asset_id': None, 'data': None} |
| num_inference_steps | int |
Number of denoising steps. | 25 |
| guidance_scale | float |
Guidance scale for generation. Higher values follow the prompt more closely. | 7.5 |
| seed | int |
Seed for the random number generator. Use -1 for a random seed. | -1 |
Outputs
| Output | Type | Description |
|---|---|---|
| output | image |
Metadata
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