Inpainting

Action ID: inpainting

Description

AI-powered image inpainting that intelligently fills or replaces masked areas in images based on text prompts.

Connection

Name	Description	Required	Category
PixelML Connection	The PixelML connection to call PixelML API.	True	pixelml

Input Parameters

Name	Type	Required	Default	Description
prompt	string	✓	-	Text description of what to generate in the masked area
image_url	string	✓	-	URL of the base image. Supported formats: PNG, JPEG, JPG, WEBP
mask_url	string	✓	-	URL of the mask image defining the area to inpaint. Supported formats: PNG, JPEG, JPG, WEBP

View JSON Schema

Input Schema

{
  "description": "Inpainting node input.",
  "properties": {
    "prompt": {
      "title": "Prompt",
      "type": "string"
    },
    "image_url": {
      "title": "Image url",
      "type": "string"
    },
    "mask_url": {
      "title": "Mask url",
      "type": "string"
    }
  },
  "required": [
    "prompt",
    "image_url",
    "mask_url"
  ],
  "title": "InpaintingNodeInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
image	string	URL of the inpainted image with masked area filled

View JSON Schema

Output Schema

{
  "description": "Inpainting node output.",
  "properties": {
    "image": {
      "title": "Image output",
      "type": "string"
    }
  },
  "required": [
    "image"
  ],
  "title": "InpaintingNodeOutput",
  "type": "object"
}

How It Works

This node uses advanced AI diffusion models to intelligently fill or replace masked areas in images. You provide a base image, a mask image that defines which areas to modify, and a text prompt describing what you want to generate. The AI analyzes the surrounding context in the base image and generates new content in the masked area that seamlessly blends with the existing image while following your prompt instructions.

Usage Examples

Example 1: Remove Unwanted Objects

Input:

prompt: "green grass and flowers"
image_url: "https://example.com/park-photo.jpg"
mask_url: "https://example.com/person-mask.png"

Output:

image: "https://storage.pixelml.com/inpainted-park.jpg"

Example 2: Add New Elements

Input:

prompt: "a red sports car parked in the driveway"
image_url: "https://example.com/house.jpg"
mask_url: "https://example.com/driveway-mask.png"

Output:

image: "https://storage.pixelml.com/house-with-car.jpg"

Example 3: Change Background Elements

Input:

prompt: "blue sky with white clouds"
image_url: "https://example.com/portrait.jpg"
mask_url: "https://example.com/sky-mask.png"

Output:

image: "https://storage.pixelml.com/portrait-new-sky.jpg"

Common Use Cases

• Object Removal: Remove unwanted objects, people, or blemishes from photos

• Background Replacement: Change backgrounds in product photos or portraits

• Content Addition: Add new elements like furniture, decorations, or objects to scenes

• Image Restoration: Fill in damaged or missing parts of images

• Creative Editing: Modify specific areas of images for artistic or design purposes

• Product Photography: Enhance product images by changing backgrounds or adding context

• Real Estate: Improve property photos by adding or removing elements

Error Handling

Error Type	Cause	Solution
Invalid Image Format	Image format is not supported	Ensure images are in PNG, JPEG, JPG, or WEBP format
Mask Mismatch	Mask dimensions don't match image dimensions	Ensure mask image has the same dimensions as the base image
Invalid Mask	Mask image is not properly formatted	Use a binary mask with white areas indicating regions to inpaint
Prompt Too Vague	Prompt doesn't provide enough detail	Provide more specific and descriptive prompts for better results
Image Too Large	Image resolution exceeds maximum limit	Resize images to a smaller resolution before inpainting
Connection Failed	Unable to access PixelML API	Check PixelML connection credentials and API availability
Processing Timeout	Operation took too long to complete	Try with a smaller image or simpler prompt

Notes

• Mask Creation: The mask image should have white areas indicating where to inpaint and black areas to preserve. The mask must have the same dimensions as the base image.

• Prompt Quality: More detailed and specific prompts generally produce better results. Describe colors, textures, lighting, and style.

• Image Resolution: Higher resolution images may take longer to process. Consider using moderate resolutions for faster results.

• Context Awareness: The AI considers the surrounding image context when generating inpainted content for natural blending.

• Multiple Iterations: You may need to try different prompts or masks to achieve desired results.

• Processing Time: Inpainting typically takes 10-30 seconds depending on image size and complexity.