Overview
This node, named "Wiro - Interior Design Generator," is designed to transform interior space images by applying a redesign based on user-provided descriptive prompts. It takes an input image URL and uses AI-powered generation to produce new interior design images that match the desired style, theme, or color palette described in the prompt.
Common scenarios where this node is beneficial include:
- Interior designers wanting to visualize different styles or themes applied to existing room photos.
- Real estate professionals showcasing potential redesigns of properties.
- Creative professionals generating concept visuals for client presentations.
For example, a user can provide a photo of a hotel bedroom and specify a prompt like "modern minimalist with natural wood accents" to generate redesigned images reflecting that style.
Properties
| Name | Meaning |
|---|---|
| Enter Your Image URL | URL of the image to be used as the base for interior redesign. |
| Prompt | Description of the desired interior style, theme, colors, etc. |
| Negative Prompt | Describes elements or styles to avoid in the output (e.g., blurry, cartoon, disfigured). |
| Samples | Number of images to generate from the input (default is 2). |
| Steps | Number of steps for the image generation process (default is 25). |
| Strength | Degree of transformation strength applied to the original image (default is 0.8). |
| ControlNet Seg Scale | Scale factor for segmentation guidance during generation (default is 0.2). |
| ControlNet Mlsd Scale | Scale factor for MLSD (line guidance) during generation (default is 0.1). |
| Scale | Classifier-free guidance scale influencing creativity vs. adherence to prompt (default 15). |
| Seed | Seed value for random number generator to allow reproducible outputs (default 1577619). |
Output
The node outputs a JSON object containing:
taskid: The unique identifier for the generation task.url: The URL of the generated interior design image once the task completes successfully.status: Status of the generation task, which can be"completed"or"failed".
The output does not include binary data directly but provides URLs to access the generated images.
Dependencies
- Requires an API key credential for authentication with the external Wiro API service.
- Makes HTTP POST requests to
https://api.wiro.ai/v1/Run/wiro/interior-design. - Uses a polling mechanism to wait until the image generation task completes, relying on a socket access token provided by the API.
- Requires network connectivity to the Wiro API endpoint.
Troubleshooting
- Missing or invalid API credentials: Ensure that the API key and secret are correctly configured in the node's credentials.
- API response missing task ID or socket token: This indicates an issue with the API request or service availability. Check the input parameters and API status.
- Task status returns failure codes (
-1,-2,-3,-4): These represent various failure states in the generation process. Retrying with adjusted parameters or checking the API service health may help. - Timeouts during polling: Network issues or slow processing on the API side can cause timeouts. Verify network stability and consider increasing timeout settings if available.
Links and References
- Wiro AI Website (for more information about the service)
- n8n Documentation on Creating Custom Nodes
- General info on ControlNet and MLSD techniques for image generation guidance