Nobim Image Generator

What This Skill Does

The Nobim Image Generator is a powerful, Python-based utility designed to bridge the gap between complex BIM data and actionable visual intelligence. It bypasses the need for resource-heavy, expensive BIM software by leveraging libraries like ifcopenshell, matplotlib, and plotly to transform raw model data into insightful 3D scatter plots and structural visualizations. By processing data derived from Revit or IFC files, it enables users to analyze spatial distributions, element categories, and geometric bounding box data programmatically.

Installation

To integrate this tool into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/datadrivenconstruction/nobim-image-generator

Additionally, ensure your Python environment is prepared with the necessary dependencies:

pip install pandas matplotlib seaborn plotly ifcopenshell

Use Cases

• Project Portfolio Audits: Automatically generate standardized summary visualizations for hundreds of BIM projects simultaneously to identify consistency issues across a portfolio.
• Automated Data Validation: Visualize Bounding Box data to quickly identify misplaced elements or model coordination errors without opening heavy 3D authoring software.
• Pipeline Integration: Use the tool as a step in a CI/CD pipeline for architectural data, ensuring that every model check-in results in a visual report sent to the project management team.
• Cost Estimation Support: Map element categories to spatial representations to verify that specific building components (like walls or HVAC components) are accounted for in the model structure.

Example Prompts

1. "Load the project data from project_a.xlsx and generate a 3D scatter plot colored by element category, then save it to the output folder."
2. "Analyze the bounding box coordinates in the latest model export and identify any elements floating outside the main building site coordinates using the Nobim Visualizer."
3. "Batch process all Excel files in the ./bim_data directory and generate a summary visualization for each project, saving them as high-resolution PNGs."

Tips & Limitations

• Data Requirements: The tool relies on pre-processed Excel data containing specific column headers like 'BBox_CenterX', 'BBox_CenterY', and 'BBox_CenterZ'. Ensure your data extraction pipeline from Revit/IFC includes these attributes.
• Scaling: While optimized for batch processing, rendering thousands of elements in a single 3D plot can hit memory limits; consider filtering element categories if plotting massive models.
• Visual Fidelity: This is a data-driven visualization tool. It does not replace high-end rendering engines like V-Ray or Enscape; it is intended for geometric analysis and rapid reporting.