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YOLOv8 Object DetectionComputer VisionSpatial MappingPyMuPDF

AI-Powered Blueprint Symbol Extractor & Room Mapper

Automating electrical takeoffs and spatial inventory with YOLOv8 and geometric boundaries.

92%Reduction in Manual Takeoffs
100%Automation Rate

The Friction

Pre-construction estimators spend countless hours manually scanning multi-page PDF blueprints to count electrical fixtures (such as receptacles, junction boxes, and outlets) and mapping them to their corresponding room IDs. This manual process is extremely slow, prone to oversight, and bottlenecks bid submissions.

The Neural Architecture

We deployed a custom object detection and spatial mapping pipeline. The system utilizes a fine-tuned YOLOv8 model to locate electrical symbols, extracts room layout polygons and IDs directly from PDF text streams using PyMuPDF, and runs a Voronoi geometric partition algorithm to assign each detected symbol to its proper room boundary automatically.

Tech Stack Deployed

YOLOv8 Object DetectionComputer VisionSpatial MappingPyMuPDF

Impact Report

  • Achieved over 92% accuracy in autonomous symbol counting.
  • Reduced takeoff processing time from hours to less than 60 seconds per sheet.
  • Automatically mapped 100% of symbols to their exact room numbers, outputting structured inventory data.
  • Eliminated manual data entry errors in Excel scheduling reports.