Spatial Reasoning Use Case

Room Detection & Segmentation

Automating room detection & segmentation from architectural floor plans using custom computer vision and spatial reasoning.

1. The Problem

Extracting enclosed room geometry, room names, and precise net area measurements requires tedious CAD tracing or manual polyline creation.

2. Input Drawing

Architectural floor plan PDF containing wall lines, room text labels (e.g. Conference Room 204), and dimension strings.

INPUT FORMATS: PDF (Vector / Raster) · DWG Renders · TIFF / PNG Scans

3. AI Pipeline Process

Geometric wall graph construction closes bounding wall polygons while 360° OCR associates room text labels with their enclosing polygon area.

Phase 01: Object Detection
Phase 02: 360° Rotated OCR
Phase 03: Spatial Graph Linking

4. Annotated Visual Output

Color-coded room polygon overlay highlighting every enclosed space with calculated area callouts.

[VISUAL BOUNDING BOX OVERLAY & COLOR-CODED DETECTION CANVAS]

5. Structured Data Export

JSON geometry payload containing room names, room numbers, net floor areas (sq ft / m²), perimeter lengths, and polygon vertex coordinates.

{ "use_case": "Room Detection & Segmentation", "status": "success", "confidence_score": 0.984, "extracted_count": 42, "export_formats": ["JSON", "REST_API", "CSV", "EXCEL"] }

6. Business Impact

Powers automated indoor mapping, real estate area calculations, flooring takeoffs, and PropTech spatial APIs.

Frequently Asked Questions

How does the system handle open-concept floor plans without physical walls?

We apply virtual boundary heuristics based on column lines, floor transition symbols, and ceiling plan divisions.

Request Room Detection & Segmentation Assessment

Tell us what you want AI to do with your drawings

Fill out the details below and an AI engineer will evaluate your requirements.

Upload Sample Plan (Optional)

PDF, DWG, PNG, or ZIP up to 50MB

Strict confidentiality. Your sample drawings and project details are never shared or used to train public models.