Architectural Floor Plan Finding and Labeling (Segmentation)

We are building a computer vision model that is able to analyze and segment architectural floor plans based on room type. We need labelers to find and annotate floor-plan images using Roboflow with polygon and segmentation tools.

Labeling tasks include:
- Drawing polygon masks around each room shown in an architectural floor plan.
- Labeling each room with an occupancy type (e.g., Bedroom, Bathroom, Corridor, Storage, Mechanical, Office, etc.).
- Ensuring polygons are clean, non-overlapping, and accurately follow the printed room boundaries.
- Verifying that text labels (e.g., room names) correspond to the assigned occupancy type.

Dataset details:
- Source files are images extracted from architectural PDFs and high-resolution raster images.
- Floor plans vary widely in style, clarity, and density (residential, commercial, mixed-use).
- Each file requires 15-20+ individual labeled items (polygons + room type tags).

Skillsets required:
- Experience with polygon/segmentation labeling in Roboflow or similar technology.
- Ability to accurately interpret architectural drawings (walls, boundaries, room name text, abbreviations).
- Basic familiarity with building layouts is preferred but not required; detailed instructions and examples will be provided.
- Strong attention to detail and consistency.

This dataset will be used to train a segmentation model for automated room detection and occupancy classification within architectural drawings.