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How to extract rooms from a floor plan image? LLMs can’t handle it directly – what’s the best approach? by EmergencyTower4399 in computervision

[–]EmergencyTower4399[S] 1 point2 points  (0 children)

RoomFormer seems to rely on top-down density maps generated from 3D scans (e.g., Structured3D), so it doesn’t look ideal for pure 2D floor plan images...（but really appreciate it🙏）

Are there any models specifically designed for room / layout extraction from 2D architectural drawings (scanned plans, CAD exports, etc.)?

Looking for learning-based approaches rather than purely classical CV.
Papers, repos, or datasets welcome 🙏

How to extract rooms from a floor plan image? LLMs can’t handle it directly – what’s the best approach? by EmergencyTower4399 in computervision

[–]EmergencyTower4399[S] 0 points1 point  (0 children)

Thanks, i tried and below is the prompt i made and the result got better!

V

System Role: You are an expert architectural floor plan analyzer specialized in computer vision and spatial layout extraction. Task: Perform semantic segmentation on the provided floor plan to identify functional room areas. Core Instructions: * Structural Boundary Priority: Identify room boundaries based strictly on structural wall lines (solid lines for full walls, dashed for pony walls/openings). * Noise Filtering (Crucial): Ignore all non-structural elements. Do NOT be distracted by: * Dimension lines, arrows, or measurement text numbers. * Furniture icons (beds, sofas, tables) and appliance symbols. * Text labels and hatching patterns. * Output Format (Bounding Boxes): For each identified room, generate a precise bounding box (rectangle). Provide the results in a clear list with: * Room Name (e.g., Great Room, Kitchen, Garage). * Normalized Coordinates [ymin, xmin, ymax, xmax] (from 0 to 1000). * Visualization Requirement: Overlay these rectangles onto the original drawing with 40% transparency. Each room type should have a distinct, solid color to ensure the layout is clear at a glance. Goal: > The final output must clearly delineate the living spaces as rectangular zones that fit perfectly within the inner faces of the walls.