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Yytsi/
floorplan-to-3d-walls

Name: floorplan-to-3d-walls
Availability: InStock

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Floorplan to 3D — segmentation model

A UNet decoder with a ResNet-34 encoder backbone (ImageNet-pretrained), trained on CubiCasa5K to segment architectural floor plans into four classes: floor / wall / door / window.

The full project (training code, polygon extractor, FastAPI inference server, 3D Three.js viewer) lives at https://github.com/Yytsi/floorplan-to-3d.

A hosted preview at floorplan-to-3d.pages.dev shows three pre-rendered example plans extruded into 3D — it's static, no backend. To run inference on your own SVGs, clone the repo and start the local FastAPI server (the viewer detects it via /healthz and reveals an upload button).

Files

best.safetensors — model weights, ~98 MB. Loadable with safetensors.torch.load_file. The epoch and best_miou are stored in the safetensors metadata header.
config.yaml — training config required by the loader (image size, letterbox, normalization, encoder name).

Quick start

bash

mkdir -p weights
curl -L -o weights/best.safetensors https://huggingface.co/Yytsi/floorplan-to-3d-walls/resolve/main/best.safetensors
curl -L -o weights/config.yaml      https://huggingface.co/Yytsi/floorplan-to-3d-walls/resolve/main/config.yaml

Then follow the README on GitHub for the inference server + viewer.

Training

Data: CubiCasa5K (high-quality + high-quality-architectural splits).
Input: 512×512 RGB, aspect-preserving letterbox so non-square plans aren't stretched. ImageNet-mean fill in the padding.
Encoder: ResNet-34 pretrained on ImageNet.
Loss: cross-entropy.
Best val mIoU: 0.983 at epoch 26.

Limitations

CubiCasa5K is dominated by Nordic residential plans drawn in a specific CAD style. The model generalizes well within that distribution but may miss elements on hand-drawn sketches, commercial blueprints, or plans using very different line conventions.
Only the four structural classes above are predicted. Furniture, fixtures, and text annotations are treated as floor.
Input is rasterized from SVG at 512×512; very long thin walls in oversized plans can get sub-pixel and be missed.

License

MIT — see the GitHub repo.