mapbox/robosat

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

50
/ 100
Established

Based on the README, here's a technical summary: Implements a complete end-to-end pipeline using fully convolutional neural networks for pixel-level segmentation, with specialized tools for data preparation (downloading imagery from Mapbox APIs, extracting OSM geometries), model training on GPU/CPU, and post-processing that transforms segmentation outputs into cleaned GeoJSON features while handling Slippy Map tile boundaries. Works with standardized tile formats (256x256 pixels) to abstract geo-referenced imagery, and provides extensibility for custom data sources and feature types beyond the built-in extractors.

2,052 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 24 / 25

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Stars

2,052

Forks

388

Language

Python

License

MIT

Last pushed

Aug 27, 2020

Commits (30d)

0

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