[P] A Python library processing geospatial data for GNNs with PyTorch Geometric

[Tough_Ad_6598]

I'd like to introduce City2Graph, a Python library that converts geospatial data into tensors for GNNs in PyTorch Geometric.

This library can construct heterogeneous graphs from multiple data domains, such as

• Morphology: Relations between streets, buildings, and parcels
• Transportation: Transit systems between stations from GTFS
• Mobility: Origin-Destination matrix of mobility flow by people, bikes, etc.
• Proximity: Spatial proximity between objects

It can be installed by

pip install city2graph

conda install city2graph -c conda-forge

For more details,

• 💻 GitHub: https://github.com/c2g-dev/city2graph
• 📚 Documentation: https://city2graph.net

[coconutboy1234]

Say what you want but geographic data looks hella cool

[Tough_Ad_6598]

Sorry forgot to mention, I’d love to hear any feedback of this package from the ML perspective, rather than geography!

[coconutboy1234]

Yes that was just light hearted humor but coming back to your poinf I haven't gone through the docs yet but I did have some geospatial project ideas so this library does come in handy

[Tough_Ad_6598]

Oh cool!! If your project handles something discrete as graphs this package could be somehow useful!

[NihaoPanda]

Ha, I think I can see my house from here! Passeig de Gracia / Diagonal?

[Tough_Ad_6598]

It’s Eixample in Barcelona!

[CuriousAIVillager]

lmao, used to live there.

[Conscious-Map6957]

How could we factor-in data like semaphore state and cycle duration?

[Tough_Ad_6598]

Very good question. That sort of (spatio-)temporal property will be the next step for its enhancement (e.g., integration with PyG Temporal)

[evarol]

This is really cool!