Radiant MLHub

ramp Building Footprint Training Dataset - Paris, France

This chipped training dataset is over Paris and includes 30cm high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 or smaller pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 1,027 tiles and 3,468 buildings. The original dataset was sourced from the SpaceNet 2 Dataset before the imagery was tiled down from 650x650 pixel chips and labels were revised to be consistent with the ramp datasets notion of rooftop as the building footprint. Dataset keywords: Urban, Dense.

Dataset ID

ramp_paris_france

DOI

10.34911/rdnt.t86thc

Creator

DevGlobal

Contact

info@dev.global

Documentation

Tools & Applications

Citation

DevGlobal, (2022). ramp Building Footprint Training Dataset - Paris, France, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.t86thc

Python Client example

from radiant_mlhub import Dataset

ds = Dataset.fetch('ramp_paris_france')
for c in ds.collections:
    print(c.id)

Python Client quick-start guide

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Source Imagery Collections

Description

ramp Building Footprint Training Dataset - Paris, France - Source Imagery

License

CC-BY-SA-4.0

Collection ID

ramp_paris_france_source

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Labels Collections

Description

ramp Building Footprint Training Dataset - Paris, France - Labels

License

CC-BY-SA-4.0

Collection ID

ramp_paris_france_labels

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