https://doi.org/10.34911/rdnt.f94cxb
building footprints segmentation
This dataset was developed as part of a challenge to segment building footprints from aerial imagery. The goal of the challenge was to accelerate the development of more accurate, relevant, and usable open-source AI models to support mapping for disaster risk management in African cities [Read more about the challenge]. The data consists of drone imagery from 10 different cities and regions across Africa
https://radiant-mlhub.s3-us-west-2.amazonaws.com/open-cities-ai-challenge/documentation.pdf
GFDRR Labs (2020). "Open Cities AI Challenge Dataset", Version 1.0, Radiant MLHub. [Date Accessed] https://doi.org/10.34911/rdnt.f94cxb
open_cities_ai_challenge_testopen_cities_ai_challenge_train_tier_1_labelsopen_cities_ai_challenge_train_tier_1_sourceopen_cities_ai_challenge_train_tier_2_labelsopen_cities_ai_challenge_train_tier_2_source