25,000 urban street scene images with pixel-level semantic segmentation masks.
Browse commercial Autonomous Vehicles → Visit original source ↗Cityscapes is a benchmark for urban scene understanding released by Daimler, MPI, and TU Darmstadt. 5,000 finely-annotated + 20,000 coarsely-annotated images of street scenes from 50 cities, with pixel-level semantic segmentation labels across 30 classes (8 categories: flat, human, vehicle, construction, object, nature, sky, void). Captured under varying weather and lighting — the de facto benchmark for urban semantic segmentation.
LQS is our 7-dimension quality score, computed from the dataset's published statistics. See methodology →
Composite score computed from the 7 dimensions below: completeness, uniqueness, validation health, size adequacy, format compliance, label density, and class balance.
Common tasks and benchmarks where Cityscapes is the default or competitive choice.
What's actually in the dataset — from the maintainer's published stats.
Cityscapes is distributed under Cityscapes License (research use). This is a third-party public dataset; LabelSets indexes and scores it but does not host or redistribute the data. Always verify current license terms with the maintainer before commercial use.
LabelSets sellers offer paid autonomous vehicles datasets with what public datasets often can't give you:
Other entries in the Autonomous Vehicles catalog.