datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
City-Landscape-In-Sight
City Landscape In Sight — Window View Perception (Images & Models)
This dataset hosts the large binary artefacts for the paper "City landscape in sight: A crowdsourced framework for unlocking urban-scale window view perceptions from real estate imagery." It is the companion of the code repository on GitHub:
Paper (arXiv): https://arxiv.org/abs/2606.15198
Code & derived data (GitHub): https://github.com/Sijie-Yang/City-Landscape-In-Sight
Images & trained weights (this dataset):… See the full description on the dataset page: https://huggingface.co/datasets/sijiey/City-Landscape-In-Sight.temporal-aerial-cityline-construction-sample
CityLine — Temporal Aerial Construction Dataset (Sample)
Temporal Aerial Vision · Construction Progress · Multiview Geometry · San Jose, CA
CityLine is a multi-year aerial imagery sequence captured from a helicopter during the construction of a major mixed-use development in San Jose, California.This sample highlights multiple construction phases over time, with several oblique views per capture date.
The full (commercial) dataset contains hundreds of high-resolution images with… See the full description on the dataset page: https://huggingface.co/datasets/SharpShots/temporal-aerial-cityline-construction-sample.naip-16d-city-cubes
NAIP 16-Day City Cubes (materialized tiles)
Each row is a 512×512 chip with 16 layers (composites, single-band indices, and masks).
What’s included (no pseudoRGB)
RGB composites: naip_rgb, s2_rgb, dem_rgb
Mono S2 layers (published as single-channel images): s2_B08, s2_MSAVI, s2_NDVI, s2_NDWI, s2_SCL
Other monos: naip_ndvi
Semantic masks: labels (task labels), landfire_family, cdl
Metadata: tile_id, city, bbox (west,south,east,north), chip_px, split, meta_json
Note:… See the full description on the dataset page: https://huggingface.co/datasets/gdurkin/naip-16d-city-cubes.garbage-classification
Trash Classification - 5,000+ photos
Dataset comprises 5,000+ photos of garbage cans featuring various capacities, types, and waste materials, designed for advancing garbage classification and waste management systems. By leveraging this dataset, researchers and developers can enhance classification systems, automate garbage collection processes, and improve strategies for reducing environmental pollution. - Get the data
Dataset characteristics:
Characteristic… See the full description on the dataset page: https://huggingface.co/datasets/ud-smart-city/garbage-classification.Crowd-Countin-Dataset
Crowd Dataset - 647 Photos
Dataset comprises 647 photos of dense crowds, containing between 1,000 to 13,000 people per image. Each image includes detailed keypoint annotations for every individual, enabling advanced data analysis and deep learning applications in crowd density estimation, object detection, and counting algorithms. - Get the data
Dataset characteristics:
Characteristic
Data
Description
Crowd photos with labeling for determining crowd density… See the full description on the dataset page: https://huggingface.co/datasets/ud-smart-city/Crowd-Countin-Dataset.City_mapThis dataset contains over 600 maps images of 45 various city around the world.
For trouble-shooting with the dataset, you may use this script to identify potentially corrupted files.
Authors
STEM.AI: stem.ai.mtl@gmail.comWilliam Harbec