datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
global-streetscapes
Global Streetscapes
Repository for the tabular portion of the Global Streetscapes dataset by the Urban Analytics Lab (UAL) at the National University of Singapore (NUS).
Content Breakdown
Global Streetscapes (74 GB)
├── data/ (49 GB)
│ ├── 21 CSV files with 346 unique features in total and 10M rows each (37 GB)
│ ├── parquet/ (12 GB) (New)
│ ├── 21 Parquet equivalents of the 21 CSV files (New)
│ ├── 1 combined Parquet file (New)
├── manual_labels/ (23… See the full description on the dataset page: https://huggingface.co/datasets/NUS-UAL/global-streetscapes.global-streetscapes-parquet
Global Streetscapes
Repository for the tabular portion of the Global Streetscapes dataset by the Urban Analytics Lab (UAL) at the National University of Singapore (NUS).
Content Breakdown
Global Streetscapes (62+ GB)
├── data/ (37 GB)
│ ├── 21 CSV files with 346 unique features in total and 10M rows each
├── manual_labels/ (23 GB)
│ ├── train/
│ │ ├── 8 CSV files with manual labels for contextual attributes (training)
│ ├── test/
│ │ ├── 8 CSV files with… See the full description on the dataset page: https://huggingface.co/datasets/ClaireDons/global-streetscapes-parquet.michiyomi-tokyo-streetscape
michiyomi — Tokyo streetscape verbalization open data
English
Overview
michiyomi pairs coordinates with structured Japanese descriptions of physical streetscapes visible in public Mapillary imagery. A vision-language model (VLM) verbalized only what is visible in each image: no map, address, place name, facility name, statistics, or other external knowledge was injected. Release 2026-09-13-r1 contains 1,914,490 scenes covering all of Tokyo: the 23… See the full description on the dataset page: https://huggingface.co/datasets/finalvent/michiyomi-tokyo-streetscape.global-streetscapes
Global Streetscapes
Repository for the tabular portion of the Global Streetscapes dataset by the Urban Analytics Lab (UAL) at the National University of Singapore (NUS).
Content Breakdown
Global Streetscapes (74 GB)
├── data/ (49 GB)
│ ├── 21 CSV files with 346 unique features in total and 10M rows each (37 GB)
│ ├── parquet/ (12 GB) (New)
│ ├── 21 Parquet equivalents of the 21 CSV files (New)
│ ├── 1 combined Parquet file (New)
├── manual_labels/ (23… See the full description on the dataset page: https://huggingface.co/datasets/lune7723/global-streetscapes.global-streetscapes
Global Streetscapes
Repository for the tabular portion of the Global Streetscapes dataset by the Urban Analytics Lab (UAL) at the National University of Singapore (NUS).
Content Breakdown
Global Streetscapes (74 GB)
├── data/ (49 GB)
│ ├── 21 CSV files with 346 unique features in total and 10M rows each (37 GB)
│ ├── parquet/ (12 GB) (New)
│ ├── 21 Parquet equivalents of the 21 CSV files (New)
│ ├── 1 combined Parquet file (New)
├── manual_labels/ (23… See the full description on the dataset page: https://huggingface.co/datasets/KevinAldrin/global-streetscapes.nihon_gaikei_japanese_streetscapesJerusalem-Streetscapes
Jerusalem Streetscapes Dataset
A small image dataset containing photos of the rapidly changing urban landscape of Jerusalem, Israel, captured by day and by night.
About
This dataset documents the evolving cityscape of Jerusalem through 120 photographs taken between June 2024 and September 2025.
Dataset Details
Number of Images: 120
Time Period: June 2024 - September 2025
Location: Jerusalem, Israel
Coverage: Day and night photography of urban landscapes… See the full description on the dataset page: https://huggingface.co/datasets/danielrosehill/Jerusalem-Streetscapes.retail-streetscape-storefront-signals
Retail Streetscape & Storefront Signals Visual Dataset
Rows: 73,704
Dataset Description
Retail Streetscape & Storefront Signals Visual Dataset is a global wildlife image dataset-style street-level imagery collection focused on retail frontage, placemaking, and urban commerce signals in real-world scenes. The labeled target in this dataset is the feature field, which captures matched visual feature labels for Storefront, Restaurant, Coffee Shop, Pharmacy, Outdoor… See the full description on the dataset page: https://huggingface.co/datasets/Outerview/retail-streetscape-storefront-signals.Global_streetscapes_max_50_per_city
