datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
KAIST-Multispectral-Pedestrian-Detection-DatasetPedestrianPart of MONSTER: https://arxiv.org/abs/2502.15122.
Pedestrian
Category
Count
Num. Examples
189,621
Num. Channels
1
Length
24
Sampling Freq.
hourly
Num. Classes
82
License
CC BY 4.0
Citations
[1]
Pedestrian represents hourly pedestrian counts at 82 locations in Melbourne, Australia between 2009 and 2022 [1]. The processed dataset consists of 189,621 (univariate) time series, each of length 24 (i.e., representing 24 hours of data per time series). The data comes… See the full description on the dataset page: https://huggingface.co/datasets/monster-monash/Pedestrian.KAIST-Multispectral-Pedestrian-Benchmarkpedestrian-crosswalks-france-v2pedestrian_counts
pedestrian_counts (TsFile format)
Hourly pedestrian counts captured from 66 sensors in Melbourne city starting from May 2009.
This repository contains the full source .tsf series from the Monash Time Series Forecasting Repository converted to Apache TsFile format.
Summary
Source dataset: Monash-University/monash_tsf
Original source: https://zenodo.org/record/4656626
Monash subset: pedestrian_counts
Modalities: Time-series
Source series: 66
Rows: 3,132,346… See the full description on the dataset page: https://huggingface.co/datasets/THULab/pedestrian_counts.CCTV-Pedestrian-1K-Person-Attribute-Dataset
Pedestrian-1K: Synthetic CCTV Attribute Dataset
High-angle surveillance dataset with natural language descriptions and structured pedestrian attributes for Vision Transformers (ViT) and Re-ID.
🧐 Overview
Pedestrian-1K is a specialized open-source synthetic dataset for Computer Vision (CV) tasks, specifically designed for Pedestrian Attribute Recognition (PAR) and Re-Identification (Re-ID) from an overhead CCTV perspective.
Most existing datasets (like… See the full description on the dataset page: https://huggingface.co/datasets/Simuletic/CCTV-Pedestrian-1K-Person-Attribute-Dataset.pedestrian_dataMini-KAIST-Multispectral-Pedestrian-Detection-DatasetNimitz_Pedestrian_Action_Recognition_Dataset
Nimitz Pedestrian Action Recognition Dataset
A high-quality video clip dataset for pedestrian action recognition at urban intersections, collected from nighttime traffic camera footage in Honolulu, Hawaii. Each clip contains one or more pedestrians annotated via a color-coded bounding box and is sorted into one of three actions.
Actions
Label
Description
Crossing
Pedestrian actively walking across the road or intersection
Walking
Pedestrian moving along the… See the full description on the dataset page: https://huggingface.co/datasets/jzhang27/Nimitz_Pedestrian_Action_Recognition_Dataset.PedestrianVehicles_Pedestrians_and_Signboards_DatasetI developed the raw version of this mini dataset by taking different frames from this video using a python script and then did automatic labeling and a bit of manual annotation of 3 classes (Vehicle, Pedestrians and Signboards) and build this dataset for object detection tasks.
Roboflow Copy of the dataset can be found here
fetch_huggingface_google_map_terminal_github_7958-footfall-pedestrian-testrun001
fetch_huggingface_google_map_terminal_github_7958-footfall-pedestrian-testrun001
Pedestrian footfall counts on downtown Portland streets.
License
This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
You may not use the data for commercial purposes.
Contents
data.csv - sample data.
pedestrian-crosswalks-france-v1hazy-pedestrian-detectionafrica-mauritius-casualty-accidents-pedestrian-and-rider-casualties-by-poli-14449be0
Casualty Accidents Pedestrian and Rider Casualties by Poli | Africa (MDPA)
308 rows - 1 Africa country/area - 2013-2024 - 4 indicators - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 308 rows from MDPA, covering Casualty Accidents Pedestrian and Rider Casualties by Poli. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-casualty-accidents-pedestrian-and-rider-casualties-by-poli-14449be0.NYC_pedestrian_intervals
Signal Timing and Phasing Dataset
OverviewThis dataset contains records of intersections across New York City where Leading Pedestrian Intervals (LPIs) have been implemented. LPIs adjust traffic signal phasing to give pedestrians a head start before vehicles receive a green signal, improving safety at crossings. Each record includes intersection location, borough, and installation metadata. No processors script was needed.
Dataset GenerationThe dataset is obtained directly from NYC… See the full description on the dataset page: https://huggingface.co/datasets/oscur/NYC_pedestrian_intervals.africa-mauritius-casualty-accidents-pedestrian-and-rider-casualties-by-poli-8ef3d8bb
Casualty Accidents Pedestrian and Rider Casualties by Poli | Africa (MDPA)
129 rows - 1 Africa country/area - 2013-2021 - source table - Engineered by Electric Sheep Africa
TL;DR
This dataset contains 129 rows from MDPA, covering Casualty Accidents Pedestrian and Rider Casualties by Poli. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
What This Dataset Measures… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-casualty-accidents-pedestrian-and-rider-casualties-by-poli-8ef3d8bb.NYC_Bi_Annual_Pedestrian_Counts
Pedestrian Counts Dataset
The Bi-Annual Pedestrian Counts dataset already contained location information and was preserved as-is.
More information about how this dataset was generated can be found here.
KAIST-Multispectral-Pedestrian-Detection-DatasetHRGC_Pedestrian_Factortight_kaist_pedestriansAbstract
These are tight pedestrian masks for the thermal images present in the KAIST Multispectral pedestrian dataset, available at https://soonminhwang.github.io/rgbt-ped-detection/
Both the thermal images themselves as well as the original annotations are a part of the parent dataset. Using the annotation files provided by the authors, we develop the binary segmentation masks for the pedestrians, using the Segment Anything Model from Meta.
All masks are present as grayscale binary png… See the full description on the dataset page: https://huggingface.co/datasets/Suranjan-G/tight_kaist_pedestrians.pedestrian_activitypedestrian_datapedestrian1_53to68pedestrian2_20to41pedestrian2