datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cocoKAIST-Multispectral-Pedestrian-Detection-Datasetanomaly-detection
On-board Anomaly Detection for Marine Environmental Monitoring — PhiSat-2 Database 2025
This folder contains data (images, metadata, and segmentation masks) used to train and test the marine anomaly detection application developed by the IRMA team at IRT Saint Exupéry for the PhiSat-2 OrbitalAI challenge.
Description
This dataset contains images generated from Sentinel-2 satellite data using the ESA simulator, designed to replicate the characteristics of the… See the full description on the dataset page: https://huggingface.co/datasets/sirbastiano94/anomaly-detection.traffic-vehicle-detection
Edge-AI Traffic Vehicle Detection (UA-DETRAC CCTV)
Part of the Edge-AI Traffic & Vehicle Analytics System repository by thundarstrom.
Dataset Summary
Curated and normalized 23,319 CCTV traffic images from fixed intersection surveillance cameras (UA-DETRAC benchmark). Contains 215,109 annotated bounding boxes in standard YOLO format across 4 vehicle classes: car, bus, truck, and van.
Class Mapping
Class 0 (car): 177,403 bboxes (82.5%)
Class 1 (bus):… See the full description on the dataset page: https://huggingface.co/datasets/PRAS4NTH/traffic-vehicle-detection.detectai-dataset
DETECTAI Dataset
Auto-collected & labeled dataset for AI content detection. 60 sources, 24-shard pipeline.
Total: 516,672 | Updated: 2026-03-12T08:01:14.589Z | Pipeline: Cloudflare Workers
ETCI-2021-Flood-Detection
ETCI 2021 Flood Detection Dataset
Description
The ETCI 2021 Flood Detection Dataset is a comprehensive flood detection segmentation dataset that focuses on SAR (Synthetic Aperture Radar) images taken by the ESA Sentinel-1 satellite. This dataset provides pairs of VV (Vertical Transmit, Vertical Receive) and VH (Vertical Transmit, Horizontal Receive) polarization images, which have been processed by the Hybrid Pluggable Processing Pipeline (hyp3). Additionally… See the full description on the dataset page: https://huggingface.co/datasets/blanchon/ETCI-2021-Flood-Detection.Obstacle-Detection-Dataset-YOLO
ROD-Dataset: Real-Time Obstacle Detection for Smartphone-Based Assistive Vision
24,326-image, 25-class YOLO dataset for obstacle detection
This dataset is the data product of our Real-Time Obstacle Detection (ROD) project at Amirkabir University of Technology, Tehran. The project addresses two related public-safety problems on the city sidewalk: the limited situational awareness of people living with visual impairments, and the elevated collision and fall risk for pedestrians… See the full description on the dataset page: https://huggingface.co/datasets/Abtinzandi/Obstacle-Detection-Dataset-YOLO.llama3-jailbreaksgemma2-jailbreaksrsna-2023-abdominal-trauma-detectionThis dataset is the preprocessed version of the dataset from RSNA 2023 Abdominal Trauma Detection Kaggle Competition.
It is tailored for segmentation and classification tasks. It contains 3 different configs as described below:
- segmentation: 206 instances where each instance includes a CT scan in NIfTI format, a segmentation mask in NIfTI format, and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
- classification: 4711 instances where each instance includes a CT scan in NIfTI format, target labels (e.g., extravasation, bowel, kidney, liver, spleen, any_injury), and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
- classification-with-mask: 206 instances where each instance includes a CT scan in NIfTI format, a segmentation mask in NIfTI format, target labels (e.g., extravasation, bowel, kidney, liver, spleen, any_injury), and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
All CT scans and segmentation masks had already been resampled with voxel spacing (2.0, 2.0, 3.0) and thus its reduced file size.Barkopedia-Dog-Vocal-Detection
🐾 Dog Vocal Detection
This dataset is curated from internet videos to support research in dog vocalization detection using both weak and strong supervision.
It contains approximately 7,500 seconds of strongly labeled training audio
Over 9,000 seconds of weakly labeled clips sourced from AudioSet are included.
The dataset also provides 24 hours of unlabeled audio clips from our own collection.
To simulate realistic conditions, some clips feature dogs present without barking… See the full description on the dataset page: https://huggingface.co/datasets/ArlingtonCL2/Barkopedia-Dog-Vocal-Detection.godseye-violence-detection-dataset
Keypoints-RWF-total Dataset
This dataset is a fusion of three distinct datasets:
RWF-2000: A dataset that includes videos of real-world fights and non-fight scenarios.
Hockey Violence Dataset: A dataset focused on violent interactions in hockey games.
Airtlab Violence Dataset: A dataset containing videos of violent incidents in various settings.
Important Note: We do not own these datasets. By using this dataset, you are agreeing to follow the rules and licensing agreements of… See the full description on the dataset page: https://huggingface.co/datasets/valiantlynxz/godseye-violence-detection-dataset.ritvij-saxena-iris-detection-pythonHere is the IRIS dataset for the project iris-detection-python.
Official Statement
I hereby declare that I do not own the rights to the dataset used in this project. This dataset was provided by the faculty and utilized solely for educational purposes as part of an assignment for the Biometrics course (CS 559) at the Illinois Institute of Technology.
The dataset is provided for academic and research purposes only, and I encourage others to use it responsibly for similar educational… See the full description on the dataset page: https://huggingface.co/datasets/saxenaritvij/ritvij-saxena-iris-detection-python.mvtec_anomaly_detectioncsgo-player-detection
CS2 player detection - native 640x640 centre crops
5473 labelled frames from Counter-Strike 2 with 10643 boxes for
player bodies and heads, split by team.
A YOLO26 detector trained on this data is at
fvossel/csgo-player-detection. Its training set is not quite
identical: it also contains the images from the source dataset named below, which
are not redistributed here.
Everything that produced this data is open: capture, demo rendering, the labelling
loop and the training and… See the full description on the dataset page: https://huggingface.co/datasets/fvossel/csgo-player-detection.visa-anomaly-detection
VisA — Visual Anomaly Dataset
Mirror of the VisA (Visual Anomaly) dataset for research use. Staged as a proxy/pretraining
dataset for CoRe's Situational Control paint-inspection work (core-lab/situational-control).
Source
Original repo: https://github.com/amazon-science/spot-diff
Original download: https://amazon-visual-anomaly.s3.us-west-2.amazonaws.com/VisA_20220922.tar
License: CC BY 4.0 (confirmed in the source repo README)
Contents
10,821… See the full description on the dataset page: https://huggingface.co/datasets/imaadd05/visa-anomaly-detection.indoor-safety-hazard-detection-and-work-zone-monitoring
Indoor Safety Hazard Detection & Work-Zone Monitoring
Generated by datapack-import.ts
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs. Files are uploaded as downloaded unless optional PNG recompression is enabled by… See the full description on the dataset page: https://huggingface.co/datasets/physicl/indoor-safety-hazard-detection-and-work-zone-monitoring.aidovecl-vehicle-detection-classification-localization
AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization
We introduce an annotated AI-generated dataset of eye-level vehicle images using outpainting, offering versatile generation of diverse vehicle classes in varied contexts with pretrained models.
Citation Notice
Please ensure that all publications and presentations using this data reference the following paper:
Kazemi, A., Fatima, Q. ul A., Kindratenko, V., & Tessum, C. W.… See the full description on the dataset page: https://huggingface.co/datasets/amir-kazemi/aidovecl-vehicle-detection-classification-localization.seraphim-drone-detection-dataset
Seraphim Drone Detection Dataset
Dataset Overview
This is a comprehensive drone image dataset curated from 23 open-source datasets and processed through a custom cleaning pipeline. The dataset is designed for training object detection models to identify drones in various environments and conditions. The majority of images feature rotary-wing (multi-rotor) unmanned aerial vehicles (UAVs), with a smaller portion representing fixed-wing and hybrid.… See the full description on the dataset page: https://huggingface.co/datasets/lgrzybowski/seraphim-drone-detection-dataset.military-aircraft-detection-dataset
Military Aircraft Detection Dataset
Military aircraft detection dataset in COCO and YOLO format.
The dataset contains 103 different military aircraft types.
['A10', 'A400M', 'AG600', 'AH64', 'AKINCI', 'AV8B', 'An124', 'An22', 'An225', 'An72', 'B1', 'B2', 'B21', 'B52', 'Be200', 'C1', 'C130', 'C17', 'C2', 'C390', 'C5', 'CH47', 'CH53', 'CL415', 'E2', 'E7', 'EF2000', 'EMB314', 'F117', 'F14', 'F15', 'F16', 'F18', 'F2', 'F22', 'F35', 'F4', 'FCK1', 'H6', 'Il76', 'J10', 'J20', 'J35'… See the full description on the dataset page: https://huggingface.co/datasets/a2015003713/military-aircraft-detection-dataset.CS2CD.Counter-Strike_2_Cheat_Detection
Counter Strike 2 Cheat Detection Dataset
Overview
The CS2CD (Counter-Strike 2 Cheat Detection) dataset is an anonymised dataset comprised of Counter-Strike 2(CS2) gameplay at a variety of skill-levels with cheater annotations. This dataset contains 478 CS2 matches with no cheater present, and 317 matches CS2 matches with at least one cheater present.
Dataset structure
The dataset is partitioned into data with at least one cheater present, and data with no… See the full description on the dataset page: https://huggingface.co/datasets/CS2CD/CS2CD.Counter-Strike_2_Cheat_Detection.lie-detection-rollouts
Lie Detection Rollouts
Assistant completions across many open-weight models on the lie-detection
evaluation suite used by the
deception research pipeline. One subset per model,
one split per task.
Columns
messages — list of OpenAI-style messages. Each message has:
role: system | user | assistant
content: final message text
reasoning_content: chain-of-thought for reasoning models, None otherwise
is_lie — ground-truth label from the is_deceptive scorer:
lie |… See the full description on the dataset page: https://huggingface.co/datasets/ai-safety-institute/lie-detection-rollouts.smart-bin-detect
arudaev/smart-bin-detect
Training data for Smart Bin Recognition – a validator ("is there a bin?")
and an identifier ("which bin?"). The design lives in docs/04-ml-pipeline.md
in the project repo, which is private; the manifests here carry per-image
provenance and are the authoritative record of what this dataset contains.
Every image carries provenance: source, source URL, licence, region,
capture date, annotator where known, label origin (human / machine /
legacy /… See the full description on the dataset page: https://huggingface.co/datasets/arudaev/smart-bin-detect.lie-detector-resultshard-hat-detection
Dataset Card for hard-hat-detection
This dataset, contains 5000 images with bounding box annotations in the PASCAL VOC format for these 3 classes:
Helmet
Person
Head
This is a FiftyOne dataset with 5000 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'split', 'max_samples', etc… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/hard-hat-detection.Safety-Toxicity-Detection
SEA Toxicity Detection
SEA Toxicity Detection evaluates a model's ability to identify toxic content such as hate speech and abusive language in text. It is sampled from MLHSD for Indonesian, TTD for Thai, and ViHSD for Vietnamese.
Supported Tasks and Leaderboards
SEA Toxicity Detection is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.
Languages
Indonesian (id)
Thai… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/Safety-Toxicity-Detection.bedroom-change-detection-state-monitoring
Bedroom Change Detection & State Monitoring
Generated by datapack-import.ts
This dataset mirrors public data-pack render outputs from Physicl.
Each row represents one render view. The image column contains a stable URL to the primary render image uploaded under /data; image_path stores the relative repository path and data_commit_sha pins the Hugging Face dataset commit used by those URLs. Files are uploaded as downloaded unless optional PNG recompression is enabled by the sync… See the full description on the dataset page: https://huggingface.co/datasets/physicl/bedroom-change-detection-state-monitoring.MLLM-Generated-Image-Detection-Dataset
MLLM-Generated Image Dataset
This dataset contains real and AI-generated image samples organized for binary MLLM-generated image detection.
Paper | Code
Dataset Summary
We construct an MLLM-generated image detection benchmark from GPT Image2 and Nano Banana2. This benchmark covers texture-dominated, structure-dominated, and hybrid-dominated. It is designed to evaluate detector performance under the new challenges introduced by large-scale image generation models.… See the full description on the dataset page: https://huggingface.co/datasets/zr-zhang/MLLM-Generated-Image-Detection-Dataset.Temporal_Action_Detectioncode_x_glue_cc_defect_detection
Dataset Card for "code_x_glue_cc_defect_detection"
Dataset Summary
CodeXGLUE Defect-detection dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Defect-detection
Given a source code, the task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack. We treat the task as binary classification (0/1), where 1 stands for insecure code and 0 for secure… See the full description on the dataset page: https://huggingface.co/datasets/google/code_x_glue_cc_defect_detection.