datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cocoanomaly-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.mvtec_anomaly_detectionritvij-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.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.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.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.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.ai_can_anomaly_detection_data
ai_can_anomaly_detection_data
The rows the detectors in
asana17/ai_can_anomaly_detection
are trained, calibrated and tested on, built from CAN logs by assemble.dataset there.
A run reads them at one revision and records that revision, so the models in
asana17/ai_can_anomaly_detection_runs
each name the data they were fitted on.
python3 -m evaluate.pc.run asana17/ai_can_anomaly_detection_data <revision> out runs_clone
main holds the dataset built from every log. A smaller one… See the full description on the dataset page: https://huggingface.co/datasets/asana17/ai_can_anomaly_detection_data.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.ppe-detectionhard-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.MRS-Trash-DetectionThis dataset was originally published here: https://www.modelscope.cn/datasets/YizheDev/trash_detection
As the original dataset did not include predefined train/validation/test splits, I performed stratified sampling to create them. The version published here includes these curated splits.
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 was initially developed exclusively for military aircraft detection, but was later expanded to include commercial airliners for a broader and more challenging detection task.
The dataset contains 103 military aircraft types and 11 commercial airliner types.
Military aircraft: A10, A400M, AG600, AH64, AKINCI, AV8B, An124, An22, An225, An72, B1, B2, B21, B52, Be200, C1… See the full description on the dataset page: https://huggingface.co/datasets/a2015003713/military-aircraft-detection-dataset.KAIST-Multispectral-Pedestrian-Detection-DatasetETCI-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.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.Language-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.CCTV-Smoke-Fire-Emergency-Detection-Dataset
CCTV Smoke & Fire Emergency Detection Dataset
Early-stage fire detection dataset featuring small ignition points, bin fires, and smoldering debris from a surveillance perspective.
🧐 Overview
CCTV Smoke & Fire is a specialized open-source synthetic dataset for Computer Vision (CV) tasks focused on Emergency Response, Smart City Safety, and Incident Monitoring.
The most critical fires are the ones detected in their first 60 seconds. While most fire datasets… See the full description on the dataset page: https://huggingface.co/datasets/Simuletic/CCTV-Smoke-Fire-Emergency-Detection-Dataset.PPE_Detectionweapon-detection-runs-backup-2026-07-24welding-defect-object-detection
Welding Defect Object Detection
2,028 annotated images of welds for defect detection, in both YOLO and COCO
formats. Three classes:
id (YOLO / COCO)
name
0 / 1
Bad Weld
1 / 2
Good Weld
2 / 3
Defect
Splits
split
images
annotations
train
1,619
4,583
valid
283
802
test
126
301
Layout
├── data.yaml # YOLO class names + split paths
├── train|valid|test/
│ ├── images/ # .jpg
│ └── labels/… See the full description on the dataset page: https://huggingface.co/datasets/rikkarth/welding-defect-object-detection.mvtech_anomaly_detection
MVTec Anomaly Detection Dataset (MVTec AD)
Dataset description
The MVTec Anomaly Detection (MVTec AD) dataset is a large-scale real-world dataset for unsupervised anomaly detection in industrial inspection scenarios.It contains high-resolution images of multiple object and texture categories, including normal samples and various defect types with pixel-level ground truth masks.
Official website:https://www.mvtec.com/company/research/datasets/mvtec-ad
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/micguida1/mvtech_anomaly_detection.Language_Detection
Language_Detection - Multilingual Text Classification Dataset
This dataset is a collection of multilingual text samples designed for training and predicting languages in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Data Science (DS) applications. It contains labeled data that associates text samples with their respective languages, enabling language detection and classification tasks.
Dataset Overview
The dataset consists of two columns:… See the full description on the dataset page: https://huggingface.co/datasets/sakthivinash/Language_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.Plant_Detection_Classification
Plant Species Classification Dataset
A comprehensive dataset containing 64 different plant species with high-quality images for machine learning and computer vision applications.
Model Trainig code and trainned model with detailed performance analysis is present on the Github
https://github.com/jameelkhalidawan/Plant-Detection-Model-using-Yolo
Dataset Overview
This dataset is designed for plant species classification tasks and contains images of various plant… See the full description on the dataset page: https://huggingface.co/datasets/jameelkhalidawan/Plant_Detection_Classification.csgo-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.drone-audio-detection-samples
Dataset Description
Drone Audio Detection Samples (DADS) is currently the largest publicly available drone audio database, specifically designed for developing drone detection systems using deep learning techniques. All audio files are standardized to a sample rate of 16,000 Hz, 16-bit depth, mono-channel, and vary in length from 500 milliseconds to several minutes.
Most drone audio files were manually trimmed to ensure that a drone was always present in the recording. However, some… See the full description on the dataset page: https://huggingface.co/datasets/geronimobasso/drone-audio-detection-samples.