datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/CADS-dataset.TACK_Tunnel_Data
TACK Tunnel Data (TTD): A Benchmark Dataset for Deep Learning-Based Defect Detection in Tunnels
Tunnels are essential elements of transportation infrastructure, but are increasingly affected by ageing and deterioration mechanisms such as cracking. Regular inspections are required to ensure their safety, yet traditional manual procedures are time-consuming, subjective, and costly. Recent advances in mobile mapping systems and Deep Learning (DL) enable automated visual inspections.… See the full description on the dataset page: https://huggingface.co/datasets/TACK-project/TACK_Tunnel_Data.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/4141ms/CADS-dataset.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.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/arekborucki/CADS-dataset.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT… See the full description on the dataset page: https://huggingface.co/datasets/mrmrx/CADS-dataset.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/WY-0206/CADS-dataset.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
Dataset rendering and preparation code (only .step files are required): https://github.com/DavidXu-JJ/eccv2026-cad-challenge-data-render
This repository contains the public… See the full description on the dataset page: https://huggingface.co/datasets/jingwei-xu-00/eccv2026-cad-challenge-data.hnm-fashion-recommendations-data
Dataset Rekomendasi Fashion H&M
Dataset ini berisi data transaksi, atribut pelanggan, dan metadata produk yang telah dianonimkan dari H&M Group. Kumpulan data komprehensif ini memungkinkan pemodelan perilaku pembelian pelanggan secara mendalam.
Wawasan yang dihasilkan dapat dimanfaatkan untuk berbagai tujuan bisnis yang strategis, mulai dari meningkatkan personalisasi pengalaman berbelanja, mengoptimalkan manajemen inventaris untuk efisiensi produksi, hingga mendukung inisiatif… See the full description on the dataset page: https://huggingface.co/datasets/einrafh/hnm-fashion-recommendations-data.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/sunghong/CADS-dataset.skin-cancer-ham10000-datasetexercise-dataset
Exercise Dataset — Free Tier (RepDB)
A free, ready-to-use fitness exercise dataset: 609 exercises, each
illustrated with flat-style 512×512 WebP images (a start/peak pose pair, or
a single main pose for static holds and stretches), with target muscles,
equipment, MET values, and full instructions in English, German, and
Spanish.
This public snapshot is the free tier of RepDB. Free for personal
and commercial use inside applications, with attribution.
Need exercise… See the full description on the dataset page: https://huggingface.co/datasets/RepDB/exercise-dataset.OpenVLHarness-Evaluation-Datasets
OpenVLHarness evaluation datasets
Processed evaluation splits used by
OpenVLHarness
(project page).
Each <split>.tsv holds the exact prompts (question) and annotations
(answer plus metadata) we evaluate on; image_path is relative to
images/<folder>/ inside images/<folder>.zip. GLIP.zip holds the ODinW-13
configs and COCO-format val/test annotations used for ODinW AP evaluation.
You normally don't need to download anything by hand: running
openvlharness-eval --data <split> ...… See the full description on the dataset page: https://huggingface.co/datasets/uclanlp/OpenVLHarness-Evaluation-Datasets.suno-ai-music-dataset
Suno AI Music Dataset (Multi-Genre Curated)
A human-curated, multi-genre audio dataset generated with Suno V5.5 (chirp-fenix), covering 100+ sub-sub-genres across electronic, hip-hop, Latin, jazz, world, rock, ambient, pop, reggae, and classical music. Each track ships with full audio (MP3), cover art, the original generation prompt, and a 32-column metadata schema designed for downstream audio-ML research.
This is not a "scrape everything Suno produces" dump. It is a… See the full description on the dataset page: https://huggingface.co/datasets/Kukedlc/suno-ai-music-dataset.llbench-dataset
LL-Bench: Rethinking Low-Level Vision Evaluation in the Era of Large-Scale Generative Models via Human Preferences
Anonymous release prepared for NeurIPS 2026 review. Please do not redistribute.
LL-Bench is a large-scale, human-preference benchmark for evaluating low-level
vision restoration in the era of large generative models (LGMs). It compares
10 LGMs with 16 specilist and 5 all-in-one models across 16 low-level vision tasks, paired with dense human annotations:pairwise… See the full description on the dataset page: https://huggingface.co/datasets/anonymousllbench/llbench-dataset.egocentric_dataset
Egocentric RGB-D + EMG/IMU Daily Activity Dataset
This dataset contains first-person daily activity recordings with synchronized RGB-D video, wrist EMG/IMU signals, hand keypoints, object masks, hand-object contact annotations, per-finger force annotations, and semantic action segments.
Multimodal showcase video: RGB-D, hand joints, 3D hand projection, and object masks
Overview
The dataset is designed for egocentric embodied AI and robot learning in everyday… See the full description on the dataset page: https://huggingface.co/datasets/Lo6yu/egocentric_dataset.spartina-ai-eco-evolution-data
Spartina AI eco-evolutionary reanalysis
Code repository: github.com/ydchen0806/spartina-ai-eco-evolution
Reproducible code, derived tables and audit figures for the Spartina alterniflora aerial-observation project. The release reconstructs the available 2014–2021 patch-record analysis and audits the recovered 2014–2020 environment–growth simulation archive.
Active manuscript and validation pilot
The full working manuscript is available as
editable DOCX and
PDF. It… See the full description on the dataset page: https://huggingface.co/datasets/cyd0806/spartina-ai-eco-evolution-data.TACK_Tunnel_Data
TACK Tunnel Data (TTD): A Benchmark Dataset for Deep Learning-Based Defect Detection in Tunnels
Tunnels are essential elements of transportation infrastructure, but are increasingly affected by ageing and deterioration mechanisms such as cracking. Regular inspections are required to ensure their safety, yet traditional manual procedures are time-consuming, subjective, and costly. Recent advances in mobile mapping systems and Deep Learning (DL) enable automated visual… See the full description on the dataset page: https://huggingface.co/datasets/jianwei131/TACK_Tunnel_Data.ML-Proto-DatasetTunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-DatasetTunisian Proverbs with Image Associations: A Cultural and Linguistic Dataset
Description
This dataset explores the rich oral tradition of Tunisian proverbs mapped into text format, pairing each with contextual explanations, English translations both word-to-word and it's equivalent Target Language dynamic, Automated prompt and AI-generated visual interpretations.
It bridges linguistic, cultural, and visual modalities making it valuable for tasks in cross-cultural NLP, generative… See the full description on the dataset page: https://huggingface.co/datasets/HabibaAbderrahim/Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-Dataset.cnn-based-drowsiness-detection-data
CNN-Based Drowsiness Detection - Dataset
Preprocessed, auto-labeled face-crop images used to train the model in
notgoodkeeper/cnn-based-drowsiness-detection.
Code: https://github.com/not-good-keeper/cnn-based-drowsiness-detection
Collection
Frames were captured from a webcam, then run through:
Haar Cascade face detection -> crop + pad + resize to 412x412
MediaPipe Selfie Segmentation -> background replaced with white
CLAHE contrast normalization -> grayscale… See the full description on the dataset page: https://huggingface.co/datasets/notgoodkeeper/cnn-based-drowsiness-detection-data.afrolm_active_learning_dataset
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages
GitHub Repository of the Paper
This repository contains the dataset for our paper AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages which will appear at the third Simple and Efficient Natural Language Processing, at EMNLP 2022.
Our self-active learning framework
Languages Covered
AfroLM has been… See the full description on the dataset page: https://huggingface.co/datasets/bonadossou/afrolm_active_learning_dataset.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/ty-li/Obstacle-Detection-Dataset-YOLO.PPCNet
PPCNet Dataset
Biplanar DRRs + Projection Matrices + Ground-Truth Point Clouds
A curated lumbar spine dataset for 3D point cloud reconstruction from biplanar radiographs.
Overview
This dataset provides paired biplanar DRRs, calibrated 3×4 projection matrices, and dense ground-truth point clouds for 1,037 patients with complete L1–L5 lumbar vertebrae, derived from the publicly available VerSe'19, VerSe'20, and CTSpine1K collections.… See the full description on the dataset page: https://huggingface.co/datasets/ppcnet-dataset/PPCNet.LabUtopia-Dataset🧪 LabUtopia-Dataset: Scientific Laboratory 3D Asset Library (OpenUSD)
LabUtopia-Dataset is a large-scale 3D asset library designed for simulating scientific laboratory environments.
It provides realistic lab scenes, scientific instruments, and environmental props, all stored in OpenUSD (.usd / .usdz) format for high interoperability and composability.
🧩 File Format: OpenUSD
Each asset is stored as a .usd or .usdz file.
You can load them directly in:
NVIDIA Omniverse (Create, Isaac Sim)… See the full description on the dataset page: https://huggingface.co/datasets/Ruinwalker/LabUtopia-Dataset.AI_Hype_Index_Panel_Data
Multi-Agent AI Washing Index Panel Data for Chinese A-share Listed Firms, 2015-2024
Dataset Description
This dataset provides firm-year panel measurements of AI washing among Chinese A-share listed companies from 2015 to 2024. It contains structured scores, qualitative classifications, adversarial multi-agent evaluation records, and verification evidence extracted from annual reports and firm-level AI capability indicators.
The dataset is designed for academic… See the full description on the dataset page: https://huggingface.co/datasets/fsyfb/AI_Hype_Index_Panel_Data.Follow-Line-Combine-Datasethnm-search-data
HnM Search Dataset Created from Recommendations Dataset
This synthetic data-set is created using the recommendations dataset:
https://huggingface.co/datasets/einrafh/hnm-fashion-recommendations-data (Use of this dataset is subject to the terms and conditions set forth on the original distribution page. This dataset is intended for non-commercial and research use.)
https://www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations/data (DATA ACCESS AND USE:… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/hnm-search-data.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
This repository contains the public data package for the challenge. The
evaluation Space accepts STEP predictions for the private evaluation split and
updates the leaderboard… See the full description on the dataset page: https://huggingface.co/datasets/Qiao123rvvr/eccv2026-cad-challenge-data.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/NivithaChandran/Obstacle-Detection-Dataset-YOLO.