datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multimodal-ct-radiology-reports
Perle AI Multi-phase CECT and CT with Radiology Reports
Summary
A de-identified CT dataset from Perle AI, paired with the original radiology reports. It supports work on multi-modal medical imaging: phase or pathology classification, report generation from images, and visual question answering.
The release has three configurations:
Config
Modality
Subjects
Pairing
cect_3phase
3-phase contrast-enhanced abdominal CT (DICOM)
5
per-subject text report +… See the full description on the dataset page: https://huggingface.co/datasets/Perle-ai/multimodal-ct-radiology-reports.SA-BENCH
SA-BENCH
SA-BENCH is the benchmark dataset released with “Beyond Pixels: Benchmarking and Reward-Based Assessing Framework for Visual Spatial Aesthetics.”
Accepted to CVPRW 2026.
GitHub | CVF Open Access | arXiv | Model
It evaluates the spatial aesthetics of interior images along four dimensions:
distortion
harmony
layout
lighting
SA-BENCH contains 17,768 annotated examples across four spatial-aesthetic dimensions, with image assets and human annotations for training and… See the full description on the dataset page: https://huggingface.co/datasets/gaoyuan-ai/SA-BENCH.ODELIA-Challenge-2025
ODELIA Challenge Dataset
This dataset is part of the ODELIA project, a European Horizon initiative focused on developing privacy-preserving, AI-driven diagnostic tools using swarm learning.
The dataset provided here represents a curated subset of data from the broader ODELIA consortium. It is designed to facilitate the development, benchmarking, and validation of AI algorithms that can operate effectively across a range of heterogeneous clinical settings.
The dataset contains… See the full description on the dataset page: https://huggingface.co/datasets/ODELIA-AI/ODELIA-Challenge-2025.house_kg_full_dataset
house.kg — Kyrgyzstan Real Estate (multimodal)
A complete snapshot of house.kg, the largest real-estate
board in Kyrgyzstan: every sale and rental listing, with coordinates, prices, seller
identities, agency ratings, reviews — and 227,294 photographs.
Field names are English; values are kept in the original language (Russian/Kyrgyz),
exactly as the site renders them.
💻 Scraper source code on GitHub →
The complete, open scraper that produced this dataset —… See the full description on the dataset page: https://huggingface.co/datasets/aiacademy-kg/house_kg_full_dataset.MM-Food-100K
Overview
This project aims to introduce and release a comprehensive food image dataset designed specifically for computer vision tasks, particularly food recognition, classification, and nutritional analysis. We hope this dataset will provide a reliable resource for researchers and developers to advance the field of food AI. By publishing on Hugging Face, we expect to foster community collaboration and accelerate innovation in applications such as smart recipe recommendations… See the full description on the dataset page: https://huggingface.co/datasets/Humanbased-AI/MM-Food-100K.HUGO-Bench-Paper-Reproducibility
HUGO-Bench Paper Reproducibility
Supplementary data and reproducibility materials for the paper:
Vision Transformers for Zero-Shot Clustering of Animal Images: A Comparative Benchmarking Study - https://arxiv.org/abs/2602.03894
Hugo Markoff, Stefan Hein Bengtson, Michael Ørsted
Aalborg University, Denmark
Dataset Description
This repository contains complete experimental results, pre-computed embeddings, and execution logs from our comprehensive benchmarking study… See the full description on the dataset page: https://huggingface.co/datasets/AI-EcoNet/HUGO-Bench-Paper-Reproducibility.anylearning-data
AnyLearning datasets
This repository contains reproducible sample datasets used to develop and test
AnyLearning OSS.
Dataset licenses are recorded in LICENSES.md. The repository's
scripts and original documentation are Apache-2.0, but that license does not
override the terms of any dataset. Check the dataset license before use.
Licence-cleared
Task
Dataset
Licence
Image classification
ZhangLabData: Chest X-Ray
CC BY 4.0
Object detection
Safety Helmet… See the full description on the dataset page: https://huggingface.co/datasets/nrl-ai/anylearning-data.tripmatch-ai-dataset
TripMatch AI Dataset
A reproducible multimodal dataset for the TripMatch AI Final Project. It contains
10,000 synthetic text trip plans with a raw idea generated for every row by the
pretrained Hugging Face model google/flan-t5-small, plus 5,000 real street-view images
retained as extra multimodal work. The two configurations are separate so Dataset
Viewer can load each schema correctly.
Dataset statistics
Configuration
Rows
Main fields
Intended task… See the full description on the dataset page: https://huggingface.co/datasets/avihayamor/tripmatch-ai-dataset.lalafo-kg-cars
lalafo.kg — Kyrgyzstan Cars (used-car market)
Scraped from lalafo.kg, the largest informal classifieds
board in Kyrgyzstan — messier and larger than the curated boards, and closer to the
real street-level market. Field names are English; values are kept in the original
language (Russian).
Subsets
subset
rows
description
listings
54,518
one row per advertisement (every category, deal and region in scope)
users
49,685
sellers (ad authors), with… See the full description on the dataset page: https://huggingface.co/datasets/aiacademy-kg/lalafo-kg-cars.africa-synth-aid-flows-brain-tumor-mri-colorized-ehr-all
Brain Tumor (MRI) Detection Colourized with EHR | Africa (Electric Sheep Africa metadata inventory)
Size category: n<1K - Formats: not declared - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-aid-flows-brain-tumor-mri-colorized-ehr-all.lalafo-kg-phones
lalafo.kg — Kyrgyzstan Mobile Phones (handsets for sale)
Scraped from lalafo.kg, the largest informal classifieds
board in Kyrgyzstan — messier and larger than the curated boards, and closer to the
real street-level market. Field names are English; values are kept in the original
language (Russian).
Subsets
subset
rows
description
listings
8,160
one row per advertisement (every category, deal and region in scope)
users
6,605
sellers (ad authors), with… See the full description on the dataset page: https://huggingface.co/datasets/aiacademy-kg/lalafo-kg-phones.house_kg_full_dataset_frames
house.kg — Kyrgyzstan Real Estate, over time
Sale and rental listings scraped from house.kg, the largest
real-estate board in Kyrgyzstan, re-measured on a schedule. Field names are
English; values are kept in the original language (Russian), exactly as the site
renders them.
Coverage: 2026-09-08. This is the baseline snapshot; later runs append new partitions.
Subsets
subset
rows
description
listings
25,264
one row per advertisement — current state plus… See the full description on the dataset page: https://huggingface.co/datasets/aiacademy-kg/house_kg_full_dataset_frames.Latent-Resonance-AI-Image-Forensics-Benchmark-N1000
Latent Resonance: SOTA Large-Scale AI Image Forensics Benchmark (N=1,000)
Author: Debdip Bandyopadhyay (Independent AI Researcher, Kolkata, India; M.Tech, IIT Jodhpur, AI & Data Science)Preprint & Paper: Latent Resonance: Zero-Shot Autoencoder Inversion and Azimuthal Spectral Forensics for Diffusion Image Attribution (IEEE Flagship / CERN Zenodo 2026)
1. Executive Summary & Diagnostic Suite
This repository contains the complete empirical evaluation records… See the full description on the dataset page: https://huggingface.co/datasets/DebdipCS/Latent-Resonance-AI-Image-Forensics-Benchmark-N1000.COCOLogic-v2
COCOLogic-V2
COCOLogic-V2 is an object-centric dataset for visual inductive reasoning on real-world
images. Built on MSCOCO, it frames reasoning as a multilabel classification task over 10
compositional first-order-logic rules (object presence/absence, counting, and count
comparisons). Samples of each rule are divided into different positive variants, as well
as types of near-boundary (NB) negatives, and the typically easy far-from-boundary (FB)
negatives. These annotations… See the full description on the dataset page: https://huggingface.co/datasets/AIML-TUDA/COCOLogic-v2.amt-airframe-handbook-dataset
AMT Airframe Handbook Dataset
A comprehensive dataset extracted from the FAA Aviation Maintenance Technician (AMT) Airframe Handbook, containing text content and rendered page images suitable for training vision-language models.
Overview
This dataset was created using the doc-parser-engine - a production-grade document parsing engine with HuggingFace integration. The source document is the FAA… See the full description on the dataset page: https://huggingface.co/datasets/Remixonwin/amt-airframe-handbook-dataset.evaluation
Skill-Aligned Annotation for Text-to-Image Evaluation
Companion dataset for the NeurIPS 2026 paper "Towards Objective Evaluation".
The dataset contains generated images from 7 text-to-image models, evaluated
by 6 human annotators (anonymized) plus an LLM judge across 9 skill-aligned
annotation strategies.
Configs
Config
Rows
Description
images
621
Generated images (621 WebP) with embedded bytes; one row per (prompt_id, generator).
prompts
179
Per-prompt… See the full description on the dataset page: https://huggingface.co/datasets/Skill-Aigned/evaluation.