datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
webvid-10MMM-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.cbis-ddsm-r
CBIS-DDSM-R: A Curated Radiomic Feature Dataset for Breast Cancer Classification
Dataset Summary
CBIS-DDSM-R is an open-source, radiomics-ready extension of the Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM). It is designed to facilitate reproducible radiomics and quantitative imaging research in breast cancer analysis.
The dataset provides a standardized preprocessing pipeline for mammograms and includes IBSI-compliant… See the full description on the dataset page: https://huggingface.co/datasets/Rosalia1212/cbis-ddsm-r.forestllava-dataset
Forest-LLaVA Multimodal Tree-Species Dataset
Forest-LLaVA is a multimodal remote-sensing dataset for tree-species
recognition and structured vision-language research. Each record is indexed by
a numeric sample_id from the US subset of GlobalGeoTree and is linked to a
60 m × 60 m patch from NAIP Optical, Sentinel-2 MSI and Sentinel-1 SAR data,
four-level taxonomic labels and geographic/environmental records.
The repository contains the complete image archives for the… See the full description on the dataset page: https://huggingface.co/datasets/minute1028/forestllava-dataset.MASH
MASH: A Multiplatform and Multimodal Annotated Dataset for Societal Impact of Hurricane
We present a Multiplatform Annotated Dataset for Societal Impact of Hurricane (MASH) that includes 59,607 relevant social media data posts from Reddit, TikTok, and YouTube.
In addition, all relevant posts are annotated on three dimensions: Humanitarian Classes, Bias Classes, and Information Integrity Classes in a multi-modal approach that considers both textual and visual content (text, images… See the full description on the dataset page: https://huggingface.co/datasets/YRC10/MASH.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.osm-europe-1k
OSM-Europe-1k
A 1,000-image street-level geolocation benchmark for Europe, sampled from
the OpenStreetView-5M (OSV-5M)
test split. Intended as a contamination-free, openly-licensed reference set
for evaluating image→GPS models. Companion benchmark to a master's thesis at
FH JOANNEUM (Florian Leber, 2026).
What's in this repo:
The 1,000 OSM/Mapillary image bytes are bundled directly under
images/ (66 MB) — re-distribution is allowed by the upstream
CC-BY-SA 4.0 license, with… See the full description on the dataset page: https://huggingface.co/datasets/lebfla11/osm-europe-1k.footwork-detection-keypoints
Footwork Detection Keypoints Dataset
Dataset Description
This dataset was created from scratch for research and development in automated footwork detection and tactical analysis using computer vision and machine learning.
Unlike datasets collected from existing public benchmarks, this dataset was specifically constructed and organized by the authors for the footwork detection task.
Dataset Creation
The dataset was collected, processed, and annotated… See the full description on the dataset page: https://huggingface.co/datasets/Pranathi196/footwork-detection-keypoints.iNaturalist_v2
Dataset Card for Dataset Name
This dataset is comprised of 1,079 observations that were posted on the iNaturalist app. iNaturalist is a website and mobile app that 'aims to
provide a crowd-sourced identification system' for plants, insects, and animals.
Dataset Details
Dataset Description
For each of the 1,079 observations included in this dataset, there is information about the quality of the associated image (quality_grade), a species label… See the full description on the dataset page: https://huggingface.co/datasets/ba188/iNaturalist_v2.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/pranuthysri/MM-Food-100K.humanoid-basic-actions-dataset-v1
Humanoid Basic Actions Dataset v1
Synthetic dataset for humanoid robot training simulation.
Description
This dataset contains labeled humanoid robot action images for basic movement recognition tasks.
Classes
walk
run
sit
stand
wave
pick_object
turn_left
turn_right
Structure
dataset/
├── train/
├── validation/
Each folder contains subfolders named after action labels.
Format
Image Classification (RGB Images 224x224)
Total… See the full description on the dataset page: https://huggingface.co/datasets/Caplin43/humanoid-basic-actions-dataset-v1.CleanPatrick
CleanPatrick: A Benchmark for Data Cleaning
Welcome to CleanPatrick, the first large-scale benchmark designed for data cleaning in the image domain.
Built on the Fitzpatrick17k dermatology dataset, CleanPatrick is a dataset for measuring the performance in detecting three major data quality issues:
off-topic samples, near-duplicates, and label errors.
Overview
CleanPatrick consists of dermatological images annotated with over 500,000 binary labels across three… See the full description on the dataset page: https://huggingface.co/datasets/akshanshmittal12/CleanPatrick.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/nyotxnyot/MM-Food-100K.europe-holdout-2k
Europe-Holdout-2k
A 2,000-location street-level geolocation benchmark sampled from the
held-out test fold of the thesis training pipeline. Designed as a
high-variation, contamination-free probe for the published thesis models
(v14 unfreeze_last2, v15, ...) and any external geolocation system.
Locations
2,000
Region
Europe (42 countries)
Source
seed=42 location-level 80/10/10 split of the thesis training corpus
Imagery
Coordinates only — Google Street View bytes… See the full description on the dataset page: https://huggingface.co/datasets/lebfla11/europe-holdout-2k.INVOICE_ANNOTATION_V1MM-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/chinnawat2424/MM-Food-100K.cifar10-stats
CIFAR-10 CNN Layerwise Training Statistics
Dataset Description
This dataset contains layer-wise training statistics for a convolutional network trained on CIFAR-10, together with the corresponding test/acc.
Each row is one point at loss landscape. The features are computed on the last training batch of 1024 samples before the end of an epoch, and test/acc is measured immediately after that epoch.
The dataset includes statistics for several convolutional layers and the… See the full description on the dataset page: https://huggingface.co/datasets/Fullfix/cifar10-stats.sat-captchas-v1
SAT Captchas V1
This dataset archive contains CAPTCHA images from the SAT CFDI verification flow targeted by the sat-captcha-solver project.
Release Context
As of the morning of March 25, 2026, the specific CAPTCHA targeted by this project had been deprecated. That deprecation is the reason the related code and this dataset archive were made public.
Contents
images.tar: archive containing the CAPTCHA image files under images/
labels.csv: filename-to-label… See the full description on the dataset page: https://huggingface.co/datasets/Thermostatic/sat-captchas-v1.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/jaisal228/MM-Food-100K.urban-scenes-v2
Urban Scenes – Preprocessing Utilities
This repository contains helper scripts used during preprocessing and validation
of the Urban Scenes v2 dataset.
Contents
preprocess.py – feature normalization utilities
stats.ipynb – exploratory statistics
label_map.json – class label mapping
Notes
Raw data is not included due to licensing constraints.
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/AbbyTan/MM-Food-100K.