Datasets

Dataset Card for OpenFake OpenFake is a dataset and benchmark for detecting AI-generated images, with a focus on politically and socially salient content where misinformation risk is highest. It pairs real photographs with synthetic counterparts produced by a wide range of frontier proprietary generators, open-source diffusion models, and community fine-tunes. A separate in-the-wild test set is sourced from Reddit to evaluate detector performance on naturally circulated synthetic… See the full description on the dataset page: https://huggingface.co/datasets/ComplexDataLab/OpenFake.

RSCD: Road Surface Condition Dataset Dataset Description The Road Surface Condition Dataset (RSCD) is a large-scale image dataset containing over 1 million images for road surface condition classification. This dataset is designed for training computer vision models to identify and classify various road surface types, moisture conditions, and damage severity levels. Dataset Summary Total Images: ~1,028,000 images Image Format: JPG Use Cases: Road condition… See the full description on the dataset page: https://huggingface.co/datasets/rezzzq/RSCD-1million.

Military Aircraft Detection Dataset Military aircraft detection dataset in COCO and YOLO format. This dataset is synchronized from the original Kaggle dataset:https://www.kaggle.com/datasets/a2015003713/militaryaircraftdetectiondataset

MR-RATE: A Vision-Language Foundation Model and Dataset for Magnetic Resonance Imaging This is the MR-RATE-coreg repository, part of the MR-RATE dataset release. It contains co-registered MRI volumes in which all imaging volumes within each study have been spatially aligned to a common T1-weighted reference frame. For full dataset details, native-space MRI volumes, radiology reports, metadata, and data splits, please… See the full description on the dataset page: https://huggingface.co/datasets/Forithmus/MR-RATE-coreg.

Dataset Card for Fish-Visual Trait Analysis (Fish-Vista) Note that the '</Use this dataset>' option will only load the CSV files. To download the entire dataset, including all processed images and segmentation annotations, refer to Instructions for downloading dataset and images. See Example Code to Use the Segmentation Dataset Figure 1. A schematic representation of the different tasks in Fish-Vista Dataset. Instructions for downloading dataset… See the full description on the dataset page: https://huggingface.co/datasets/saffatgazi/fish-vista.

Dataset Card for mmla-mpala Dataset Details This is a dataset containing annotated video frames of giraffes, Grevy's zebras, and Plains zebras collected at the Mpala Research Center in Kenya. The dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery. The annotations indicate the presence of animals in the images in YOLO format. The dataset is designed to facilitate research in wildlife… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/mmla_mpala.

FLARE 2026: Multimodal Model for 3D Medical Image Parsing The task is to train one multimodal model for report generation and vision QA. Data Description The dataset contains two subsets for abdomen and lung CT report generation and VQA. FLARE-Task5-MLLM-3D/ ├── README.md ├── train # training set │ ├── CT-AMOS-1290 # source: https://era-ai-biomed.github.io/amos/ │ ├── CT-AMOS-Tr.json │ ├── CT-RATE-2000 # source:… See the full description on the dataset page: https://huggingface.co/datasets/FLARE-MedFM/FLARE26-MLLM-3D.

REPID: Rendering Evaluation of Photographic Image Dataset REPID (officially introduced as the Rendering Evaluation of Photographic Image Dataset) is a large-scale benchmark designed for Image Rendering Quality Assessment (IRQA). Unlike traditional Image Quality Assessment (IQA) which focuses on technical degradations like noise or blur, REPID aims to model subjective human aesthetic preferences for different rendering styles of the same scene. Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/vsevolodpl/REPID.

Dataset Card for Street View House Numbers Dataset Summary SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting. It can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images) and comes from a significantly harder, unsolved, real world problem… See the full description on the dataset page: https://huggingface.co/datasets/ufldl-stanford/svhn.

Dataset Card for MMLA Ol Pejeta Conservancy Dataset Details This is a dataset containing annotated video frames of Plains zebras collected at the Ol Pejeta Conservancy (OPC) in Kenya using the semi-autonomous WildWing system. The dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery. It includes frames from various sessions, with annotations indicating the presence of zebras in the… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/mmla_opc.

PURGE: Partition-Aware Unlearning for Removing Spurious-Correlation Generated Errors PURGE is a partitioning strategy applied to existing public datasets (MSCOCO 2017) that separates object-relevant evidence from spurious background cues in LVLMs. This repository hosts the resulting preprocessed retain/forget partitions for direct reuse. NeurIPS 2026 Evaluations & Datasets Track, Submission #2701. Hosted under an anonymous account for double-blind review; will be transferred… See the full description on the dataset page: https://huggingface.co/datasets/anonnnnnsub/neuripsED_2701.

Tomato Leaves Dataset Overview This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images. Dataset Structure The dataset is organized into three main splits: train validation test… See the full description on the dataset page: https://huggingface.co/datasets/codraja2006/tomato-leaves-dataset.

Agentic Critic Dataset High-quality AIGC images with rich metadata for aesthetic evaluation. Metadata Fields Each entry in metadata.jsonl contains: prompt: Positive prompt negative_prompt: Negative prompt model: Model name and hash sampler: Sampling method steps: Generation steps cfg_scale: CFG scale seed: Random seed stats: Engagement metrics image_path: Relative path to image Usage from datasets import load_dataset dataset =… See the full description on the dataset page: https://huggingface.co/datasets/ChengyouJia/agentic-critic-dataset.

Gilt Posture Recognition Dataset Each RGB image has a matching depth image (same filename, .png extension). YOLO-format label files correspond to each image. 🐷 Annotated Postures Five postures are labeled using YOLO bounding boxes: Class Name Class ID feeding 0 lateral_lying 1 sitting 2 standing 3 sternal_lying 4 📊 Class Distribution Below is a histogram showing the distribution of posture classes across the dataset:… See the full description on the dataset page: https://huggingface.co/datasets/anilbhujel/Gilt_posture_dataset.

Military Aircraft Detection & Classification Dataset 88 Classes with Advanced Background Suppression Overview This dataset is a professionally curated resource for training high-performance object detection and image classification models such as YOLOv11.It contains 88 distinct military aircraft classes and is explicitly designed for real-world deployment, where false positives from civilian aircraft, birds, and small drones are common. To address this, the… See the full description on the dataset page: https://huggingface.co/datasets/Ahnuf/Military_Aircraft_Detection_Classification_Image_Dataset.

IndoLepAtlas — Indian Lepidoptera & Host Plants Dataset A large-scale computer vision dataset of Indian butterflies, moths, and their larval host plants. Sourced from ifoundbutterflies.org with public CC-licensed photographs. Inspired by: iNaturalist | Domain: Indian Wildlife & Biodiversity Dataset Overview Butterflies Host Plants Total Species ~967 ~127 ~1,094 Images ~60,000 ~700 ~60,700 Source ifoundbutterflies.org ifoundbutterflies.org —… See the full description on the dataset page: https://huggingface.co/datasets/Butterfree/IndoLepAtlas.

Dataset Card for "LexGLUE" Dataset Summary Inspired by the recent widespread use of the GLUE multi-task benchmark NLP dataset (Wang et al., 2018), the subsequent more difficult SuperGLUE (Wang et al., 2019), other previous multi-task NLP benchmarks (Conneau and Kiela, 2018; McCann et al., 2018), and similar initiatives in other domains (Peng et al., 2019), we introduce the Legal General Language Understanding Evaluation (LexGLUE) benchmark, a benchmark dataset to evaluate… See the full description on the dataset page: https://huggingface.co/datasets/coastalcph/lex_glue.

Dataset Card for NOAA-ESD-CORAL-Bleaching Classification Dataset v1 Overview For the development of machine learning models to classify coral health, specifically identifying healthy hard coral (CORAL) and bleached hard coral (CORAL_BL).This dataset contains underwater imagery collected by NOAA's Ecosystem Sciences Division (ESD) and other benthic surveys. Labels Label Name Functional Group CORAL Healthy Hard Coral Hard Coral CORAL_BL Bleached… See the full description on the dataset page: https://huggingface.co/datasets/krithik274/NOAA-PIFSC-ESD-CORAL-Bleaching-Dataset.

Dataset Card for FashionMNIST Dataset Summary Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing… See the full description on the dataset page: https://huggingface.co/datasets/zalando-datasets/fashion_mnist.

TorNet-Temporal: Temporal Dual-Pol NEXRAD Radar for Tornado Detection A large-scale dataset of storm-centered NEXRAD WSR-88D radar sequences for tornado detection and prediction, featuring 24-channel dual-polarimetric data across variable-length temporal sequences. Dataset Summary 24,862 storm events from NEXRAD Level-II radar archives (2013-2022) 8-22 consecutive radar scans per event (~4-5 min cadence, ~45-90 min total; median 13 frames) 24 channels: 6 dual-pol radar… See the full description on the dataset page: https://huggingface.co/datasets/deepguess/tornet-temporal.