Datasets

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.

Dataset Card for Dataset Name Homepage: https://hazyresearch.stanford.edu/legalbench/ Repository: https://github.com/HazyResearch/legalbench/ Paper: https://arxiv.org/abs/2308.11462 Dataset Description Dataset Summary The LegalBench project is an ongoing open science effort to collaboratively curate tasks for evaluating legal reasoning in English large language models (LLMs). The benchmark currently consists of 162 tasks gathered from 40… See the full description on the dataset page: https://huggingface.co/datasets/nguha/legalbench.

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

GroMo25: Multiview Time-Series Plant Image Dataset for Age Estimation and Leaf Counting Dataset Summary GroMo25 is a multiview, time-series plant image dataset designed for plant age estimation (in days) and leaf counting tasks in precision agriculture. It contains high-quality images of four crop species — Wheat, Okra, Radish, and Mustard — captured over multiple days under controlled conditions. Each plant is photographed from 24 angles across 5 vertical levels per day… See the full description on the dataset page: https://huggingface.co/datasets/MrigLabIITRopar/GroMo25.

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.

Dataset Card for MVTec AD This dataset originates from MVTec but is provided in a different format. You can easily load it using FiftyOne The total number of samples remains the same as the original: 5,354. 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 'max_samples', etc dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/mvtec-ad.

Dataset Card for DASP Dataset Description The DASP (Distributed Analysis of Sentinel-2 Pixels) dataset consists of cloud-free satellite images captured by Sentinel-2 satellites. Each image represents the most recent, non-partial, and cloudless capture from over 30 million Sentinel-2 images in every band. The dataset provides a near-complete cloudless view of Earth's surface, ideal for various geospatial applications. Images were converted from JPEG2000 to JPEG-XL to… See the full description on the dataset page: https://huggingface.co/datasets/RichardErkhov/DASP.

Stanford Cars Dataset Dataset Overview Splits: Training: 8144 images used for model training. Test: 8041 images used for evaluation. Contrast: 8041 images with high contrast for robustness testing. Gaussian Noise: 8041 images corrupted by Gaussian noise for robustness testing. Impulse Noise: 8041 images corrupted by impulse noise for robustness testing. JPEG Compression: 8041 compressed images for robustness testing. Motion Blur: 8041 images with motion blur for… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/stanford_cars.