Datasets

Dataset Card for "rotten_tomatoes" Dataset Summary Movie Review Dataset. This is a dataset of containing 5,331 positive and 5,331 negative processed sentences from Rotten Tomatoes movie reviews. This data was first used in Bo Pang and Lillian Lee, ``Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales.'', Proceedings of the ACL, 2005. Supported Tasks and Leaderboards More Information Needed Languages… See the full description on the dataset page: https://huggingface.co/datasets/cornell-movie-review-data/rotten_tomatoes.

Dataset Card for Office-Home This is a FiftyOne dataset with 15588 samples. 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 = fouh.load_from_hub("Voxel51/Office-Home") # Launch the App session = fo.launch_app(dataset) Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Office-Home.

Horama/animal-200 Raw wildlife image collection covering 199 species (mammals, birds, reptiles), scraped from multiple web sources. Images are organized by species folder and can be used as-is for image classification (species identification) or as input for downstream annotation pipelines (object detection, etc.). For animal detection, see Horama/animal-200-detection dataset. Sources Images were collected from three web sources using dedicated scrapers: Source… See the full description on the dataset page: https://huggingface.co/datasets/Horama/animal-200.

-- 2nd International Chinese Word Segmentation Bakeoff - Data Release Release 1, 2005-11-18 Introduction This directory contains the training, test, and gold-standard data used in the 2nd International Chinese Word Segmentation Bakeoff. Also included is the script used to score the results submitted by the bakeoff participants and the simple segmenter used to generate the baseline and topline data. File List gold/ Contains the gold standard… See the full description on the dataset page: https://huggingface.co/datasets/zeroMN/hanlp_date-zh.

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.

LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text. This dataset consists of twenty different tasks, covering key long-text application scenarios such as multi-document QA, single-document QA, summarization, few-shot learning, synthetic tasks, and code completion.

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.

Papas Nativas Peruanas — 83 Variedades (UNSAAC 2024) Colección de imágenes de 83 variedades de papas nativas peruanas para clasificación visual mediante modelos de visión computacional. Descripción del dataset Dataset recopilado de forma colaborativa por estudiantes de Ingeniería Informática de la Universidad Nacional de San Antonio Abad del Cusco (UNSAAC) en el curso de Aprendizaje Automático (2024). Las imágenes fueron capturadas en condiciones variadas (distintos… See the full description on the dataset page: https://huggingface.co/datasets/ayayon/papas-nativas-peru-83-variedades.

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.

Architectural Styles Dataset (Curated and Extended) Dataset Summary A curated and extended version of dumitrux's Architectural Styles Dataset. The original dataset covered 25 architectural styles; 630 images were removed by automated filters (duplicates, low-resolution), leaving 9,483 images. A 26th class, Brutalism, was added from 284 manually curated Wikimedia Commons photographs, bringing the total to 9,767 images across 26 classes. Intended use: training and… See the full description on the dataset page: https://huggingface.co/datasets/axel-riben/arcdataset-brutalism-extension.

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.