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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
17,713 datasets
Medigan is a Python-based collection of pretrained generative models for medical image synthesis developed by RichardObi and updated in July 2024. It provides a toolbox for generating synthetic data across modalities including MRI, endoscopy, and radiology using Generative Adversarial Networks (GANs).
NYUv2 provides a multimodal dataset for indoor scene understanding tasks. Each sample includes an 'image', 'segmentation', 'depth', 'normal', and synthetically generated 'noise'. The dataset was uploaded by tanganke to Hugging Face on June 6, 2024, and is split into 'train' and 'val' sets.
FLAIR is a large labelled image dataset designed for benchmarking in federated learning. It was published at NeurIPS 2022 by Apple and captures characteristics encountered in federated learning scenarios. The dataset was last updated on the Hugging Face platform on 2024-05-27.
421,200 simulated Atomic Force Microscopy images for 1,755 organic molecules, each with 24 3D image stacks at 256x256 pixel resolution. This dataset was created by Quasar Science Resources S.L. and the Universidad Autónoma de Madrid's SPMTH group, with a last update recorded on 2024-05 05. It includes molecular depictions, IUPAC names, formulas, coordinates, and atom height maps.
UzCrawl contains web and Telegram crawl materials from nearly 1.2 million unique sources in the Uzbek language. The dataset is updated to March 2024 and was created to support research on low-resource languages. It is a large-scale text corpus assembled by the author tahrirchi.
Organizational structure of the DEPARTMENT FOR THE PROTECTION OF BORN WORK, CIVIL PROTECTION AND COMMUNICATION WITH RIGHT ORGANS OF POLTAV REGIONAL STATE ADMINISTRATION. The dataset was last updated on June 11, 2024, and originates from the States site of Ukraine.
CommonCatalog CC-BY-SA is a collection of high-resolution Creative Commons images sourced from Yahoo Flickr users in 2014. It contains approximately 100 million images with synthetic captions. The dataset was created by the common-canvas organization.
327,680 color images extracted from histopathologic scans of lymph node sections form a benchmark for machine learning. Each 96x96 pixel image is annotated with a binary label indicating the presence of metastatic tissue. The dataset, created by 1aurent and last updated on Hugging Face in May 2024, is designed to be trainable on a single GPU.
A register listing open datasets owned by the organizational department of the Shostka City Council. The dataset was published on the States site of Ukraine and last updated on 2024-06-11. It is available for download in the EXCEL XLSX file format.
NWPU VHR-10 is a ten-class geospatial object detection dataset containing 800 very-high-resolution optical remote sensing images. The dataset was created by the Northwestern Polytechnical University, with 715 color images from Google Earth and 85 pansharpened color infrared images from Vaihingen data. It was mirrored to Hugging Face by the user 'satellite-image-deep-learning' in May 2024.
100 million high-resolution Creative Commons images collected from Yahoo Flickr users in 2014. The dataset contains images of up to 4k resolution, making it one of the highest resolution captioned image collections available. It was created by common-canvas and last updated on HuggingFace in May 2024.
108,754 images across 397 scene categories, with at least 100 images per category. The dataset is a subset of the SUN database, created for research purposes by tanganke and last updated on Hugging Face in May 2024.
25,000 images containing over 40,000 people with annotated body joints form this benchmark for articulated human pose estimation. The dataset was systematically collected using a taxonomy of everyday human activities, covering 410 distinct activity labels, and each image was extracted from a YouTube video. It is hosted on Hugging Face by Voxel51 and was last updated in May 2024.
Far infrared images collected from a vehicle driven in outdoor urban scenarios. The dataset was manually annotated with pedestrian bounding boxes and is divided into a classification subset with rescaled images and a detection subset with original images. It was authored by Daniel Olmeda and last updated on May 5, 2024.
Radial growth data for Fagus sylvatica, Quercus petraea, and Quercus pyrenaica trees sampled in El Hayedo de Montejo, measured with 0.01 mm precision. The dataset includes tree perimeters from 2018 and estimated competition metrics, in basal area (m2/ha), for adjacent trees from 1994 to 2015. It supports research on the relative importance of stand density and climate change on observed growth decline.
22,176 facial images featuring 11-class pixel-level semantic segmentation masks and 106-point facial landmarks. The collection includes significant variations in pose, expression, and occlusion to facilitate research in fine-grained face parsing.
A 2024-05-02 updated image dataset for vehicle recognition, uploaded to HuggingFace by tanganke. It contains 8,144 training images and 8,041 test images, with additional test splits for robustness evaluation. The splits include images with high contrast, Gaussian noise, impulse noise, JPEG compression, and motion blur.
NREL's Photovoltaic Rooftop Database provides geospatially-resolved estimates of suitable roof surfaces and their solar technical potential. The dataset covers 128 metropolitan regions in the United States, organized by city and year of lidar collection. It includes five geospatial layers per city-year, such as building footprints, developable planes, and technical potential estimates.
12,000+ Vietnamese-language questions and symptoms categorized into medical domains such as cardiovascular, digestive, and neurological health. The collection facilitates the development of symptom classification models and preliminary disease identification tools specifically for Vietnamese speakers.
QUAM-AFM is a dataset of 165 million simulated Atomic Force Microscopy images generated from 685,513 organic molecules. The dataset was created by Quasar Science Resources S.L. and the SPMTH Research Group at Universidad Autónoma de Madrid, funded by the Comunidad de Madrid, and was last updated in May 2024. It includes 24 3D image stacks per molecule, each with 10 tip-sample distances, plus molecular depictions, IUPAC names, and atomic coordinates.