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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
16,121 datasets
LUNA16 YOLO Dataset v4 is a computer vision dataset derived from the Lung Nodule Analysis 2016 challenge. It likely contains CT scan images with bounding box annotations formatted for the YOLO object detection framework. The dataset is hosted on Kaggle, but its specific scale, creation date, and author are not detailed in the provided metadata.
Brawl_System_Yolo11 is a dataset published on Kaggle. The title suggests it contains images for training or evaluating object detection models, likely using the YOLOv11 architecture. No further metadata regarding size, source, or creation date is available.
Singpath-CytoText is a cervical cytology image dataset with structured pathological descriptions and annotations. Each image includes a bounding box for an anchor cell, a structured description of nuclear features, a natural language caption, and a final cytological label. The dataset was created by zqiu96 and was last updated on the Hugging Face platform in February 2026.
Canada is the geographic focus of this dataset, which appears to contain imagery for semantic segmentation tasks related to tornado damage. The dataset likely contains images with pixel-level annotations for identifying fallen trees. It was published on Kaggle, but details on the author, organization, and collection date are unknown.
Derived from the action-value data released with DeepMind's 'Grandmaster-Level Chess Without Search' paper, this dataset reorganizes chess positions and their legal moves. It provides per-move win probabilities and augments decisive moves with Stockfish-calculated mate depths. The dataset was created by Ramora0 and last updated on Hugging Face on February 6, 2026.
best_NO_pgd_PER_SEGMENT_MITBIH_GAN_modelV2 is a dataset hosted on Kaggle. The title suggests it contains ECG signal segments, likely derived from the MIT-BIH arrhythmia database. The dataset appears to involve a Generative Adversarial Network (GAN) model.
Kaggle hosts a dataset of dental X-ray images formatted for YOLO object detection models. The collection is described as balanced across four distinct classes, though the specific classes are not detailed in the minimal metadata. The dataset's author, organization, and collection date are unknown.
Malnutrition Image datasets is a collection of image data hosted on Kaggle. The dataset's specific content, scale, and provenance are not detailed in the available metadata. Its intended use likely involves computer vision tasks related to health and nutrition.
LISC-GAN is a dataset hosted on Kaggle. The title suggests it contains data related to Generative Adversarial Networks, a machine learning model for generating synthetic images. No further details on its size, creator, or update history are available from the provided metadata.
Twenty water samples collected from five sites along the River Wyre in northwest England measure dissolved polycyclic aromatic hydrocarbons (PAHs) and dissolved organic carbon (DOC). Data includes concentrations of freely dissolved PAHs, total dissolved PAHs, estimated DOC-associated fractions, and calculated DOC-water partition coefficients. Samples were gathered from August 2010 to June 2011.
Environmental Information Data Centre provides concentrations of dissolved organic carbon, inorganic carbon, CO2, CH4, and N2O from the Black Burn stream draining a Scottish peatland. Measurements were taken weekly to fortnightly from approximately 2006 to present at sites adjacent to drain blocking interventions. Data collection was initiated by a University of Edinburgh masters project and continued by the Centre for Ecology & Hydrology.
British predatory bird monitoring data contains concentrations of Persistent Organic Pollutants and mercury in merlin and golden eagle egg contents. The Predatory Bird Monitoring Scheme records the year, region of collection, and egg shell index for each sample to track contaminant variations across species, regions, and time.
Bioassay experiments from 25 river sites across Great Britain investigate phytoplankton growth responses to inorganic and organic nutrient additions. The dataset includes calculated growth responses and background nutrient concentrations measured concurrently at the sites.
This repository provides 8 pre-trained model assets and weights for the ReActor face swap extension, maintained by Gourieff and updated in March 2026. The collection includes specialized files for face detection, swapping, and restoration, such as InsightFace and GFPGAN weights. It serves as the central asset hub for ComfyUI and Stable Diffusion web UI integrations.
Aurora Australis collected 1993 temperature measurements in the Tasman Sea using expendable bathythermographs (XBTs). Data was submitted to the NOAA National Centers for Environmental Information by CSIRO for XBT/CTD instrument comparisons. The dataset contains vertical temperature profiles from a single austral research voyage.
Polychaete worm records from the Admiralty Bay benthos database document Antarctic marine biodiversity. The dataset contains species occurrence information for the Southern Ocean, compiled by the SCIOPS organization. Data collection was focused on the period from 1979 to 1980.
A database records benthic polychaete worm species diversity in Admiralty Bay, King George Island. The dataset was compiled by the SCIOPS organization from fieldwork conducted during the 1979-1980 Antarctic seasons. It was last updated in the system in 1986.
A training dataset for optical character recognition of the Sinhala script. It contains line-level images paired with corresponding ground truth text. The dataset was sourced from Kaggle, but details on its creator, size, and collection date are unknown.
YOLO11 is a dataset published on Kaggle. The dataset's content and scale are not described in the provided metadata. Its author, organization, and specific creation details are unknown.
A Kaggle dataset providing extracted visual features for video question answering tasks. The title suggests the features are derived from object detection models GDINO and FRCNN, likely for causal reasoning in videos. The dataset's specific content, scale, and origin require verification after download.