farsi-asr/ganjoor-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset

This dataset was created by SeshuRaju 🧘‍♂️

Released under CC0: Public Domain

Contents

midooy/RDRF-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

VLM-3R Training Data

Training QA data for VLM-3R: vsibench_train/ (VSI-Bench-style tasks) and vstibench_train/ (VSTI-Bench tasks over ScanNet train split).

  Erratum (2026-07-13): corrected camera-position ground truth

A bug in the QA generation pipeline (reported by Jacob Yeung, CMU) extracted the camera center from camera-to-world poses using -R.T @ t instead of pose[:3, 3]. Answers in five vstibench_train files depended on the camera's world position and have… See the full description on the dataset page: https://huggingface.co/datasets/Journey9ni/VLM-3R-DATA.

Digital Caps'ule Memories

## Overview

Digital Caps'ule Memories is a dataset for object detection tasks - it contains Beer Bottle Caps annotations for 248 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The Allen Brain Observatory – Visual Coding is a large-scale, standardized survey of physiological activity across the mouse visual cortex, hippocampus, and thalamus. It includes datasets collected with both two-photon imaging and Neuropixels probes, two complementary techniques for measuring the activity of neurons in vivo. The two-photon imaging dataset features visually evoked calcium responses from GCaMP6-expressing neurons in a range of cortical layers, visual areas, and Cre lines. The Neuropixels dataset features spiking activity from distributed cortical and subcortical brain regions, collected under analogous conditions to the two-photon imaging experiments. We hope that experimentalists and modelers will use these comprehensive, open datasets as a testbed for theories of visual information processing.

COCO-Counterfactuals is a high quality synthetic dataset for multimodal vision-language model evaluation and for training data augmentation. Each COCO-Counterfactuals example includes a pair of image-text pairs; one is a counterfactual variation of the other. The two captions are identical to each other except a noun subject. The two corresponding synthetic images differ only in terms of the altered subject in the two captions. In our accompanying paper, we showed that the COCO-Counterfactuals dataset is challenging for existing pre-trained multimodal models and significantly increase the difficulty of the zero-shot image-text retrieval and image-text matching tasks. Our experiments also demonstrate that augmenting training data with COCO-Counterfactuals improves OOD generalization on multiple downstream tasks.

The dataset includes following fields: (Food) Item, Category, Sub Category, Item Name, Price, Cost. The purpose of this dataset is to practice data visualization in tools like power bi and python.

joekaw/test-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

Global Football (Soccer) Data Lake

Cleaned, deduplicated, quality-gated football match data for BTTS / goals modelling. Sources: API-Football + football-data.co.uk. Pipeline & docs: https://github.com/eatpizzanot/soccer-dataset

673,966 fixtures (644,901 played), 271 leagues, 11,104 teams, 2008-06-07 - 2027-06-06. BTTS base rate 0.5063. xG fake-zeros removed; known_at leakage guard; 12-dimension QA gate (QUALITY_REPORT.md).

Caveats: league history is uneven — check… See the full description on the dataset page: https://huggingface.co/datasets/eatpizzanot/soccer-dataset.

Overview

This dataset provides real skeletal radiographs sampled from the FracAtlas dataset (Abedeen et al., Scientific Data 2023, doi: 10.1038/s41597-023-02932-1, CC BY 4.0), one of the largest publicly available collections of annotated bone X-rays.

The dataset includes images across multiple skeletal regions. It is designed to challenge models in identifying whether a fracture is present from medical imaging.

Source Dataset

Dataset Structure

The raw downloaded artifact contains the following structure:

images/ folder:- 4,083 images in two subdirectories: Fractured/ (717 images) and Non_fractured/ (3,366 images)
Original resolution varies; resized to ≤384px PNG during processing

Annotations/ folder:- Contains detailed fracture bounding box and polygon annotations in multiple formats: COCO JSON/, PASCAL VOC/, VGG JSON/, and YOLO/. (Note: This challenge focuses on image-level multi-task classification and does not evaluate bounding box metrics).

Utilities/ folder:- Contains helper notebooks (coco2yolo.ipynb, yolo2voc.ipynb) and metadata for standard dataset splits (Fracture Split/) dataset.csv | Column | Data Type | Description | |:---|:---|:---| | image_id | String | Original filename (e.g., IMG0000019.jpg) | | hand, leg, hip, shoulder | Integer (0/1) | One-hot anatomical region encoding | | mixed | Integer (0/1) | Mixed anatomical regions | | hardware | Integer (0/1) | Orthopedic hardware visible | | multiscan | Integer (0/1) | Multiple views in single image | | fractured | Integer (0/1) | Binary fracture label | | fracture_count | Integer | Number of visible fractures | | frontal, lateral, oblique | Integer (0/1) | X-ray projection type |

Notes

The images are real, down-sampled radiographs.
The splits generated in the public dataset correspond strictly to standard diagnosis workflows, mapping visual radiograph properties to human-readable radiology impressions.

Addv2_v1

## Overview

Addv2_v1 is a dataset for object detection tasks - it contains Can Foam Plastic Plasticbottle U YgPQ annotations for 1,461 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset contains the digitized treatments in Plazi based on the original journal article Skoracka, Anna, Shi, Aoxiang, Pacyna, Anna (2001): New eriophyoid mites (Acari: Eriophyoidea) associated with grasses from Mongolia. Zootaxa 9: 1-18, DOI: 10.5281/zenodo.4620032

Abstract

Two new species, Aculodes mongolicus sp. n. from Hordeum brevisubulatum (Trin.) Link, Eriophyes bromusi sp. n. from Bromus inermis Leyss, are described from Mongolia. Four new records of eriophyoid mites collected from grasses in Mongolia are also presented.

Key words: Aculodes mongolicus, Eriophyes bromusi, Eriophyoidea, grasses, Mongolia, taxonomy

Food safety practices play a crucial role in the prevention of foodborne diseases, particularly in low- and middle-income countries like Bangladesh. This study assessed food safety practices among household food handlers in Patuakhali, Bangladesh, and identified associated factors influencing these practices. A cross-sectional study was conducted among 300 randomly selected households, using structured interviews and direct observations. The findings revealed that only 46% of participants demonstrated good food safety practices, with notable deficiencies in proper handwashing techniques (36.7%). Multiple logistic regression analysis identified that secondary education (AOR = 2.84; 95% CI: 1.44, 5.59), government employment (AOR = 5.74; 95% CI: 1.24, 26.53), monthly income between 15,000 and 30,000 BDT (AOR = 4.50; 95% CI: 2.17, 9.31), and participation in food safety training (AOR = 5.01; 95% CI: 1.95, 12.90) were significantly associated with good food safety practices. Conversely, living in rural areas (AOR = 0.30; 95% CI: 0.13–0.67) and, being aged 39–58 years (AOR = 0.36; 95% CI: 0.15–0.84) were associated with poor food safety practices. Addressing these factors, particularly socioeconomic disparities and offering targeted food safety education, could significantly improve public health outcomes and overall food safety practices.

Chaves County School Employees location dataset — United States subset. Verified addresses, coordinates, and phones. Licensed via CREHQ Data Store.

This dataset contains the digitized treatments in Plazi based on the original journal article Braganca, Pedro H. N., Zeeventer, Ryan M. van, Bills, Roger, Tweddle, Denis, Chakona, Albert (2020): Diversity of the southern Africa Lacustricola Myers, 1924 and redescription of Lacustricola johnstoni (Guenther, 1894) and Lacustricola myaposae (Boulenger, 1908) (Cyprinodontiformes, Procatopodidae). ZooKeys 923: 91-113, DOI: http://dx.doi.org/10.3897/zookeys.923.48420, URL: http://dx.doi.org/10.3897/zookeys.923.48420

The development plan (BPL) contains the legally binding stipulations for the urban development order. In principle, the development plan must be developed from the land use plan. The available data are the development plan ‘Bei der Schule, 1st Amendment’ of the municipality of Bretzfeld from XPlanung 5.0. Description: Development Plan At School, 1st Amendment.

Mgallery Hotel Collection location dataset — Taiwan subset. Verified addresses, coordinates, and phones. Licensed via CREHQ Data Store.

The application of Artificial Intelligence (AI) has been evident in the agricultural sector recently. The main goal of AI in agriculture is to improve crop yield, control crop pests/diseases, and reduce cost. The agricultural sector in developing countries faces severe in the form of disease and pest infestation, the knowledge gap between farmers and technology, and a lack of storage facilities, among others. To help address some of these challenges, this work presents crop pests/disease datasets sourced from local farms in Ghana. The dataset is presented in two folds; the raw images which consists of 24,881 images ( 6,549-Cashew, 7,508-Cassava, 5,389-Maize, and 5,435-Tomato) and augmented images which is further split into train and test set consists of 102,976 images (25,811-Cashew, 26,330-Cassava, 23,657-Maize, and 27,178-Tomato), categorized into 22 classes. All images are de-identified, validated by expert plant virologists, and freely available for use by the research community.

Local dataset • Reachy Mini Moves

Community-contributed Marionette recordings captured on Reachy Mini.

Moves uploaded: 1 Total motion time: 10.0 seconds Audio tracks: 0 Last updated: 2026-08-07T05:04:46Z

Files live under data/ — each move ships as a JSON trajectory (Reachy Mini emotions schema) plus an optional WAV recorded directly from the robot.

  How this dataset was produced

These takes were recorded with the Marionette Reachy Mini app. Pick the moves to… See the full description on the dataset page: https://huggingface.co/datasets/ninadpchaudhari/local-dataset.