Small(-ish) datasets for fun and teaching

Common repository for example datasets used by Vega-related projects

Data repository for seaborn examples

This dataset offers a comprehensive collection of images featuring tablet names, perfectly suited for applications like OCR, image classification, and drug recognition. It's neatly organized into 26 folders, one for each letter of the alphabet (A-Z), with each folder containing 100 unique images of tablet names starting with that letter. Additionally, the dataset includes over 10,000 augmented images, derived from the original set using various techniques, significantly boosting the diversity and size of the training pool for more robust machine learning model development.

Tablets can be used to facilitate systematic testing of academic skills. Yet, when using validated paper tests on tablet, comparability between the mediums must be established. In this dataset, comparability between a tablet and a paper version of a basic math skills test (HRT: Heidelberger Rechen Test 1–4) was investigated.

Four of the five samples included in the current study covered a broad spectrum of schools regarding student achievement in mathematics, proportion of non-native students, parental educational levels, and diversity of ethnic background. The fifth sample, the intervention sample in the Apps-project, presented with similar characterstics except on mathematical achievement where they showed lower results.

To examine the test-retest reliability of the tablet versions of HRT and the Math Battery several samples were tested twice on each measure in various contexts. To test the correlation between the paper and tablet version between HRT, the participants were tested on both paper and tablet versions of HRT using a counterbalanced design to avoid potential order effects. This sample is referred to as the Different formats sample. Finally, norms were collected for HRT, the Math Battery and the mathematical word problem-solving measure. This sample (called the Normative sample) was also use to investigate the correlation, or convergent validity, between HRT and Math Battery (third hypothesis).

See article "Tablets instead of paper-based tests for young children? Comparability between paper and tablet versions of the mathematical Heidelberger Rechen Test 1-4" by Hassler Hallstedt (2018) for further information.

The dataset was originally published in DiVA and moved to SND in 2024.

This dataset is about artworks. It has 1 row and is filtered where the art medium is Writing Board (Tablet). It features 13 columns including creation start date, creation end date, width, and height.

Dataset

This dataset was created by Enes Harman

Contents

The Tabla Solo dataset is a parallel corpus comprising time-aligned syllabic scores and audio-recordings of 38 solo tabla compositions. The audio and scores for these recordings is from the instructional video DVD titled Shades of Tabla by Pt. Arvind Mulgaonkar.

A companion page to the paper is here: http://compmusic.upf.edu/ismir-2015-tabla

Introduction

In Hindustani music, tabla is the main rhythm accompaniment (Examples of individual strokes of tabla can be obtained from here). To showcase the nuances of the tāl (the rhythmic framework of Hindustani music) as well as the skill of the percussionist with the tabla, Hindustani music concerts feature a tabla solo. A tabla solo is intricate and elaborate, with a variety of pre-composed forms used for developing further elaborations. There are specific principles that govern these elaborations. Musical forms of tabla such as the thēkā, kāyadā, palatā, ̣ rēlā, pēśkār and gat ̣are a part of the solo performance and have different functional and aesthetic roles in a solo performance. Harmonium or sarangi usually plays the role of a time-keeper in tabla solo performances.

Percussion in Hindustani music is organized and orally transmitted with the use of onomatopoeic mnemonic syllables (called the bōl) representative of the different strokes of tabla. Further, tabla has different stylistic schools called gharānās. The repertoires of major gharānās or schools of tabla differ in aspects such as the use of specific bōls, the dynamics of strokes, ornamentation and rhythmic phrases. But there are also many similarities due to the fact that same forms and same standard phrases reappear across these repertoires.

The Dataset

The syllabic representation for tabla solos provide a meaningful representation for analysis. This dataset uses a such a representation. The dataset comprises audio recordings, scores and time aligned syllabic transcriptions for 38 tabla solo compositions of different forms in tīntāl (a metrical cycle of 16 time units). The compositions are from the instructional video DVD Shades Of Tabla by Pandit Arvind Mulgaonkar, who is among the most renowned contemporary tabla maestros. Out of the 120 compositions in the DVD, we chose 38 representative compositions spanning all the gharānās of tabla (Ajrada, Benaras, Dilli, Lucknow, Punjab, Farukhabad). The dataset contains about 17 minutes of audio with over 8200 syllables.

Audio

The audio is extracted from the DVD video and segmented at the level of compositions from the full audio recording. The audio files are mono wav files, sampled at 44.1 kHz with a bit depth of 16 bits. All audios have a soft harmonium accompaniment.

Annotations

The booklet accompanying the DVD provides a syllabic transcription for each composition. We used Tesseract, an open source Optical Character Recognizer (OCR) engine to convert printed scores to a machine readable format. The scores obtained from OCR were manually verified and corrected for errors, adding the the vibhāgs (sections) of the tāl to the syllabic transcription. A time aligned syllabic transcription for each score and audio file pair was obtained using a spectral flux based onset detector followed by manual correction. The score for each composition has additional metadata describing gharānā, composer and its musical form.

The scores in the booklet consists of 41 different mnemonic syllables that are reduced and mapped to 18 syllables based on the timbral similarity between the syllables. The list of syllables along with their mapping can be found here: Syllable Mappings

Dataset Organization

The dataset consists of set of four files for each composition:

• WAV audio file (*.wav)

• The syllable scores as retrieved from the booklet with the metadata (*.txt)

• Time-aligned non-mapped syllabic score with stroke onset times (*.csv)

• Time-aligned mapped syllabic score with stroke onset times (*.csv)

Possible Uses of the Dataset

The dataset can be used for variety of of MIR tasks such as onset detection, percussion transcription, rhythm and percussion pattern analysis, and tabla stroke modeling.

Using this dataset

If you use the dataset in your work, please cite the following publication:

S. Gupta, A. Srinivasamurthy, M. Kumar, H. A. Murthy, X. Serra. Discovery of Syllabic Percussion Patterns in Tabla Solo Recordings. In Proc. of the 16th International Society for Music Information Retrieval Conference (ISMIR), 2015.

http://hdl.handle.net/10230/25697

We are interested in knowing if you find our datasets useful! If you use our dataset please email us at mtg-info@upf.edu and tell us about your research.

Contact

Ajay Srinivasamurthy
PhD Student, Music Technology Group
Universitat Pompeu Fabra,
Barcelona, Spain
ajays.murthy@upf.edu

Swapnil Gupta
Masters Student, Sound and Music Computing
Universitat Pompeu Fabra,
Barcelona, Spain
suapnilgupta.iiith@gmail.com

Xavier Serra
Head, Music Technology Group
Universitat Pompeu Fabra,
Barcelona, Spain
xavier.serra@upf.edu

http://compmusic.upf.edu/tabla-solo-dataset

Tablet

## Overview

Tablet is a dataset for object detection tasks - it contains Tablet annotations for 428 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).

Context

More than 10 million people worldwide are living with Parkinson's disease. Improving machine learning model which identifies Parkinson's disease will lead to helping patients with early dialogs and reduction of treatment cost.

Content

Handwriting database consists of 62 PWP(People with Parkinson) and 15 healthy individuals. The data was collected in 2009.

Number of instances: 77, Number of attributes: 7

Acknowledgements

Source: https://archive.ics.uci.edu/ml/datasets/Parkinson+Disease+Spiral+Drawings+Using+Digitized+Graphics+Tablet

Citation:

1.Isenkul, M.E.; Sakar, B.E.; Kursun, O. . 'Improved spiral test using digitized graphics tablet for monitoring Parkinson's disease.' The 2nd International Conference on e-Health and Telemedicine (ICEHTM-2014), pp. 171-175, 2014.

2.Erdogdu Sakar, B., Isenkul, M., Sakar, C.O., Sertbas, A., Gurgen, F., Delil, S., Apaydin, H., Kursun, O., 'Collection and Analysis of a Parkinson Speech Dataset with Multiple Types of Sound Recordings', IEEE Journal of Biomedical and Health Informatics, vol. 17(4), pp. 828-834, 2013.

This dataset is about artists. It has 1 row and is filtered where the artworks is Tablet Litho 8. It features 9 columns including birth date, death date, country, and gender.

MLR dataset of KU Leuven cuneiform tablet NP 46 Dataset including the processed results of one Multi-Light Reflectance (MLR) recording + derivates, produced with the KU Leuven Portable Light Dome system >>>CONTENT<<< One inscribed cuneiform tablet, a script from Southwest Asia used in the time period ca. 3500 BCE - 75 AD, a letter dated to the Middle-Assyrian period (1363 BC–912 BCE). Its collection numbers is NP 46, standing for Naster Paul (former professor in Assyriology at KU Leuven and compiler of this collection). The tablet is kept at the KU Leuven, presumably since 1947-1948. >>>PUBLICATION<<< The digital assets of the cuneiform tablet in the dataset has been used for the published study: Hameeuw, Hendrik 2012: "1947: Two Tablets as a Christmas Gift to a Leuven Assyriologist", in: T. Boiy et al. (eds), The Ancient Near East, A Life! Festschrift Karel Van Lerberghe (Orientalia Lovaniensia Analecta 220), Leuven, 268-277. see also: https://limo.libis.be/primo-explore/fulldisplay?docid=LIRIAS1815979&context=L&vid=Lirias&search_scope=Lirias&tab=default_tab&lang=en_US >>>THE DATASET<<< (1) RAW, source image set (in recordings folder, 260 .pnm files for each of the 6 recorded sides) + processed results (.csp files, in relightings folder) of a Multi-Light Reflectance (MLR) acquisition and digitizing procedure as obtained with the Portable Light Dome system (2) Final processed results (based on data in (1)), i.e. interactive relightable .cun file (including for each tablet all recorded sides) (3) Derivate 3D models based on the data in the .cun files (in folder '3Ds', .ply, .pgm & .hdr files) (4) Derivate JPG raster images based on the data in the .cun file: ° color: .jpg file with color information and simulating one static condition how raking light interacts on the surface, each time on all recorded sides ° shaded: .jpg file without color information and simulating one static condition how raking light interacts on the surface, each time on all recorded sides ° sketch: .jpg file using the information of the surface orientations to accentuate rapid variations in the relief, each time on all recorded sides (5) Derivates based on the 3D models (.ply), see (3): ° 3D-radiance scaling: .jpg file with radiance scaling render shader and simulating one static condition how raking light interacts on the surface, each time on all recorded sides ==> the .cun file can be consulted via https://www.heritage-visualisation.org/viewer/ >>>DATA ACQUISITION<<< Recordings by Hendrik Hameeuw at KU Leuven: August 2009 & September 2010 >>>PROCESSING<<< The Multi-Light reflectance dataset: with 'PLDdigitize.exe' by ESAT/VISICS at KU Leuven Derivates of the Multi-Light Reflectance dataset: 'PLDviewer.exe' by ESAT/VISICS at KU Leuven; GIMP GNU Image Manipulation; Adobe Photoshop; Meshlab

You can query the relevant information of the input capsule tablet food which has been inspected, registered and approved by the Ministry of Health and Welfare through this dataset.

ID: AO 17199 Object type: tablet Material: clay Measurements: ? Provenience: Ugarit (mod. Ras Shamra) Period/Date: Middle Babylonian (c. 1400-1100 BCE) Language: Sumerian, Akkadian Genre: lexical (ur5-ra, wooden objects) Museum/Collection: Louvre Museum, Paris, France CDLI: P332930

ID: AO 7054 Object type: tablet Material: clay Measurements: ? Provenience: Kanesh (mod. Kültepe) Period/Date: Old Assyrian (c. 1950-1850 BCE) Language: Akkadian Genre: letter Museum/Collection: Louvre Museum, Paris, France CDLI: P357340

Since January 2011, our country has implemented the "domestic vitamin tablet-shaped and capsule-shaped food inspection and registration." According to the regulations announced by the Ministry of Health and Welfare on February 12, 2018, for domestically produced tablet-shaped (referring to the production process through the tabletting step) and capsule-shaped food containing any vitamin, the daily intake falls within the scope of the criteria for the "standards for the identification of domestic vitamin tablet-shaped, capsule-shaped food subject to inspection and registration", then inspection and registration must be carried out, and production, manufacturing, sales, and circulation are allowed only after obtaining inspection and registration permits.

This Dataset contains year and district wise received, unusable and distributed stock data for all the indicators related to Family Planning, Maternal Health, and Immunization under HMIS for Maharashtra

This study is divided in 2 parts. Part 1a is being conducted to evaluate the safety, tolerability, and relative bioavailability of the 2 free base tablet formulations (roller compacted [RC] and high shear wet granulation [HSWG]) compared to the reference capsule formulation under fasted conditions. This is a 3-period; cross-over study that will guide which gepotidacin formulation will be used for future studies. Following review of pharmacokinetic (PK) and safety data in Part 1a, a decision will be made whether to proceed with Parts 1b and 2.

Part 1b is a 2-period, cross-over study and will assess the effect of food on the PK of the selected gepotidacin tablet formulation from Part 1a. In Part 2, the PK of the selected gepotidacin tablet formulation from Part 1a in Japanese (2a) and Chinese (2b) subjects will be evaluated under fasted conditions.

The duration of the study (from Screening to the Follow-up visit) will be approximately 44 days (Part 1a), 41 days (Part 1b) and 38 days (Part 2a and 2b each), respectively. The approximate number of subjects enrolled in Part 1a will be 27 (9 subjects in each of the 3 treatment sequences), 16 in Part 1b (8 subjects in each of the 2 treatment sequences) and 12 Japanese and 12 Chinese subjects in Part 2a and 2b, respectively.

Dataset - Writing Board (Tablet) in the news

BB-MAS is a behavioural biometrics dataset. It consists of data collected from 117 subjects for typing (both fixed and free text), gait (walking, upstairs and downstairs) and touch on Desktop, Tablet and Phone. The dataset consists a total of about: 3.5 million keystroke events; 57.1 million data-points for accelerometer and gyroscope each; 1.7 million data-points for swipes; and enables future research to explore previously unexplored directions in inter-device and inter-modality biometrics.