Omkar2118/datasets huggingface dataset:
SALAMI
Full name: Structural Analysis of Large Amounts of Music Information

Comes from https://ddmal.music.mcgill.ca/research/SALAMI/:

SALAMI is an innovative and ambitious computational musicology project. To date, musical analysis has been conducted by individuals and on a small scale. Our computational approach, combined with the huge volume of data now available from such source as the Internet Archive, will: a) deliver a very substantive corpus of musical analyses in a common framework for use by music scholars, students and beyond; and, b) establish a methodology and tooling which will enable others to add to this in the future and to broaden the application of the techniques we establish. A resource of SALAMI’s magnitude empowers musicologists to approach their work in a new and different way, starting with the data, and to ask research questions that have not been possible before.

There are two resources available on this site:

 - Annotation data: Visit this page to access the annotation data and to learn about how it was collected.
 - Blog: Here you’ll find updates about SALAMI features and tools. The older posts recount the data collection process.
 - Background: The background page gives an overview of the SALAMI project. It consists mainly of the proposal for the Digging Into Data grant that SALAMI was awarded in 2009.

Through a Digging Into Data grant, this research was supported by the Social Sciences and Humanities Research Council of Canada, by the National Science Foundation, and by JISC.
Lower-limb Kinematics and Kinetics During Continuously Varying Human Locomotion

This dataset reports the lower-limb kinematics and kinetics of ten able-bodied subjects walking at multiple inclines (± 0°, 5°, and 10°) and speeds (0.8 m/s, 1 m/s, and 1.2 m/s), running over level-ground at multiple speeds (1.8 m/s, 2 m/s, 2.2 m/s, and 2.4 m/s), walking and running with constant acceleration and deceleration (± 0.2 m/s2, and 0.5 m/s2), and stair ascent/descent with multiple stair inclines (± 20°, 25°, 30°, and 35°). This dataset also includes sit-stand transitions, walk-run transitions, and walk-stairs transitions. Data were recorded by a Vicon motion capture system and, for applicable tasks, a Bertec instrumented treadmill. This dataset can aid in the development of kinematic models of multi-activity human locomotion and the design and control of agile wearable robots.

Introducing paper: Lower-limb kinematics and kinetics during continuously varying human locomotion
TMBuD

**TMBuD** is a dataset for building recognition and 3D reconstruction of human made structures in urban scenarios. The dataset features 160 images of buildings from Timişoara, Romania, with a resolution of 768 x 1024 pixels each. The proposed dataset will allow proper evaluation of salient edges and semantic segmentation of images focusing on the street view perspective

Introducing paper: TMBuD: A dataset for urban scene building detection
Surgical Hands

Surgical Hands is a dataset that provides multi-instance articulated hand pose annotations for in-vivo videos. The dataset contains 76 video clips from 28 publicly available surgical videos and over 8.1k annotated hand pose instances.

Introducing paper: Temporally Guided Articulated Hand Pose Tracking in Surgical Videos