Omkar2118/datasets huggingface dataset:
MAPS
Full name: Midi Aligned Piano Dataset

MAPS – standing for MIDI Aligned Piano Sounds – is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.
VisEvent

**VisEvent** (Visible-Event benchmark) is a dataset constructed for the evaluation of tracking by combing visible and event cameras. VisEvent is featured in: 

Large-scale: 820 video sequences (RGB video + Event flows), contains 371,128 frames, 500 / 320 for the train / testing respectively; 

High-quality Dense Annotation: Manual annotation with careful inspection in each frame; 

Multiple-baseline: Dual-modality SOTA trackers.

Image Source: [VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows](/paper/visevent-reliable-object-tracking-via)

Introducing paper: VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows
Images from camera traps in the Jura and Ain counties (France)

This dataset contains images taken from camera traps set up in the Jura and Ain counties in France. We use this dataset to illustrate the training of a deep learning algorithm with application to animal specie sidentification. See more here https://github.com/oliviergimenez/computo-deeplearning-occupany-lynx.

Introducing paper: Trade-off between deep learning for species identification and inference about predator-prey co-occurrence: Reproducible R workflow integrating models in computer vision and ecological statistics