[GSoC] 8. Add time-series anomaly detection support to Anomalib

[samet-akcay]

Short description

Anomalib currently only contains visual anomaly detection algorithms that operate in the image- and video domain. However, the principles of anomaly detection can be applied to other domains, such as audio, as well. The goal of this project is to add support for anomaly detection in 1D (time-series) data, such as audio signals. The following components would need to be added/modified to achieve time-series anomaly detection support:

Pytorch-Lightning compatible dataset adapters for reading 1D-data
At least 1 fully functional time-series anomaly detection model
Metrics and visualization utilities for qualitative and quantitative evaluation of the model’s performance.
Expected outcomes: Time-series data adapters, 1D anomaly detection model, metrics and visualization utilities

Skills required/preferred

Basic ML knowledge, Signal processing basics, Python

Mentors

Dick Ameln, Samet Akcay

Size of project

175 hours

Difficulty
Medium

[Ravindu987]

Hi
I'm expecting to apply for GSoC '23 with OpenVINO and I'm interested in this particular project. I've done the prerequisite task and did the PR.
I've read this article on Anomalib and I'd like to gain a deeper understanding. Could you please provide me with some materials