igor3357/post-discharge-channel

Dataset Description

This dataset is designed for training and evaluating computer vision models for the segmentation of post-discharge channels in shadowgraph images.

A post-discharge channel is a gas region formed after a pulsed electrical discharge. Due to heating and the resulting density gradients, the channel can be observed using shadowgraph imaging. Its shape changes over time as a result of gas expansion, diffusion, convective motion, and interaction with shock waves and other flow structures.

Automatic segmentation makes it possible to process large sequences of experimental images and quantitatively investigate the evolution of the channel, including its area, characteristic dimensions, deformation, displacement, and lifetime.

The dataset can be used for training YOLO26 and other YOLO-compatible segmentation models.

The dataset contains 695 annotated images and includes one segmentation class:

Class ID: 0

Class name: post-discharge-channel

Citation

If you use this model, dataset, or accompanying software in your research, please cite one or more of the following publications, selecting those most relevant to your work:

• https://doi.org/10.1016/j.actaastro.2025.09.091
• https://doi.org/10.26089/NumMet.v24r217
• https://doi.org/10.1615/JFlowVisImageProc.2025058234
• https://doi.org/10.1016/j.actaastro.2023.11.021
• https://doi.org/10.26583/sv.15.4.01