Tracking bacterial active matter in complex environments using deep learning paper - Tracking code Updated

This dataset contains the code used for the machine-learning-based tracking method outlined in the paper - "Tracking bacterial active matter in complex environments using deep learning".

The tracking method follows two steps - (1) object detection and (2) detection linking that are combined to output the trajectories of multiple particles from video microscopy data. Each step has a corresponding python notebook. This method is also compared to Trackpy (a popular tracking software for video microscopy data) and the notebook for this algorithm is in this dataset. The dataset also contains a README file which presents further information regarding the different code files. The notebook to perform step (2) detection linking has been updated.