| # DynamicNuclearNet -- Tracking Data | |
| The tracking portion of the DynamicNuclearDataset includes all data used for tracking. | |
| The following files are included: | |
| - `train.trk` | |
| - Dimensions: (91, 71, 584, 600, 1) BTYXC | |
| - Tracks: 11,039 | |
| - Divisions: 1,608 | |
| - `val.trk` | |
| - Dimensions: (27, 71, 584, 600, 1) BTYXC | |
| - Tracks: 2,923 | |
| - Divisions: 444 | |
| - `test.trk` | |
| - Dimensions: (12, 71, 584, 600, 1) BTYXC | |
| - Tracks: 1,213 | |
| - Divisions: 178 | |
| - `data-source.npz` | |
| - A record of the source of each batch divided into one array per data split | |
| Each `trks` file contains three components: | |
| - X: raw fluorescent nuclear data | |
| - y: nuclear segmentation masks | |
| - lineages: lineage records including the cell id, frames present and division links from parents to daughter cells | |
| ## Change Log | |
| DynamicNuclearNet 1.0 (June 2023): The original dataset used for all experiments in Schwartz et al. 2023 | |
| ## Instructions for use | |
| ```python | |
| import os | |
| import numpy as np | |
| import pandas as pd | |
| from deepcell_tracking.trk_io import load_trks | |
| data_dir = 'path_to_data' | |
| data = load_trks(os.path.join(data_dir, 'test.trks')) | |
| X = data['X'] | |
| y = data['y'] | |
| lineages = data['lineages'] | |
| data_source = np.load(os.path.join(data_dir, 'data-source.npz'), allow_pickle=True) | |
| meta = pd.DataFrame(data_source['test'], columns=['filename', 'experiment', 'pixel_size', 'screening_passed', 'time_step', 'specimen']) | |
| ``` | |