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        "description": "# ![DeepCell Tracking Banner](https://raw.githubusercontent.com/vanvalenlab/deepcell-tracking/master/docs/images/DeepCell_tracking_Banner.png)\n\n[![PyPI version](https://badge.fury.io/py/DeepCell-Tracking.svg)](https://badge.fury.io/py/DeepCell-Tracking)\n[![Build Status](https://github.com/vanvalenlab/deepcell-tracking/workflows/build/badge.svg)](https://github.com/vanvalenlab/deepcell-tracking/actions)\n[![Coverage Status](https://coveralls.io/repos/github/vanvalenlab/deepcell-tracking/badge.svg?branch=master)](https://coveralls.io/github/vanvalenlab/deepcell-tracking?branch=master)\n\n`deepcell-tracking` uses deep learning models from [deepcell-tf](https://github.com/vanvalenlab/deepcell-tf) within an assignment problem framework to [track cells through time-lapse sequences](https://www.biorxiv.org/content/10.1101/803205v2) and build cell lineages. The assignment problem is solved using the [Hungarian algorithm.](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2747604/)\n\n## Getting Started\n\n`deepcell-tracking` is a Python package that can be installed with `pip`:\n\n```bash\npip install deepcell-tracking\n```\n\nOr it can be installed from source:\n\n```bash\ngit clone https://github.com/vanvalenlab/deepcell-tracking.git\n\ncd deepcell-tracking\n\n# install the dependencies\npip install .\n```\n\n## How to Use\n\n```python\nfrom deepcell_tracking import CellTracker\n\n# X and y are the time-sequence data and their corresponding segmentations (labels), respectively.\n# model is a deepcell-tf tracking model.\ntracker = CellTracker(X, y, model)\n\ntracker.track_cells()  # runs in place, builds tracks\n\n# Save all tracked data and lineage files to a .trk file\ntracker.dump('./results.trk')\n\n# Open the track file\nfrom deepcell_tracking.utils import load_trks\n\ndata = load_trks('./results.trk')\n\nlineage = data['lineages']  # linage information\nX = data['X']  # raw X data\ny = data['y']  # tracked y data\n```\n\n\n",
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