Metadata-Version: 2.1
Name: DeepCell_Tracking
Version: 0.3.1
Summary: Tracking cells and lineage with deep learning.
Home-page: https://github.com/vanvalenlab/deepcell-tracking
Author: Van Valen Lab
Author-email: vanvalenlab@gmail.com
License: LICENSE
Download-URL: https://github.com/vanvalenlab/deepcell-tracking/tarball/0.3.1
Description: # ![DeepCell Tracking Banner](https://raw.githubusercontent.com/vanvalenlab/deepcell-tracking/master/docs/images/DeepCell_tracking_Banner.png)
        
        [![PyPI version](https://badge.fury.io/py/Deepcell-Tracking.svg)](https://badge.fury.io/py/Deepcell-Tracking)
        [![Build Status](https://github.com/vanvalenlab/deepcell-tracking/workflows/build/badge.svg)](https://github.com/vanvalenlab/deepcell-tracking/actions)
        [![Coverage Status](https://coveralls.io/repos/github/vanvalenlab/deepcell-tracking/badge.svg?branch=master)](https://coveralls.io/github/vanvalenlab/deepcell-tracking?branch=master)
        
        `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/)
        
        ## Getting Started
        
        `deepcell-tracking` is a Python package that can be installed with `pip`:
        
        ```bash
        pip install deepcell-tracking
        ```
        
        Or it can be installed from source:
        
        ```bash
        git clone https://github.com/vanvalenlab/deepcell-tracking.git
        
        cd deepcell-tracking
        
        # install the dependencies
        pip install .
        ```
        
        ## How to Use
        
        ```python
        from deepcell_tracking import CellTracker
        
        # X and y are the time-sequence data and their corresponding segmentations (labels), respectively.
        # model is a deepcell-tf tracking model.
        tracker = CellTracker(X, y, model)
        
        tracker.track_cells()  # runs in place, builds tracks
        
        # Save all tracked data and lineage files to a .trk file
        tracker.dump('./results.trk')
        
        # Open the track file
        from deepcell_tracking.utils import load_trks
        
        data = load_trks('./results.trk')
        
        lineage = data['lineages']  # linage information
        X = data['X']  # raw X data
        y = data['y']  # tracked y data
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Provides-Extra: tests
