Skip to main content

Tracking cells and lineage with deep learning.

Project description

DeepCell Tracking Banner

PyPI version Build Status Coverage Status

deepcell-tracking uses deep learning models from deepcell-tf within an assignment problem framework to track cells through time-lapse sequences and build cell lineages. The assignment problem is solved using the Hungarian algorithm.

Getting Started

deepcell-tracking is a Python package that can be installed with pip:

pip install deepcell-tracking

Or it can be installed from source:

git clone

cd deepcell-tracking

# install the dependencies
pip install .

How to Use

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

# 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

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DeepCell_Tracking-0.6.1.tar.gz (37.3 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page