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Timelapse Feature Explorer

Timelapse Feature Explorer is a web tool for interacting with and visualizing features in time-series segmented data. You can apply color maps and ranges, switch between features in your dataset, play through your data to observe motion, and view plots showing how feature data change over time.

This project originated from the Allen Institute for Cell Science (AICS) Nuclear Morphogenesis project and is being updated to support broader use cases. View our Issues page for more details about potential future features!

Builds

Stable build: timelapse.allencell.org

Latest (main branch): https://allen-cell-animated.github.io/timelapse-colorizer/

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Viewing Custom Datasets

Datasets must be preprocessed for viewing in Timelapse Feature Explorer. We provide the colorizer-data Python package, which includes tutorials and documentation about the data specification. See our getting started guide for more details.

Compatible datasets hosted over HTTPS can be loaded directly from the interface. Click the Load button in the top right to open a URL.

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Note: If your dataset is hosted via HTTP rather than HTTPS, you'll need to install and run the project locally for security reasons. See below for more help.

Installation

Installation is optional and is only necessary for accessing datasets via HTTP. You can use the hosted version of Timelapse Feature Explorer to access HTTPS-hosted datasets without installing the project.

Prerequisites:

  • Node 18 or higher: https://nodejs.org
  • Python 3 (and optionally, a virtual Python environment)

Web tool

Open a command terminal and run the following commands. Installation may take a few minutes.

git clone https://github.com/allen-cell-animated/timelapse-colorizer.git
cd timelapse-colorizer
npm install

To start the development server, run:

npm run dev

This will allow you to access the viewer from your browser. By default, the server will be hosted at http://localhost:5173/.

You can also access our internal build (which may have some additional experimental features) by running npm run dev-internal.

Development

See CONTRIBUTING.md for information related to developing the code.

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A web-based, time-series visualizer for tracked segmented data.

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