Model Details

Model Description

A pretrained, general purpose microscopy identity tracking model. Trained on diverse data across scales, from cells to organelles. Expects videos with accompanying detection labels in .slp or CellTrackingChallenge format.

Developed by: talmolab
Shared by: talmolab
License: [More Information Needed]

Model Sources

Repository: talmolab/dreem
Paper [optional]: [More Information Needed]

Uses

To track identities of instances in microscopy timelapses. Maintains consistent identities across time.

How to Get Started with the Model

See https://dreem.sleap.ai

Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

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Training Hyperparameters

See configuration files provided in model directory

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

Metrics

CLEARMOT metrics, implemented by https://github.com/cheind/py-motmetrics

CellTrackingChallenge metrics, implemented by https://github.com/CellTrackingChallenge/py-ctcmetrics#

Results

[More Information Needed]

Summary

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

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More Information [optional]

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Model Card Authors [optional]

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Model Card Contact

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