FlameTrack 1.0.0b1

Python tool for image dewarping and flame front tracking in experimental fire research.

FlameTrack

FlameTrack is a Python application for analyzing flame spread experiments, including room corner tests and lateral flame spread tests. It offers an intuitive graphical user interface (GUI) for:

• Image Dewarping – correcting perspective distortions for different setups.
• Flame Edge Tracking – detecting and following the flame front over time.
• Data Export – saving processed images, metadata, and measurements for further analysis.

Designed for research environments, FlameTrack combines precision with ease of use.

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Features

• Two experiment modes – Room Corner and Lateral Flame Spread, with tailored workflows.
• Point-based calibration for accurate dewarping.
• Dynamic edge detection with adjustable thresholds.
• Structured result storage in HDF5 format.

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Installation

The easiest way to install FlameTrack is from PyPI:

pip install flametrack

For updates:

pip install --upgrade flametrack

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Usage

Start the application

flametrack

(or)

python -m flametrack

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Typical workflow

1. Select experiment type – Room Corner or Lateral Spread.
2. Load your experimental data – images.
3. Mark reference points – for dewarping calibration.
4. Run dewarping – to obtain corrected images.
5. Start flame edge tracking – extract flame position over time.

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Development installation

If you want to contribute or run FlameTrack from source:

git clone https://github.com/FireDynamics/FlameTrack.git
cd FlameTrack
pip install -e .

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Contributing

Contributions are welcome – whether it’s bug reports, feature suggestions, or code improvements. Please open an issue or submit a pull request on GitHub.

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License

See the LICENSE file for details.