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Pipeline for building deep learning models to classify PhenoCam images.

Project description

PhenoCamSnow

Documentation Status Code style: black

PhenoCamSnow is a Python package for quickly building deep learning models to classify PhenoCam images.

Installation

PhenoCamSnow supports Python 3.7+ and can be installed via pip:

pip install phenocam-snow

Optional dependencies for development and documentation purposes can be installed by specifying the extras [dev] and [docs], repsectively.

Example Usage

The following code snippets show how to train and evaluate a model on classifying images from the canadaojp site into "snow", "no snow", and "too dark".

python -m phenocam_snow.train \
   canadaojp \
   --model resnet18 \
   --learning_rate 5e-4 \
   --weight_decay 0.01 \
   --new \
   --n_train 120 \
   --n_test 30 \
   --classes snow no_snow too_dark

This will print out the file path of the best model, which can be substituted into the next command.

python -m phenocam_snow.predict \
   canadaojp \
   [path/to/best_model.ckpt] \
   resnet18 \
   --categories snow no_snow too_dark
   --url https://phenocam.nau.edu/data/latest/canadaojp.jpg

Advanced usage details can be found in the documentation.

Citation

If you use PhenoCamSnow for your work, please see CITATION.cff or use the citation prompt provided by GitHub in the sidebar.

Acknowledgements

Professor Jochen Stutz and Zoe Pierrat.

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