Resnet-based model to predict species presence vectors from satellite images. The model uses PECL (Paired Embeddings Contrastive Loss) as contrastive regularisation. More details to be added following an upcoming publication.
- Use conda to install packages using
pecl.yml
or pip install fromrequirements.txt
. - Add your user profile data paths in
content/data_paths_pecl.json
. (This step is not needed when just experimenting with the code and the example data provided in the repo).
- An example data set is provided in
tests/data_tests/
. - Go to
notebooks/Getting started.ipynb
to see examples of how to load the data and model. - A link to the full S2-BMS data set will be added soon.
- Details will follow in the upcoming publication.
- PyTorch implementation can be found in
scripts/paired_embeddings_models.py
(ImageEncoder.pecl_loss()
). - Models are trained by running
scripts/train.py
andscripts/train_randomsearch.py
.
- The
notebooks/
folder contains the notebooks for creating figures/tables.