deepforest 1.4.0

Tree crown prediction using deep learning retinanets

Deepforest

Full documentation

http://deepforest.readthedocs.io/en/latest/

Installation

Compiled wheels have been made for linux, osx and windows

#Install DeepForest
pip install deepforest

Get in touch

See the GitHub Repo to see the source code or submit issues and feature requests.

Citation

Most usage of DeepForest should cite two papers.

The first is the DeepForest paper, which describes the package:

Weinstein, B.G., Marconi, S., Aubry‐Kientz, M., Vincent, G., Senyondo, H. and White, E.P., 2020. DeepForest: A Python package for RGB deep learning tree crown delineation. Methods in Ecology and Evolution, 11(12), pp.1743-1751. https://doi.org/10.1111/2041-210X.13472

The second is the paper describing the model.

For the tree detection model cite:

Weinstein, B.G.; Marconi, S.; Bohlman, S.; Zare, A.; White, E.P., 2019. Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks. Remote Sensing 11, 1309 https://doi.org/10.3390/rs11111309

For the bird detection model cite:

Weinstein, B.G., L. Garner, V.R. Saccomanno, A. Steinkraus, A. Ortega, K. Brush, G.M. Yenni, A.E. McKellar, R. Converse, C.D. Lippitt, A. Wegmann, N.D. Holmes, A.J. Edney, T. Hart, M.J. Jessopp, R.H. Clarke, D. Marchowski, H. Senyondo, R. Dotson, E.P. White, P. Frederick, S.K.M. Ernest. 2022. A general deep learning model for bird detection in high‐resolution airborne imagery. Ecological Applications: e2694 https://doi.org/10.1002/eap.2694

Acknowledgments

Development of this software was funded by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative through Grant GBMF4563 to Ethan P. White.