This repo was set up to share code for semantic segmentation in the LELE project as described in "Testing the suitability of consumer-grade UAV imagery for semantic segmentation of savanna vegetation"1. Requirements are—amongst others—installation of:
- TensorFlow (CNN training)
- ArcGIS Pro (reference data creation)
- GDAL (tile generation for training and deployment of CNN)
since main workflows are based on this software. Additional requirements are listed in requirements.txt files within the subdirectory containing Python scripts and a summary is located in the main project directory.
Extensive information can be found in the LeleNet Wiki.
1Popp, M.R., Kalwij, J.M. Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers. Sci Rep 13, 13892 (2023). http://dx.doi.org/10.1038/s41598-023-40989-7