Intetion to smoth deep learning implementation with geoespatial data
The workflow is:
- Download tiff images
- Create Pytorch Dataset
- Transferlearning
- Train/Test with Pytorch
- Register every iteration in tensorboard
#Comment codes properly
#transate variable names to english
#Configure paths to work in anywhere
#Example jupyter notebooks with hyperspectral handling
#rename variables in english
#Example in a jupyter notebook how to work with one 1 band raster
#Example jupyter notebooks with hyperspectral handling and transfer learning
#Ensemble models with images from different bands with different resolutions
#Create a free QGIS plugin for semi-supervisionade DL s2
#Example how to work with one 1 band raster
#Code hyperspectral handling
#Code transfer learning with hyperspectral handling
Commits are welcome!