Remote-sensing-processor

- Added `normalize` function that applies min/max normalization to data
- Segmentation `train` and `test` now support multiple datasets input
- Segmentation `train`, `test` and `generate_map` now support multiprocessing
- Added support for more Landsat products
- Various bug fixes

Remote Sensing Processor 0.2 adds image segmentation module

- Added `train` and `test` functions that train and test pytorch and sklearn segmentation models
- `generate_tiles` and `generate map` functions reworked and moved to `rsp.segmentation` module
- Sentinel-2 superresolution algorithm rewritten in pytorch
- `normalized_difference` function renamed to `calculate_index`

This is the first release of Remote Sensing Processor.

It includes Sentinel-2 and Landsat preprocessing, creating raster mosaics, calculating normalized difference indices (for now NDVI only), cutting rasters to tiles and creating maps using pre-trained models.