S2s2net - Sentinel-2 Super-Resolution Segmentation Network

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Deep Learnings2s2net
Overview

S2S2Net

Sentinel-2 Super-Resolution Segmentation Network

Getting started

Installation

Basic

To help out with development, start by cloning this repo-url

git clone <repo-url>

Then I recommend using mamba to install both non-python binaries and python libraries. A virtual environment will also be created with Python and JupyterLab installed.

cd s2s2net
mamba env create --file environment.yml

Activate the virtual environment first.

mamba activate s2s2net

Finally, double-check that the libraries have been installed.

mamba list

Advanced

This is for those who want full reproducibility of the virtual environment.

Making an explicit conda-lock file (only needed if creating a new virtual environment/refreshing an existing one).

mamba env create --file environment.yml
mamba list --explicit > environment-linux-64.lock

Creating/Installing a virtual environment from a conda lock file. See also https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/managenvironments.html#building-identical-conda-environments.

mamba create --name s2s2net --file environment-linux-64.lock
mamba install --name s2s2net --file environment-linux-64.lock

Running jupyter lab

mamba activate s2s2net
python -m ipykernel install --user --name s2s2net  # to install virtual env properly
jupyter kernelspec list --json                     # see if kernel is installed
jupyter lab &
Owner
Wei Ji
Geospatial Data Scientist, Postdoc doing Remote Sensing AI research.
Wei Ji
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