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tools/pretraining_data_builder/README.md

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+# Pretraining Data Builder
+This code is for building pretraining data for the self-supervised learning of SkySense++.
+
+## Install
+Prepare the environment:
+```
+conda create -n data_builder python=3.12
+conda activate data_builder
+pip install -r requirements.txt
+```
+Download pretraining data list in lmdb format from [Zenodo](https://zenodo.org/records/14994430)
+
+## Download Data
+```
+python -m rsi_download --username <username> --password <password> --api_key <api_key> <X> <Y> <Z> <date_min> <date_max>
+```
+Notes:
+1. `username` and `password` can be created in the [Copernicus Data Space Ecosystem](https://data.copernicus.eu/cdsapp/#!/home), 
+`api_key` can be created in the [Maxar](https://ard.maxar.com/docs/about/).
+2. `X` `Y` `Z` are coordinates in the Web Mercator coordinate system.
+3. `date_min` and `date_max` are in the format of `YYYY-MM`.
+
+## Process Data
+```
+python -m rsi_process --platform <platform> --fn_img path/to/image.zip --save_dir output_<platform>/
+```
+Notes:
+1. `platform` can be `s1`, `s2`, `wv`.
+2. `fn_img` is the path to the downloaded zip file.
+3. `save_dir` is the directory to save the processed data.
+
+## Automatic Script
+```
+sh run_data_builder.sh
+```
+This script will first read the pretraining list, then download the data according to the list, and proceed them automatically.