BigEarthNet Common

A collection of common tools to interact with the BigEarthNet dataset.

This library provides a collection of high-level tools to better work with the BigEarthNet dataset.

bigearthnet_common tries to:

Collect the most relevant constants into a single place to reduce the time spent looking for these, like:
- The 19 or 43 class nomenclature strings
- URL
- Band statistics (mean/variance) as integer and float
- Channel names
- etc.
Provide common metadata related functions
- Safe JSON parser for S1/S2
- Get the original split
- Get a list of snowy/cloudy patches
- Convert the old labels to the new label nomenclature
- Generate multi-hot encoded label views
Easily filter patches and generate subsets as CSV files
Allow to quickly test code on BigEarthNet data without requiring to download the entire archvie

Installation

The package is available via PyPI and can be installed with:

pip install bigearthnet_common

The package has Python-only dependencies and should cause no issues in more complex Conda environments with various binaries.

Review constants

To quickly search for BigEarthNet constants of interest, call:

ben_constants_prompt or
python -m bigearthnet_common.constants

Sets generator

To generate sets/subsets from the data and to store them as a CSV file, use:

ben_build_csv_sets --help

This command-line tool lets the user easily create subsets from common constraints. To generate a CSV file that contains all Sentinel-2 patches from Serbia only during the Summer and Spring months, call the function as:

ben_build_csv_sets <FILE_PATH> S2 --seasons Winter --seasons Summer --countries Serbia --remove-unrecommended-dl-patches

:::{note}

By default, this tool will always remove the unrecommended patches, i.e., patches that contain seasonal snow, shadows, clouds, or that have no labels in the 19-class nomenclature

:::

Describe patch

The library provides a tool to quickly visualize meta-data information about each patch:

ben_describe_patch <S1/S2 patch name>

Metadata

Release files for bigearthnet-common 2.8.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bigearthnet-common 2.8.0
File	Size	Uploaded
bigearthnet-common-2.8.0.tar.gz	6.9 MB	Oct 18, 2022	Details

Built distribution (wheel)

Table of built distributions (wheels) for bigearthnet-common 2.8.0
File	Interpreter	ABI	Platform	Reset
bigearthnet_common-2.8.0-py3-none-any.whl 6.8 MB Oct 18, 2022	Python 3	none	any	Details

Total release size: 13.7 MB

Release files / bigearthnet-common-2.8.0.tar.gz

Download URL	bigearthnet-common-2.8.0.tar.gz
Size	6.9 MB
Tags	Source
SHA-256 checksum How to use checksums	`250d034351299ba4a0a3edb0c85adba983bdf445303f98616fd527c470d8157e`
BLAKE2b-256 checksum How to use checksums	`2965149b39956721d00aa5282414a88aef68630a20a85de69b8fc2401b5b16bb`
Upload date	Oct 18, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`pdm/2.1.5 CPython/3.8.14`

Release files / bigearthnet_common-2.8.0-py3-none-any.whl

Download URL	bigearthnet_common-2.8.0-py3-none-any.whl
Size	6.8 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`6c2bcf2b1d39a3f48925b0d941557152f9e523576fbb9d2b881a842ed92fd6af`
BLAKE2b-256 checksum How to use checksums	`66a360660c379273ea266e203585af8fea47e993046ca27fcdbf4c66141f0fa1`
Upload date	Oct 18, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`pdm/2.1.5 CPython/3.8.14`