Python library to work with geospatial data
- Aim and scope
- Modules
- Quickstart example
- Requirements and installation
- Documentation and wiki
- Citing
- License
Aim and scope
As a part of Aeronetlib, which is designed to make it easier for the deep learning researchers to handle the remote sensing data, Aeronet_raster provides an interface to handle geotiff raster images.
- Modules and classes
- .raster
- Band | BandCollection
- BandSample | BandSampleCollection
- .collectionprocessor
- CollectionProcessor
- SampleWindowWriter
- SampleCollectionWindowWriter
- .visualization
- add_mask
Quickstart example
Requirements and installation
- python 3
- rasterio >= 1.0.0
- shapely >= 1.7.1
- rtree>=0.8.3
- opencv-python>=4.0.0
- tqdm >=4.36.1
Pypi package: .. code:: bash
$ pip install aeronet[all]
for partial install:
Raster-only .. code:: bash
$ pip install aeronet[raster]
Vector-only .. code:: bash
$ pip install aeronet[vector]
Source code: .. code:: bash
$ pip install git+https://github.com/aeronetlab/aeronetlib
Contributing We accept pull-requests and bug reports at github page
You can use `make build` to build the libraries and `make upload` to update them at pypi (authorization required).
Testing
1. Create and activate virtual environment
2. `make prepare` to install all requirements in the venv
3. `make test` to run all tests
Documentation and wiki
The project wiki contains some insights about the background of the remote sensing data storage and processing and useful links to the external resources. Latest documentation is available at Read the docs
Citing
@misc{Yakubovskiy:2019,
Author = {Pavel Yakubovskiy, Alexey Trekin},
Title = {Aeronetlib},
Year = {2019},
Publisher = {GitHub},
Journal = {GitHub repository},
Howpublished = {\url{https://github.com/aeronetlab/aeronetlib}}
}License
Project is distributed under MIT License.