Lazy raster band processing
Small Python library for processing large raster images.
Currently a work in progress.
source = AWSLandsat8Source("LC08_L1TP_139045_20170304_20170316_01_T1", band="8") # Lazily create a band and build a description of processing steps band = Band(source) \ .and_then(Resize(extents)) \ .and_then(HistogramAdjust()) \ .and_then(Reproject(crs)) # Forces computation array = band.render_to_array() band.render_to_file("output.tif")
Installing GDAL is the most challenging part. Installing directly from PyPI is historically unlikely to work.
First, install numpy:
pip install numpy
Then, choose one of the following:
- install with a system package manager
sudo apt install libgdal-dev
brew install gdal
- install from conda-forge:
conda install -c conda-forge gdal
- compile manually
Afterwards, the correct Python bindings can be installed with
pip install GDAL==$(gdal-config --version) --global-option=build_ext --global-option="-I/usr/include/gdal"
pip install picoraster
python -m src.tests
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Hashes for picoraster-0.0.2-py3-none-any.whl