pyotb 2.0.0.dev7

Library to enable easy use of the Orfeo ToolBox (OTB) in Python

pyotb: a pythonic extension of Orfeo Toolbox

pyotb wraps the Orfeo Toolbox (OTB) python bindings to make it more developer friendly.

Key features

• Easy use of OTB applications from python
• Simplify common sophisticated I/O features of OTB
• Lazy execution of in-memory pipelines with OTB streaming mechanism
• Interoperable with popular python libraries (numpy, rasterio)
• Extensible

Documentation hosted at pyotb.readthedocs.io.

Example

Building a simple pipeline with OTB applications

import pyotb

# RigidTransformResample application, with input parameters as dict
resampled = pyotb.RigidTransformResample({
    "in": "https://some.remote.data/input.tif",  # Note: no /vsicurl/...
    "interpolator": "linear", 
    "transform.type.id.scaley": 0.5,
    "transform.type.id.scalex": 0.5
})

# OpticalCalibration, with automatic input parameters resolution
calib = pyotb.OpticalCalibration(resampled)

# BandMath, with input parameters passed as kwargs
ndvi = pyotb.BandMath(calib, exp="ndvi(im1b1, im1b4)")

# Pythonic slicing using lazy computation (no memory used)
roi = ndvi[20:586, 9:572]

# Pipeline execution
# The actual computation happens here !
roi.write("output.tif", "float")

pyotb's objects also enable easy interoperability with numpy and rasterio:

# Numpy and RasterIO style attributes
print(roi.shape, roi.dtype, roi.transform)
print(roi.metadata)

# Other useful information
print(roi.get_infos())
print(roi.get_statistics())

array = roi.to_numpy()
array, profile = roi.to_rasterio()

Contributing

Contributions are welcome on Github or the source repository hosted on the Orfeo ToolBox GitLab.