Some functions have been written, entirely based on OTB, to mimic the behavior of some well-known numpy functions.

pyotb.where¶

Equivalent of numpy.where. It is the equivalent of the muparser syntax condition ? x : y that can be used in OTB's BandMath.

import pyotb

# transforming filepaths to pyotb objects
labels, image1, image2 = pyotb.Input('labels.tif'), pyotb.Input('image1.tif') , pyotb.Input('image2.tif')

# If labels = 1, returns image1. Else, returns image2
res = pyotb.where(labels == 1, image1, image2)  # this would also work: pyotb.where(labels == 1, 'image1.tif', 'image2.tif')

# A more complex example
# If labels = 1, returns image1. If labels = 2, returns image2. If labels = 3, returns 3. Else 0
res = pyotb.where(labels == 1, image1,
                  pyotb.where(labels == 2, image2,
                              pyotb.where(labels == 3, 3, 0)))

pyotb.clip¶

Equivalent of numpy.clip. Clip (limit) the values in a raster to a range.

import pyotb

res = pyotb.clip('my_image.tif', 0, 255)  # clips the values between 0 and 255

pyotb.all¶

Equivalent of numpy.all.

For only one image, this function checks that all bands of the image are True (i.e. !=0) and outputs a singleband boolean raster. For several images, this function checks that all images are True (i.e. !=0) and outputs a boolean raster, with as many bands as the inputs.

pyotb.any¶

Equivalent of numpy.any.

For only one image, this function checks that at least one band of the image is True (i.e. !=0) and outputs a singleband boolean raster. For several images, this function checks that at least one of the images is True (i.e. !=0) and outputs a boolean raster, with as many bands as the inputs.