Comparison between otbApplication and pyotb¶

Single application execution¶

Using OTB, the code would be like :

import otbApplication

input_path = 'my_image.tif'
resampled = otbApplication.Registry.CreateApplication('RigidTransformResample')
resampled.SetParameterString('in', input_path)
resampled.SetParameterString('interpolator', 'linear')
resampled.SetParameterFloat('transform.type.id.scalex', 0.5)
resampled.SetParameterFloat('transform.type.id.scaley', 0.5)
resampled.SetParameterString('out', 'output.tif')
resampled.SetParameterOutputImagePixelType('out', otbApplication.ImagePixelType_uint16)
resampled.ExecuteAndWriteOutput()

Using pyotb:

import pyotb
resampled = pyotb.RigidTransformResample({'in': 'my_image.tif', 'interpolator': 'linear',
                                          'transform.type.id.scaley': 0.5, 'transform.type.id.scalex': 0.5})
resampled.write('output.tif', pixel_type='uint16')

In-memory connections¶

Using OTB :

import otbApplication

resampled = otbApplication.Registry.CreateApplication('RigidTransformResample')
resampled.SetParameterString('in', 'my_image.tif')
resampled.SetParameterString('interpolator', 'linear')
resampled.SetParameterFloat('transform.type.id.scalex', 0.5)
resampled.SetParameterFloat('transform.type.id.scaley', 0.5)
resampled.Execute()

calibrated = otbApplication.Registry.CreateApplication('OpticalCalibration')
calibrated.ConnectImage('in', resampled, 'out')
calibrated.SetParameterString('level', 'toa')
calibrated.Execute()

dilated = otbApplication.Registry.CreateApplication('BinaryMorphologicalOperation')
dilated.ConnectImage('in', calibrated, 'out')
dilated.SetParameterString("filter", 'dilate')
dilated.SetParameterString("structype", 'ball')
dilated.SetParameterInt("xradius", 3)
dilated.SetParameterInt("yradius", 3)
dilated.SetParameterString('out', 'output.tif')
dilated.SetParameterOutputImagePixelType('out', otbApplication.ImagePixelType_uint16)
dilated.ExecuteAndWriteOutput()

Using pyotb:

import pyotb

resampled = pyotb.RigidTransformResample({'in': 'my_image.tif', 'interpolator': 'linear', 
                                          'transform.type.id.scaley': 0.5, 'transform.type.id.scalex': 0.5})

calibrated = pyotb.OpticalCalibration({'in': resampled, 'level': 'toa'}) 

dilated = pyotb.BinaryMorphologicalOperation({'in': calibrated, 'out': 'output.tif', 'filter': 'dilate', 
                                              'structype': 'ball', 'xradius': 3, 'yradius': 3})
dilated.write('result.tif', pixel_type='uint16')

Arithmetic operations¶

Every pyotb object supports arithmetic operations, such as addition, subtraction, comparison... Consider an example where we want to perform the arithmetic operation image1 * image2 - 2*image3

Using OTB, the following code works for 3-bands images :

import otbApplication

bmx = otbApplication.Registry.CreateApplication('BandMathX')
bmx.SetParameterStringList('il', ['image1.tif', 'image2.tif', 'image3.tif'])  # all images are 3-bands
exp = 'im1b1*im2b1 - 2*im3b1; im1b2*im2b2 - 2*im3b2; im1b3*im2b3 - 2*im3b3'
bmx.SetParameterString('exp', exp)
bmx.SetParameterString('out', 'output.tif')
bmx.SetParameterOutputImagePixelType('out', otbApplication.ImagePixelType_uint8)
bmx.ExecuteAndWriteOutput()

With pyotb, the following works with images of any number of bands :

import pyotb

# transforming filepaths to pyotb objects
input1, input2, input3 = pyotb.Input('image1.tif'), pyotb.Input('image2.tif') , pyotb.Input('image3.tif')

res = input1 * input2 - 2 * input2
res.write('output.tif', pixel_type='uint8')

Slicing¶

Using OTB, for selection bands or ROI, the code looks like:

import otbApplication

# selecting first 3 bands
extracted = otbApplication.Registry.CreateApplication('ExtractROI')
extracted.SetParameterString('in', 'my_image.tif')
extracted.SetParameterStringList('cl', ['Channel1', 'Channel2', 'Channel3'])
extracted.Execute()

# selecting 1000x1000 subset
extracted = otbApplication.Registry.CreateApplication('ExtractROI')
extracted.SetParameterString('in', 'my_image.tif')
extracted.SetParameterString('mode', 'extent')
extracted.SetParameterString('mode.extent.unit', 'pxl')
extracted.SetParameterFloat('mode.extent.ulx', 0)
extracted.SetParameterFloat('mode.extent.uly', 0)
extracted.SetParameterFloat('mode.extent.lrx', 999)
extracted.SetParameterFloat('mode.extent.lry', 999)
extracted.Execute()

Instead, using pyotb:

import pyotb

# transforming filepath to pyotb object
inp = pyotb.Input('my_image.tif')

extracted = inp[:, :, :3]  # selecting first 3 bands
extracted = inp[:1000, :1000]  # selecting 1000x1000 subset