A brief tour of OTB Applications


OTB ships with more than 90 ready to use applications for remote sensing tasks. They usually expose existing processing functions from the underlying C++ library, or compose them into high level pipelines. OTB applications allow to:

  • combine together two or more functions from the Orfeo Toolbox,
  • provide a nice high level interface to handle: parameters, input data, output data and communication with the user.

OTB applications can be launched in different ways, and accessed from different entry points. The framework can be extended, but Orfeo Toolbox ships with the following:

  • A command-line launcher, to call applications from the terminal,
  • A graphical launcher, with an auto-generated QT interface, providing ergonomic parameters setting, display of documentation, and progress reporting,
  • A SWIG interface, which means that any application can be loaded set-up and executed into a high-level language such as Python or Java for instance.
  • QGIS plugin built on top of the SWIG/Python interface is available with seamless integration within QGIS.

The OTB Applications are now rich of more than 90 tools, which are listed in the applications reference documentation, presented in chapter [chap:apprefdoc], page.

Running the applications

Common framework

All standard applications share the same implementation and expose automatically generated interfaces. Thus, the command-line interface is prefixed by otbcli_, while the Qt interface is prefixed by otbgui_. For instance, calling otbcli_Convert will launch the command-line interface of the Convert application, while otbgui_Convert will launch its GUI.

Using the command-line launcher

The command-line application launcher allows to load an application plugin, to set its parameters, and execute it using the command line. Launching the otbApplicationLauncherCommandLine without argument results in the following help to be displayed:

$ otbApplicationLauncherCommandLine
Usage : ./otbApplicationLauncherCommandLine module_name [MODULEPATH] [arguments]

The module_name parameter corresponds to the application name. The [MODULEPATH] argument is optional and allows to pass to the launcher a path where the shared library (or plugin) corresponding to module_name is.

It is also possible to set this path with the environment variable OTB_APPLICATION_PATH, making the [MODULEPATH] optional. This variable is checked by default when no [MODULEPATH] argument is given. When using multiple paths in OTB_APPLICATION_PATH, one must make sure to use the standard path separator of the target system, which is : on Unix, and ; on Windows.

An error in the application name (i.e. in parameter module_name) will make the otbApplicationLauncherCommandLine lists the name of all applications found in the available path (either [MODULEPATH] and/or OTB_APPLICATION_PATH).

To ease the use of the applications, and try avoiding extensive environment customization, ready-to-use scripts are provided by the OTB installation to launch each application, and takes care of adding the standard application installation path to the OTB_APPLICATION_PATH environment variable.

These scripts are named otbcli_<ApplicationName> and do not need any path settings. For example you can start the Orthorectification application with the script called otbcli_Orthorectification.

Launching an application with no or incomplete parameters will make the launcher display a summary of the parameters, indicating the mandatory parameters missing to allow for application execution. Here is an example with the OrthoRectification application:

$ otbcli_OrthoRectification

ERROR: Waiting for at least one parameter...

====================== HELP CONTEXT ======================
NAME: OrthoRectification
DESCRIPTION: This application allows to ortho-rectify optical images from supported sensors.

otbcli_OrthoRectification -io.in QB_TOULOUSE_MUL_Extract_500_500.tif -io.out QB_Toulouse_ortho.tif

DOCUMENTATION: http://www.orfeo-toolbox.org/Applications/OrthoRectification.html
======================= PARAMETERS =======================
        -progress                        <boolean>        Report progress
MISSING -io.in                           <string>         Input Image
MISSING -io.out                          <string> [pixel] Output Image  [pixel=uint8/int8/uint16/int16/uint32/int32/float/double]
        -map                             <string>         Output Map Projection [utm/lambert2/lambert93/transmercator/wgs/epsg]
MISSING -map.utm.zone                    <int32>          Zone number
        -map.utm.northhem                <boolean>        Northern Hemisphere
        -map.transmercator.falseeasting  <float>          False easting
        -map.transmercator.falsenorthing <float>          False northing
        -map.transmercator.scale         <float>          Scale factor
        -map.epsg.code                   <int32>          EPSG Code
        -outputs.mode                    <string>         Parameters estimation modes [auto/autosize/autospacing]
MISSING -outputs.ulx                     <float>          Upper Left X
MISSING -outputs.uly                     <float>          Upper Left Y
MISSING -outputs.sizex                   <int32>          Size X
MISSING -outputs.sizey                   <int32>          Size Y
MISSING -outputs.spacingx                <float>          Pixel Size X
MISSING -outputs.spacingy                <float>          Pixel Size Y
        -outputs.isotropic               <boolean>        Force isotropic spacing by default
        -elev.dem                        <string>         DEM directory
        -elev.geoid                      <string>         Geoid File
        -elev.default                    <float>          Average Elevation
        -interpolator                    <string>         Interpolation [nn/linear/bco]
        -interpolator.bco.radius         <int32>          Radius for bicubic interpolation
        -opt.rpc                         <int32>          RPC modeling (points per axis)
        -opt.ram                         <int32>          Available memory for processing (in MB)
        -opt.gridspacing                 <float>          Resampling grid spacing

For a detailed description of the application behaviour and parameters, please check the application reference documentation presented chapter [chap:apprefdoc], page  or follow the DOCUMENTATION hyperlink provided in otbApplicationLauncherCommandLine output. Parameters are passed to the application using the parameter key (which might include one or several . character), prefixed by a -. Command-line examples are provided in chapter [chap:apprefdoc], page .

Using the GUI launcher

The graphical interface for the applications provides a useful interactive user interface to set the parameters, choose files, and monitor the execution progress.

This launcher needs the same two arguments as the command line launcher :

$ otbApplicationLauncherQt module_name [MODULEPATH]

The application paths can be set with the OTB_APPLICATION_PATH environment variable, as for the command line launcher. Also, as for the command-line application, a more simple script is generated and installed by OTB to ease the configuration of the module path : to launch the graphical user interface, one will start the otbgui_Rescale script.

The resulting graphical application displays a window with several tabs:

  • Parameters is where you set the parameters and execute the application.
  • Logs is where you see the output given by the application during its execution.
  • Progress is where you see a progress bar of the execution (not available for all applications).
  • Documentation is where you find a summary of the application documentation.

In this interface, every optional parameter has a check box that you have to tick if you want to set a value and use this parameter. The mandatory parameters cannot be unchecked.

The interface of the application is shown here as an example.


Using the Python interface

The applications can also be accessed from Python, through a module named otbApplication. However, there are technical requirements to use it. If you use OTB through standalone packages, you should use the supplied environment script otbenv to properly setup variables such as PYTHONPATH and OTB_APPLICATION_PATH (on Unix systems, don’t forget to source the script). In other cases, you should set these variables depending on your configuration.

On Unix systems, it is typically available in the /usr/lib/otb/python directory. Depending on how you installed OTB, you may need to configure the environment variable PYTHONPATH to include this directory so that the module becomes available from Python.

On Windows, you can install the otb-python package, and the module will be available from an OSGeo4W shell automatically.

As for the command line and GUI launchers, the path to the application modules needs to be properly set with the OTB_APPLICATION_PATH environment variable. The standard location on Unix systems is /usr/lib/otb/applications. On Windows, the applications are available in the otb-bin OSGeo4W package, and the environment is configured automatically so you don’t need to tweak OTB_APPLICATION_PATH.

In the otbApplication module, two main classes can be manipulated :

  • Registry, which provides access to the list of available applications, and can create applications
  • Application, the base class for all applications. This allows to interact with an application instance created by the Registry

Here is one example of how to use Python to run the Smoothing application, changing the algorithm at each iteration.

#  Example on the use of the Smoothing application

# We will use sys.argv to retrieve arguments from the command line.
# Here, the script will accept an image file as first argument,
# and the basename of the output files, without extension.
from sys import argv

# The python module providing access to OTB applications is otbApplication
import otbApplication

# otbApplication.Registry can tell you what application are available
print "Available applications : "
print str( otbApplication.Registry.GetAvailableApplications() )

# Let's create the application with codename "Smoothing"
app = otbApplication.Registry.CreateApplication("Smoothing")

# We print the keys of all its parameter
print app.GetParametersKeys()

# First, we set the input image filename
app.SetParameterString("in", argv[1])

# The smoothing algorithm can be set with the "type" parameter key
# and can take 3 values : 'mean', 'gaussian', 'anidif'
for type in ['mean', 'gaussian', 'anidif']:

  print 'Running with ' + type + ' smoothing type'

  # Here we configure the smoothing algorithm
  app.SetParameterString("type", type)

  # Set the output filename, using the algorithm to differentiate the outputs
  app.SetParameterString("out", argv[2] + type + ".tif")

  # This will execute the application and save the output file

Using OTB from QGIS

The processing toolbox

OTB applications are available from QGIS. Use them from the processing toolbox, which is accessible with Processing \rightarrow Toolbox. Switch to “advanced interface” in the bottom of the application widget and OTB applications will be there.


Using a custom OTB

If QGIS cannot find OTB, the “applications folder” and “binaries folder” can be set from the settings in the Processing \rightarrow Settings \rightarrow “service provider”.


On some versions of QGIS, if an existing OTB installation is found, the textfield settings will not be shown. To use a custom OTB instead of the existing one, you will need to replace the otbcli, otbgui and library files in QGIS installation directly.

Advanced applications capabilities

Load/Save OTB-Applications parameters from/to file

Since OTB 3.20, OTB applications parameters can be export/import to/from an XML file using inxml/outxml parameters. Those parameters are available in all applications.

An example is worth a thousand words

otbcli_BandMath -il input_image_1 input_image_2
                -exp "abs(im1b1 - im2b1)"
                -out output_image
                -outxml saved_applications_parameters.xml

Then, you can run the applications with the same parameters using the output XML file previously saved. For this, you have to use the inxml parameter:

otbcli_BandMath -inxml saved_applications_parameters.xml

Note that you can also overload parameters from command line at the same time

otbcli_BandMath -inxml saved_applications_parameters.xml
                -exp "(im1b1 - im2b1)"

In this case it will use as mathematical expression “(im1b1 - im2b1)” instead of “abs(im1b1 - im2b1)”.

Finally, you can also launch applications directly from the command-line launcher executable using the inxml parameter without having to declare the application name. Use in this case:

otbApplicationLauncherCommandLine -inxml saved_applications_parameters.xml

It will retrieve the application name and related parameters from the input XML file and launch in this case the BandMath applications.

In-memory connection between applications

Applications are often use as parts of larger processing chains. Chaining applications currently requires to write/read back images between applications, resulting in heavy I/O operations and a significant amount of time dedicated to writing temporary files.

Since OTB 5.8, it is possible to connect an output image parameter from one application to the input image parameter of the next parameter. This results in the wiring of the internal ITK/OTB pipelines together, allowing to perform image streaming between the applications. There is therefore no more writing of temporary images. The last application of the processing chain is responsible for writing the final result images.

In-memory connection between applications is available both at the C++ API level and using the python bindings to the application presented in the Using the Python interface section.

Here is a Python code sample connecting several applications together:

import otbApplication as otb

app1 = otb.Registry.CreateApplication("Smoothing")
app2 = otb.Registry.CreateApplication("Smoothing")
app3 = otb.Registry.CreateApplication("Smoothing")
app4 = otb.Registry.CreateApplication("ConcatenateImages")

app1.IN = argv[1]

# Connection between app1.out and app2.in

# Execute call is mandatory to wire the pipeline and expose the
# application output. It does not write image

app3.IN = argv[1]

# Execute call is mandatory to wire the pipeline and expose the
# application output. It does not write image

# Connection between app2.out, app3.out and app4.il using images list

app4.OUT = argv[2]

# Call to ExecuteAndWriteOutput() both wires the pipeline and
# actually writes the output, only necessary for last application of
# the chain.

Note: Streaming will only work properly if the application internal implementation does not break it, for instance by using an internal writer to write intermediate data. In this case, execution should still be correct, but some intermediate data will be read or written.

Parallel execution with MPI

Provided that Orfeo ToolBox has been built with MPI and SPTW modules activated, it is possible to use MPI for massive parallel computation and writing of an output image. A simple call to mpirun before the command-line activates this behaviour, with the following logic. MPI writing is only triggered if:

  • OTB is built with MPI and SPTW,
  • The number of MPI processes is greater than 1,
  • The output filename is .tif or .vrt

In this case, the output image will be divided into several tiles according to the number of MPI processes specified to the mpirun command, and all tiles will be computed in parallel.

If the output filename extension is .tif, tiles will be written in parallel to a single Tiff file using SPTW (Simple Parallel Tiff Writer).

If the output filename extension is .vrt, each tile will be written to a separate Tiff file, and a global VRT file will be written.

Here is an example of MPI call on a cluster:

$ mpirun -np $nb_procs --hostfile $PBS_NODEFILE  \
  otbcli_BundleToPerfectSensor \
  -inp $ROOT/IMG_PHR1A_P_001/IMG_PHR1A_P_201605260427149_ORT_1792732101-001_R1C1.JP2 \
  -inxs $ROOT/IMG_PHR1A_MS_002/IMG_PHR1A_MS_201605260427149_ORT_1792732101-002_R1C1.JP2 \
  -out $ROOT/pxs.tif uint16 -ram 1024

  ------------ JOB INFO 1043196.tu-adm01 -------------

  JOBID           : 1043196.tu-adm01
  USER            : michelj
  GROUP           : ctsiap
  JOB NAME        : OTB_mpi
  SESSION         : 631249
  RES REQSTED     : mem=1575000mb,ncpus=560,place=free,walltime=04:00:00
  RES USED        : cpupercent=1553,cput=00:56:12,mem=4784872kb,ncpus=560,vmem=18558416kb,
  BILLING         : 42:46:40 (ncpus x walltime)
  QUEUE           : t72h
  ACCOUNT         : null

------------ END JOB INFO 1043196.tu-adm01 ---------

One can see that the registration and pan-sharpening of the panchromatic and multi-spectral bands of a Pleiades image has bee split among 560 cpus and took only 56 seconds.

Note that this MPI parallel invocation of applications is only available for command-line calls to OTB applications, and only for images output parameters.