.. _ComputeConfusionMatrix: 

ComputeConfusionMatrix
======================





Computes the confusion matrix of a classification

Description
-----------

This application computes the confusion matrix of a classification map relative to a ground truth dataset. The ground truth can be provided as either a raster or a vector data. Only reference and produced pixels with values different from NoData are handled in the calculation of the confusion matrix. The confusion matrix is organized the following way: rows = reference labels, columns = produced labels. In the header of the output file, the reference and produced class labels are ordered according to the rows/columns of the confusion matrix.



Parameters
----------

.. contents:: :local:

.. |br| raw:: html

   <br />

.. |em| raw:: html

   &emsp;

**Input Image** :code:`-in image` *Mandatory* |br|
The input classification image.

**Matrix output** :code:`-out filename [dtype]` *Mandatory* |br|
Filename to store the output matrix (csv format)

**set the output format to contingency table or confusion matrix** :code:`-format [confusionmatrix|contingencytable]` *Default value: confusionmatrix* |br|
Choice of the output format as a contingency table for unsupervised algorithmsor confusion matrix for supervised ones.

* **Choice of a confusion matrix as output.** |br| 

* **Choice of a contingency table as output.** |br| 



**Ground truth** :code:`-ref [raster|vector]` *Default value: raster* |br|
Choice of ground truth format

* **Ground truth as a raster image** |br| 

* **Ground truth as a vector data file** |br| 



Ground truth as a raster image options
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

**Input reference image** :code:`-ref.raster.in image` *Mandatory* |br|
Input image containing the ground truth labels

**Value for nodata pixels in the reference raster** :code:`-ref.raster.nodata int` *Default value: 0* |br|
Label to be treated as nodata in the reference raster.

Ground truth as a vector data file options
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

**Input reference vector data** :code:`-ref.vector.in vectorfile` *Mandatory* |br|
Input vector data of the ground truth

**Field name** :code:`-ref.vector.field string` |br|
Field name containing the label values

**Value for nodata pixels in the reference vector** :code:`-ref.vector.nodata int` *Default value: 0* |br|
Label to be treated as nodata in the reference vector. Please note that this value is always used in vector mode, to generate default values. Please set it to a value that does not correspond to a class label.



------------

**Value for nodata pixels in the input image** :code:`-nodatalabel int` *Default value: 0* |br|
Label to be treated as nodata in the input image

**Available RAM (MB)** :code:`-ram int` *Default value: 256* |br|
Available memory for processing (in MB).



Examples
--------

From the command-line:

.. code-block:: bash

    otbcli_ComputeConfusionMatrix -in clLabeledImageQB1.tif -out ConfusionMatrix.csv -ref vector -ref.vector.in VectorData_QB1_bis.shp -ref.vector.field Class -ref.vector.nodata 255


From Python:

.. code-block:: python

	import otbApplication

	app = otbApplication.Registry.CreateApplication("ComputeConfusionMatrix")

	app.SetParameterString("in", "clLabeledImageQB1.tif")
	app.SetParameterString("out", "ConfusionMatrix.csv")
	app.SetParameterString("ref","vector")
	app.SetParameterString("ref.vector.in", "VectorData_QB1_bis.shp")
	app.SetParameterString("ref.vector.field", "Class")
	app.SetParameterInt("ref.vector.nodata", 255)

	app.ExecuteAndWriteOutput()