Confusion matrix Computation¶

Detailed description¶

This application computes the confusion matrix of a classification map relatively to a ground truth. This ground truth can be given as 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¶

This section describes in details the parameters available for this application. Table [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is ComputeConfusionMatrix .

Input Image The input classification image.

Matrix output Filename to store the output matrix (csv format).

Ground truth Choice of ground truth format. Available choices are:

• Ground truth as a raster image

• Input reference image : Input image containing the ground truth labels.
• Ground truth as a vector data file

• Input reference vector data : Input vector data of the ground truth.
• Field name : Field name containing the label values.

Value for nodata pixels Label for the NoData class. Such input pixels will be discarded from the ground truth and from the input classification map. By default, ‘nodatalabel = 0’.

Available RAM (Mb) Available memory for processing (in MB).

Load otb application from xml file Load otb application from xml file.

Save otb application to xml file Save otb application to xml file.

Example¶

To run this example in command-line, use the following:

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

To run this example from Python, use the following code snippet:

#!/usr/bin/python

# Import the otb applications package
import otbApplication

# The following line creates an instance of the ComputeConfusionMatrix application
ComputeConfusionMatrix = otbApplication.Registry.CreateApplication("ComputeConfusionMatrix")

# The following lines set all the application parameters:
ComputeConfusionMatrix.SetParameterString("in", "clLabeledImageQB1.tif")

ComputeConfusionMatrix.SetParameterString("out", "ConfusionMatrix.csv")

ComputeConfusionMatrix.SetParameterString("ref","vector")

ComputeConfusionMatrix.SetParameterString("ref.vector.in", "VectorData_QB1_bis.shp")

ComputeConfusionMatrix.SetParameterString("ref.vector.field", "Class")

ComputeConfusionMatrix.SetParameterInt("nodatalabel", 255)

# The following line execute the application
ComputeConfusionMatrix.ExecuteAndWriteOutput()