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Commit 4596b516 authored by Jonathan Guinet's avatar Jonathan Guinet
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COMP: missing file.

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/*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
// Software Guide : BeginCommandLineArgs
// INPUTS: {ROI_QB_MUL_1.png}
// OUTPUTS: {MSLabeledOutput.tif}, {MSClusteredOutput.tif} {MSLabeledOutput-pretty.png}, {MSClusteredOutput-pretty.png}
// 16 16 100 100 0.1
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// This example demonstrates the use of the
// \doxygen{otb}{MeanShiftSegmentationFilter} class which implements
// filtering and clustering using the mean shift algorithm
// \cite{Comaniciu2002}. For a given pixel, the mean shift will
// build a set of neighboring pixels within a given spatial radius
// and a color range. The spatial and color center of this set is
// then computed and the algorithm iterates with this new spatial and
// color center. The Mean Shift can be used for edge-preserving
// smoothing, or for clustering.
//
// Software Guide : EndLatex
#include "itkMacro.h"
#include "otbVectorImage.h"
#include "otbImageFileReader.h"
#include "otbStreamingImageFileWriter.h"
#include "otbImageFileWriter.h"
#include "otbPrintableImageFilter.h"
#include "itkRGBPixel.h"
#include "itkScalarToRGBPixelFunctor.h"
#include "itkUnaryFunctorImageFilter.h"
// Software Guide : BeginLatex
//
// We start by including the needed header file.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "otbMeanShiftSegmentationFilter.h"
// Software Guide : EndCodeSnippet
int main(int argc, char * argv[])
{
if (argc != 11)
{
std::cerr << "Usage: " << argv[0]
<< " infname labeledfname clusteredfname labeledpretty clusteredpretty "
<< "spatialRadius rangeRadius minRegionSize maxiter thres"
<< std::endl;
return EXIT_FAILURE;
}
const char * infname = argv[1];
const char * labeledfname = argv[2];
const char * clusteredfname = argv[3];
const char * labeledpretty = argv[4];
const char * clusteredpretty = argv[5];
const unsigned int spatialRadius = atoi(argv[6]);
const double rangeRadius = atof(argv[7]);
const unsigned int minRegionSize = atoi(argv[8]);
const unsigned int maxiter = atoi(argv[9]);
const double thres = atof(argv[10]);
// Software Guide : BeginLatex
//
// We start by the classical \code{typedef}s needed for reading and
// writing the images.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
const unsigned int Dimension = 2;
typedef float PixelType;
typedef unsigned int LabelPixelType ;
typedef itk::RGBPixel<unsigned char> ColorPixelType;
typedef otb::VectorImage<PixelType, Dimension> ImageType;
typedef otb::Image<LabelPixelType, Dimension> LabelImageType;
typedef otb::Image<ColorPixelType, Dimension> RGBImageType;
typedef otb::ImageFileReader<ImageType> ReaderType;
typedef otb::StreamingImageFileWriter<ImageType> WriterType;
typedef otb::StreamingImageFileWriter<LabelImageType> LabelWriterType;
typedef otb::MeanShiftSegmentationFilter<ImageType, LabelImageType, ImageType> FilterType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We instantiate the filter, the reader, and 2 writers (for the
// labeled and clustered images ):
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
FilterType::Pointer filter = FilterType::New();
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer1 = WriterType::New();
LabelWriterType::Pointer writer2 = LabelWriterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We set the file names for the reader and the writers:
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
reader->SetFileName(infname);
writer1->SetFileName(clusteredfname);
writer2->SetFileName(labeledfname);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We can now set the parameters for the filter. There are 3 main
// parameters: the spatial radius used for defining the neighborhood,
// the range radius used for defining the interval in the color space
// and the minimum size for the regions to be kept after clustering.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetSpatialBandwidth(spatialRadius);
filter->SetRangeBandwidth(rangeRadius);
filter->SetMinRegionSize(minRegionSize);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Two another parameters can be set the maximum iteration number, which define maximum number of iteration until convergence.
// Algorithm iterative scheme will stop if convergence hasn't been reached after the maximum number of iterations.
// Threshold parameter defines mean-shift vector convergence value. Algorithm iterative scheme will stop if mean-shift vector is below this threshold or if iteration number reached maximum number of iterations.
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetMaxIterationNumber(maxiter);
filter->SetThreshold(thres);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We can now plug the pipeline and run it.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetInput(reader->GetOutput());
writer1->SetInput(filter->GetClusteredOutput());
writer2->SetInput(filter->GetLabelOutput());
writer1->Update();
writer2->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
// Figure~\ref{fig:MeanShiftSegmentationFilter} shows the result of applying the mean shift
// to a Quickbird image.
// \begin{figure}
// \center
// \includegraphics[width=0.40\textwidth]{ROI_QB_MUL_1.eps}
// \includegraphics[width=0.40\textwidth]{MSClusteredOutput-pretty.eps}
// \includegraphics[width=0.40\textwidth]{MSLabeledOutput-pretty.eps}
// \itkcaption[Mean Shift]{From top to bottom and left to right:
// Original image, image filtered by
// mean shift after clustering clustering, and labeled image..}
// \label{fig:MeanShiftSegmentationFilter}
// \end{figure}
// Software Guide : EndLatex
typedef otb::PrintableImageFilter<ImageType> PrintableFilterType;
PrintableFilterType::Pointer printableImageFilter = PrintableFilterType::New();
printableImageFilter->SetChannel(1);
printableImageFilter->SetChannel(2);
printableImageFilter->SetChannel(3);
typedef PrintableFilterType::OutputImageType OutputImageType;
typedef otb::ImageFileWriter<OutputImageType> PrettyWriterType;
PrettyWriterType::Pointer prettyWriter = PrettyWriterType::New();
printableImageFilter->SetInput(filter->GetClusteredOutput());
prettyWriter->SetFileName(clusteredpretty);
prettyWriter->SetInput(printableImageFilter->GetOutput());
prettyWriter->Update();
typedef otb::ImageFileWriter<RGBImageType> LabelRGBWriterType;
LabelRGBWriterType::Pointer labelRGBWriter = LabelRGBWriterType::New();
// Label to RGB image
typedef itk::Functor::ScalarToRGBPixelFunctor<LabelPixelType> FunctorType;
typedef itk::UnaryFunctorImageFilter<LabelImageType, RGBImageType,
FunctorType> ColorLabelFilterType;
ColorLabelFilterType::Pointer labelToRGB = ColorLabelFilterType::New();
labelToRGB->SetInput(filter->GetLabelOutput());
labelRGBWriter->SetFileName(labeledpretty);
labelRGBWriter->SetInput(labelToRGB->GetOutput());
labelRGBWriter->Update();
return EXIT_SUCCESS;
}
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