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/*
* Copyright (C) 2005-2022 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* Example usage:
./GenerateTrainingImageExample Input/ROI_QB_MUL_4.tif Input/LearningROIs.txt Output/ROI_QB_MUL_4_training.png
*/
// This example illustrates how to generate a training image for an
// image supervised classification.
#include "itkNumericTraits.h"
#include "otbImage.h"
#include "otbImageFileWriter.h"
#include "otbImageFileReader.h"
#include "itkImageRegionIterator.h"
#include <stdio.h>
#include <iostream>
#include <fstream>
int main(int argc, char* argv[])
{
if (argc != 4)
{
std::cout << "Usage : " << argv[0] << " inputImage roiFile outputTrainingImage" << std::endl;
return EXIT_FAILURE;
}
const char* imageFilename = argv[1];
const char* roiFilename = argv[2];
const char* outputFilename = argv[3];
using InputPixelType = unsigned char;
using OutputPixelType = unsigned char;
const unsigned int Dimension = 2;
using InputImageType = otb::Image<InputPixelType, Dimension>;
using OutputImageType = otb::Image<OutputPixelType, Dimension>;
using ReaderType = otb::ImageFileReader<InputImageType>;
using WriterType = otb::ImageFileWriter<OutputImageType>;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
reader->SetFileName(imageFilename);
writer->SetFileName(outputFilename);
reader->Update();
// We allocate the output image
OutputImageType::Pointer trainingImage = OutputImageType::New();
// Declare the type of the index to access images
using myIndexType = itk::Index<Dimension>;
// Declare the type of the size
using mySizeType = itk::Size<Dimension>;
// Declare the type of the Region
using myRegionType = itk::ImageRegion<Dimension>;
// Define their size, and start index
mySizeType size;
size[0] = reader->GetOutput()->GetRequestedRegion().GetSize()[0];
size[1] = reader->GetOutput()->GetRequestedRegion().GetSize()[1];
myIndexType start;
start[0] = 0;
start[1] = 0;
myRegionType region;
region.SetIndex(start);
region.SetSize(size);
// Initialize Image B
trainingImage->SetLargestPossibleRegion(region);
trainingImage->SetBufferedRegion(region);
trainingImage->SetRequestedRegion(region);
trainingImage->Allocate();
OutputPixelType pix;
pix = itk::NumericTraits<OutputPixelType>::Zero;
trainingImage->FillBuffer(pix);
// For each line of the ROIs file, we create a region iterator and
// assign the value of the labels to the pixels
std::ifstream roisFile;
roisFile.open(roiFilename);
unsigned int nbRois = 0;
roisFile >> nbRois;
std::cout << "Nb of ROIS " << int(nbRois) << std::endl;
while (!roisFile.fail() && (nbRois > 0))
{
--nbRois;
OutputPixelType label = 0;
unsigned long xUL, yUL, xBR, yBR, tmp_label = 0;
roisFile >> tmp_label;
roisFile >> xUL;
roisFile >> yUL;
roisFile >> xBR;
roisFile >> yBR;
label = static_cast<OutputPixelType>(tmp_label);
std::cout << "Label : " << int(label) << std::endl;
std::cout << "( " << xUL << " , " << yUL << " )" << std::endl;
std::cout << "( " << xBR << " , " << yBR << " )" << std::endl;
// Region creation
start[0] = xUL;
start[1] = yUL;
size[0] = xBR - xUL;
size[1] = yBR - yUL;
region.SetSize(size);
region.SetIndex(start);
// Iterator creation
using IteratorType = itk::ImageRegionIterator<OutputImageType>;
IteratorType it(trainingImage, region);
it.GoToBegin();
// Iteration and pixel value assignment
while (!it.IsAtEnd())
{
it.Set(static_cast<OutputPixelType>(label));
// std::cout << (int)static_cast<OutputPixelType>(label) << " -- ";
// std::cout << (int)it.Get() << std::endl;
++it;
}
}
writer->SetInput(trainingImage);
writer->Update();
return EXIT_SUCCESS;
}
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