otbOpenCVUtils.h

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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.
 */
 
#ifndef otbOpenCVUtils_h
#define otbOpenCVUtils_h
 
#if defined(__GNUC__) || defined(__clang__)
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wcast-align"
#include <opencv2/core/core.hpp>
#include <opencv2/core/core_c.h>
#pragma GCC diagnostic pop
#else
#include <opencv2/core/core.hpp>
#include <opencv2/core/core_c.h>
#endif
 
#if defined(__GNUC__) || defined(__clang__)
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Woverloaded-virtual"
#include <opencv2/ml/ml.hpp>
#pragma GCC diagnostic pop
#else
#include <opencv2/ml/ml.hpp>
#endif
 
#include "otb_opencv_api.h"
 
#include "OTBSupervisedExport.h"
 
#include "itkListSample.h"
 
#define CV_TYPE_NAME_ML_SVM "opencv-ml-svm"
#define CV_TYPE_NAME_ML_RTREES "opencv-ml-random-trees"
#define CV_TYPE_NAME_ML_BOOSTING "opencv-ml-boost-tree"
#define CV_TYPE_NAME_ML_ANN_MLP "opencv-ml-ann-mlp"
#define CV_TYPE_NAME_ML_NBAYES "opencv-ml-bayesian"
#define CV_TYPE_NAME_ML_TREE "opencv-ml-tree"
 
#define CvSVM cv::ml::SVM
#define CvANN_MLP_TrainParams cv::ml::ANN_MLP
#define CvANN_MLP cv::ml::ANN_MLP
#define CvBoost cv::ml::Boost
 
#define CV_VAR_NUMERICAL cv::ml::VAR_NUMERICAL
#define CV_VAR_CATEGORICAL cv::ml::VAR_CATEGORICAL
 
 
namespace otb
{
template <class T>
void SampleToMat(const T& sample, cv::Mat& output)
{
  output.create(1, sample.Size(), CV_32FC1);
 
  // Loop on sample size
  for (unsigned int i = 0; i < sample.Size(); ++i)
  {
    output.at<float>(0, i) = sample[i];
  }
}
 
 
template <class T>
void ListSampleToMat(const T* listSample, cv::Mat& output)
{
  // Sample index
  unsigned int sampleIdx = 0;
 
  // Check for valid listSample
  if (listSample != nullptr && listSample->Size() > 0)
  {
    // Retrieve samples count
    unsigned int sampleCount = listSample->Size();
 
    // Build an iterator
    typename T::ConstIterator sampleIt = listSample->Begin();
 
    // Retrieve samples size alike
    const unsigned int sampleSize = listSample->GetMeasurementVectorSize();
 
    // Allocate CvMat
    output.create(sampleCount, sampleSize, CV_32FC1);
 
    // Fill the cv matrix
    for (; sampleIt != listSample->End(); ++sampleIt, ++sampleIdx)
    {
      // Retrieve sample
      typename T::MeasurementVectorType sample = sampleIt.GetMeasurementVector();
 
      // Loop on sample size
      for (unsigned int i = 0; i < sampleSize; ++i)
      {
        output.at<float>(sampleIdx, i) = sample[i];
      }
    }
  }
}
 
template <typename T>
void ListSampleToMat(typename T::Pointer listSample, cv::Mat& output)
{
  return ListSampleToMat(listSample.GetPointer(), output);
}
 
template <typename T>
void ListSampleToMat(typename T::ConstPointer listSample, cv::Mat& output)
{
  return ListSampleToMat(listSample.GetPointer(), output);
}
 
template <typename T>
typename T::Pointer MatToListSample(const cv::Mat& cvmat)
{
  // Build output type
  typename T::Pointer output = T::New();
 
  // Get samples count
  unsigned sampleCount = cvmat.rows;
 
  // Get samples size
  unsigned int sampleSize = cvmat.cols;
 
  // Loop on samples
  for (unsigned int i = 0; i < sampleCount; ++i)
  {
    typename T::MeasurementVectorType sample;
    itk::NumericTraits<typename T::MeasurementVectorType>::SetLength(sample, sampleSize);
 
    unsigned int realSampleSize = sample.Size();
 
    for (unsigned int j = 0; j < realSampleSize; ++j)
    {
      // Don't forget to cast
      sample[j] = static_cast<typename T::MeasurementVectorType::ValueType>(cvmat.at<float>(i, j));
    }
    // PushBack the new sample
    output->PushBack(sample);
  }
  // return the output
  return output;
}
}
 
#endif