tests/CaffePreprocessor.cpp

   1 //
   2 // Copyright © 2017 Arm Ltd. All rights reserved.
   3 // SPDX-License-Identifier: MIT
   4 //
   5 #include "InferenceTestImage.hpp"
   6 #include "CaffePreprocessor.hpp"
   7
   8 #include <boost/numeric/conversion/cast.hpp>
   9 #include <boost/format.hpp>
  10
  11 #include <iostream>
  12 #include <fcntl.h>
  13 #include <array>
  14
  15 const std::vector<ImageSet> g_DefaultImageSet =
  16 {
  17     {"shark.jpg", 2}
  18 };
  19
  20 CaffePreprocessor::CaffePreprocessor(const std::string& binaryFileDirectory, unsigned int width, unsigned int height,
  21                                    const std::vector<ImageSet>& imageSet)
  22 :   m_BinaryDirectory(binaryFileDirectory)
  23 ,   m_Height(height)
  24 ,   m_Width(width)
  25 ,   m_ImageSet(imageSet.empty() ? g_DefaultImageSet : imageSet)
  26 {
  27 }
  28
  29 std::unique_ptr<CaffePreprocessor::TTestCaseData> CaffePreprocessor::GetTestCaseData(unsigned int testCaseId)
  30 {
  31     testCaseId = testCaseId % boost::numeric_cast<unsigned int>(m_ImageSet.size());
  32     const ImageSet& imageSet = m_ImageSet[testCaseId];
  33     const std::string fullPath = m_BinaryDirectory + imageSet.first;
  34
  35     InferenceTestImage image(fullPath.c_str());
  36     image.Resize(m_Width, m_Height, CHECK_LOCATION());
  37
  38     // The model expects image data in BGR format.
  39     std::vector<float> inputImageData = GetImageDataInArmNnLayoutAsFloatsSubtractingMean(ImageChannelLayout::Bgr,
  40                                                                                          image, m_MeanBgr);
  41
  42     // List of labels: https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
  43     const unsigned int label = imageSet.second;
  44     return std::make_unique<TTestCaseData>(label, std::move(inputImageData));
  45 }