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/assert.hpp>
  10 #include <boost/format.hpp>
  11
  12 #include <iostream>
  13 #include <fcntl.h>
  14 #include <array>
  15
  16 const std::vector<ImageSet> g_DefaultImageSet =
  17 {
  18     {"shark.jpg", 2}
  19 };
  20
  21 CaffePreprocessor::CaffePreprocessor(const std::string& binaryFileDirectory, unsigned int width, unsigned int height,
  22                                    const std::vector<ImageSet>& imageSet)
  23 :   m_BinaryDirectory(binaryFileDirectory)
  24 ,   m_Height(height)
  25 ,   m_Width(width)
  26 ,   m_ImageSet(imageSet.empty() ? g_DefaultImageSet : imageSet)
  27 {
  28 }
  29
  30 std::unique_ptr<CaffePreprocessor::TTestCaseData> CaffePreprocessor::GetTestCaseData(unsigned int testCaseId)
  31 {
  32     testCaseId = testCaseId % boost::numeric_cast<unsigned int>(m_ImageSet.size());
  33     const ImageSet& imageSet = m_ImageSet[testCaseId];
  34     const std::string fullPath = m_BinaryDirectory + imageSet.first;
  35
  36     InferenceTestImage image(fullPath.c_str());
  37     image.Resize(m_Width, m_Height, CHECK_LOCATION());
  38
  39     // The model expects image data in BGR format.
  40     std::vector<float> inputImageData = GetImageDataInArmNnLayoutAsFloatsSubtractingMean(ImageChannelLayout::Bgr,
  41                                                                                          image, m_MeanBgr);
  42
  43     // List of labels: https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a
  44     const unsigned int label = imageSet.second;
  45     return std::make_unique<TTestCaseData>(label, std::move(inputImageData));
  46 }