1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "InferenceTestImage.hpp"
7 #include "ImagePreprocessor.hpp"
8
9 #include <armnn/TypesUtils.hpp>
10
11 #include <armnnUtils/Permute.hpp>
12 #include <armnn/utility/NumericCast.hpp>
13
14 #include <iostream>
15 #include <fcntl.h>
16 #include <array>
17
18 template <typename TDataType>
GetLabelAndResizedImageAsFloat(unsigned int testCaseId,std::vector<float> & result)19 unsigned int ImagePreprocessor<TDataType>::GetLabelAndResizedImageAsFloat(unsigned int testCaseId,
20 std::vector<float> & result)
21 {
22 testCaseId = testCaseId % armnn::numeric_cast<unsigned int>(m_ImageSet.size());
23 const ImageSet& imageSet = m_ImageSet[testCaseId];
24 const std::string fullPath = m_BinaryDirectory + imageSet.first;
25
26 InferenceTestImage image(fullPath.c_str());
27
28 // this ResizeBilinear result is closer to the tensorflow one than STB.
29 // there is still some difference though, but the inference results are
30 // similar to tensorflow for MobileNet
31
32 result = image.Resize(m_Width, m_Height, CHECK_LOCATION(),
33 InferenceTestImage::ResizingMethods::BilinearAndNormalized,
34 m_Mean, m_Stddev, m_Scale);
35
36 // duplicate data across the batch
37 for (unsigned int i = 1; i < m_BatchSize; i++)
38 {
39 result.insert(result.end(), result.begin(), result.begin() + armnn::numeric_cast<int>(GetNumImageElements()));
40 }
41
42 if (m_DataFormat == DataFormat::NCHW)
43 {
44 const armnn::PermutationVector NHWCToArmNN = { 0, 2, 3, 1 };
45 armnn::TensorShape dstShape({m_BatchSize, 3, m_Height, m_Width});
46 std::vector<float> tempImage(result.size());
47 armnnUtils::Permute(dstShape, NHWCToArmNN, result.data(), tempImage.data(), sizeof(float));
48 result.swap(tempImage);
49 }
50
51 return imageSet.second;
52 }
53
54 template <>
55 std::unique_ptr<ImagePreprocessor<float>::TTestCaseData>
GetTestCaseData(unsigned int testCaseId)56 ImagePreprocessor<float>::GetTestCaseData(unsigned int testCaseId)
57 {
58 std::vector<float> resized;
59 auto label = GetLabelAndResizedImageAsFloat(testCaseId, resized);
60 return std::make_unique<TTestCaseData>(label, std::move(resized));
61 }
62
63 template <>
64 std::unique_ptr<ImagePreprocessor<uint8_t>::TTestCaseData>
GetTestCaseData(unsigned int testCaseId)65 ImagePreprocessor<uint8_t>::GetTestCaseData(unsigned int testCaseId)
66 {
67 std::vector<float> resized;
68 auto label = GetLabelAndResizedImageAsFloat(testCaseId, resized);
69
70 size_t resizedSize = resized.size();
71 std::vector<uint8_t> quantized(resized.size());
72
73 for (size_t i=0; i<resizedSize; ++i)
74 {
75 quantized[i] = static_cast<uint8_t>(resized[i]);
76 }
77
78 return std::make_unique<TTestCaseData>(label, std::move(quantized));
79 }
80