From 6940dd720ebb6b3d1df8ca203ab696daefe58189 Mon Sep 17 00:00:00 2001 From: Jim Flynn Date: Fri, 20 Mar 2020 12:25:56 +0000 Subject: renamed Documentation folder 20.02 and added .nojekyll file Signed-off-by: Jim Flynn --- 20.02/_image_tensor_generator_8hpp_source.xhtml | 145 ++++++++++++++++++++++++ 1 file changed, 145 insertions(+) create mode 100644 20.02/_image_tensor_generator_8hpp_source.xhtml (limited to '20.02/_image_tensor_generator_8hpp_source.xhtml') diff --git a/20.02/_image_tensor_generator_8hpp_source.xhtml b/20.02/_image_tensor_generator_8hpp_source.xhtml new file mode 100644 index 0000000000..4104e3e576 --- /dev/null +++ b/20.02/_image_tensor_generator_8hpp_source.xhtml @@ -0,0 +1,145 @@ + + + + + + + + + + + + + +ArmNN: tests/ImageTensorGenerator/ImageTensorGenerator.hpp Source File + + + + + + + + + + + + + + + + +
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ImageTensorGenerator.hpp
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+Go to the documentation of this file.
1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "../InferenceTestImage.hpp"
7 
8 #include <armnn/TypesUtils.hpp>
9 
10 #include <armnnUtils/Permute.hpp>
11 
12 #include <algorithm>
13 #include <fstream>
14 #include <iterator>
15 #include <string>
16 
17 // Parameters used in normalizing images
18 struct NormalizationParameters
19 {
20  float scale{ 1.0 };
21  std::array<float, 3> mean{ { 0.0, 0.0, 0.0 } };
22  std::array<float, 3> stddev{ { 1.0, 1.0, 1.0 } };
23 };
24 
25 enum class SupportedFrontend
26 {
27  Caffe = 0,
28  TensorFlow = 1,
29  TFLite = 2,
30 };
31 
32 /** Get normalization parameters.
33  * Note that different flavours of models and different model data types have different normalization methods.
34  * This tool currently only supports Caffe, TF and TFLite models
35  *
36  * @param[in] modelFormat One of the supported frontends
37  * @param[in] outputType Output type of the image tensor, also the type of the intended model
38  */
39 NormalizationParameters GetNormalizationParameters(const SupportedFrontend& modelFormat,
40  const armnn::DataType& outputType)
41 {
42  NormalizationParameters normParams;
43  // Explicitly set default parameters
44  normParams.scale = 1.0;
45  normParams.mean = { 0.0, 0.0, 0.0 };
46  normParams.stddev = { 1.0, 1.0, 1.0 };
47  switch (modelFormat)
48  {
49  case SupportedFrontend::Caffe:
50  break;
51  case SupportedFrontend::TensorFlow:
52  case SupportedFrontend::TFLite:
53  default:
54  switch (outputType)
55  {
56  case armnn::DataType::Float32:
57  normParams.scale = 127.5;
58  normParams.mean = { 1.0, 1.0, 1.0 };
59  break;
60  case armnn::DataType::Signed32:
61  normParams.mean = { 128.0, 128.0, 128.0 };
62  break;
63  case armnn::DataType::QAsymmU8:
64  default:
65  break;
66  }
67  break;
68  }
69  return normParams;
70 }
71 
72 /** Prepare raw image tensor data by loading the image from imagePath and preprocessing it.
73  *
74  * @param[in] imagePath Path to the image file
75  * @param[in] newWidth The new width of the output image tensor
76  * @param[in] newHeight The new height of the output image tensor
77  * @param[in] normParams Normalization parameters for the normalization of the image
78  * @param[in] batchSize Batch size
79  * @param[in] outputLayout Data layout of the output image tensor
80  */
81 template <typename ElemType>
82 std::vector<ElemType> PrepareImageTensor(const std::string& imagePath,
83  unsigned int newWidth,
84  unsigned int newHeight,
85  const NormalizationParameters& normParams,
86  unsigned int batchSize = 1,
87  const armnn::DataLayout& outputLayout = armnn::DataLayout::NHWC);
88 
89 // Prepare float32 image tensor
90 template <>
91 std::vector<float> PrepareImageTensor<float>(const std::string& imagePath,
92  unsigned int newWidth,
93  unsigned int newHeight,
94  const NormalizationParameters& normParams,
95  unsigned int batchSize,
96  const armnn::DataLayout& outputLayout)
97 {
98  // Generate image tensor
99  std::vector<float> imageData;
100  InferenceTestImage testImage(imagePath.c_str());
101  if (newWidth == 0)
102  {
103  newWidth = testImage.GetWidth();
104  }
105  if (newHeight == 0)
106  {
107  newHeight = testImage.GetHeight();
108  }
109  // Resize the image to new width and height or keep at original dimensions if the new width and height are specified
110  // as 0 Centre/Normalise the image.
111  imageData = testImage.Resize(newWidth, newHeight, CHECK_LOCATION(),
112  InferenceTestImage::ResizingMethods::BilinearAndNormalized, normParams.mean,
113  normParams.stddev, normParams.scale);
114  if (outputLayout == armnn::DataLayout::NCHW)
115  {
116  // Convert to NCHW format
117  const armnn::PermutationVector NHWCToArmNN = { 0, 2, 3, 1 };
118  armnn::TensorShape dstShape({ batchSize, 3, newHeight, newWidth });
119  std::vector<float> tempImage(imageData.size());
120  armnnUtils::Permute(dstShape, NHWCToArmNN, imageData.data(), tempImage.data(), sizeof(float));
121  imageData.swap(tempImage);
122  }
123  return imageData;
124 }
125 
126 // Prepare int32 image tensor
127 template <>
128 std::vector<int> PrepareImageTensor<int>(const std::string& imagePath,
129  unsigned int newWidth,
130  unsigned int newHeight,
131  const NormalizationParameters& normParams,
132  unsigned int batchSize,
133  const armnn::DataLayout& outputLayout)
134 {
135  // Get float32 image tensor
136  std::vector<float> imageDataFloat =
137  PrepareImageTensor<float>(imagePath, newWidth, newHeight, normParams, batchSize, outputLayout);
138  // Convert to int32 image tensor with static cast
139  std::vector<int> imageDataInt;
140  imageDataInt.reserve(imageDataFloat.size());
141  std::transform(imageDataFloat.begin(), imageDataFloat.end(), std::back_inserter(imageDataInt),
142  [](float val) { return static_cast<int>(val); });
143  return imageDataInt;
144 }
145 
146 // Prepare qasymm8 image tensor
147 template <>
148 std::vector<uint8_t> PrepareImageTensor<uint8_t>(const std::string& imagePath,
149  unsigned int newWidth,
150  unsigned int newHeight,
151  const NormalizationParameters& normParams,
152  unsigned int batchSize,
153  const armnn::DataLayout& outputLayout)
154 {
155  // Get float32 image tensor
156  std::vector<float> imageDataFloat =
157  PrepareImageTensor<float>(imagePath, newWidth, newHeight, normParams, batchSize, outputLayout);
158  std::vector<uint8_t> imageDataQasymm8;
159  imageDataQasymm8.reserve(imageDataFloat.size());
160  // Convert to uint8 image tensor with static cast
161  std::transform(imageDataFloat.begin(), imageDataFloat.end(), std::back_inserter(imageDataQasymm8),
162  [](float val) { return static_cast<uint8_t>(val); });
163  return imageDataQasymm8;
164 }
165 
166 /** Write image tensor to ofstream
167  *
168  * @param[in] imageData Image tensor data
169  * @param[in] imageTensorFile Output filestream (ofstream) to which the image tensor data is written
170  */
171 template <typename ElemType>
172 void WriteImageTensorImpl(const std::vector<ElemType>& imageData, std::ofstream& imageTensorFile)
173 {
174  std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<ElemType>(imageTensorFile, " "));
175 }
176 
177 // For uint8_t image tensor, cast it to int before writing it to prevent writing data as characters instead of
178 // numerical values
179 template <>
180 void WriteImageTensorImpl<uint8_t>(const std::vector<uint8_t>& imageData, std::ofstream& imageTensorFile)
181 {
182  std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<int>(imageTensorFile, " "));
183 }
+
armnn::DataLayout
DataLayout
Definition: Types.hpp:49
+
SupportedFrontend::Caffe
+
SupportedFrontend::TFLite
+ +
SupportedFrontend::TensorFlow
+
NormalizationParameters::stddev
std::array< float, 3 > stddev
Definition: ImageTensorGenerator.hpp:22
+
GetNormalizationParameters
NormalizationParameters GetNormalizationParameters(const SupportedFrontend &modelFormat, const armnn::DataType &outputType)
Get normalization parameters.
Definition: ImageTensorGenerator.hpp:39
+
PrepareImageTensor
std::vector< ElemType > PrepareImageTensor(const std::string &imagePath, unsigned int newWidth, unsigned int newHeight, const NormalizationParameters &normParams, unsigned int batchSize=1, const armnn::DataLayout &outputLayout=armnn::DataLayout::NHWC)
Prepare raw image tensor data by loading the image from imagePath and preprocessing it...
+
WriteImageTensorImpl
void WriteImageTensorImpl(const std::vector< ElemType > &imageData, std::ofstream &imageTensorFile)
Write image tensor to ofstream.
Definition: ImageTensorGenerator.hpp:172
+
PrepareImageTensor< uint8_t >
std::vector< uint8_t > PrepareImageTensor< uint8_t >(const std::string &imagePath, unsigned int newWidth, unsigned int newHeight, const NormalizationParameters &normParams, unsigned int batchSize, const armnn::DataLayout &outputLayout)
Definition: ImageTensorGenerator.hpp:148
+ +
armnnUtils::NHWCToArmNN
const armnn::PermutationVector NHWCToArmNN
Definition: ParserHelper.cpp:16
+
armnnUtils::Permute
void Permute(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)
Definition: Permute.cpp:121
+
TypesUtils.hpp
+ +
Permute.hpp
+
armnn::DataType
DataType
Definition: Types.hpp:32
+
InferenceTestImage::GetWidth
unsigned int GetWidth() const
Definition: InferenceTestImage.hpp:75
+ +
WriteImageTensorImpl< uint8_t >
void WriteImageTensorImpl< uint8_t >(const std::vector< uint8_t > &imageData, std::ofstream &imageTensorFile)
Definition: ImageTensorGenerator.hpp:180
+
PrepareImageTensor< int >
std::vector< int > PrepareImageTensor< int >(const std::string &imagePath, unsigned int newWidth, unsigned int newHeight, const NormalizationParameters &normParams, unsigned int batchSize, const armnn::DataLayout &outputLayout)
Definition: ImageTensorGenerator.hpp:128
+
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:192
+ + +
NormalizationParameters::mean
std::array< float, 3 > mean
Definition: ImageTensorGenerator.hpp:21
+ + +
SupportedFrontend
SupportedFrontend
Definition: ImageTensorGenerator.hpp:25
+ +
PrepareImageTensor< float >
std::vector< float > PrepareImageTensor< float >(const std::string &imagePath, unsigned int newWidth, unsigned int newHeight, const NormalizationParameters &normParams, unsigned int batchSize, const armnn::DataLayout &outputLayout)
Definition: ImageTensorGenerator.hpp:91
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