From fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf Mon Sep 17 00:00:00 2001 From: Jan Eilers Date: Thu, 25 Feb 2021 17:44:00 +0000 Subject: IVGCVSW-5687 Update Doxygen Docu * Update Doxygen Documentation for 21.02 release Signed-off-by: Jan Eilers Change-Id: I9ed2f9caab038836ea99d7b378d7899fe431a4e5 --- 21.02/_image_tensor_generator_8hpp.xhtml | 580 +++++++++++++++++++++++++++++++ 1 file changed, 580 insertions(+) create mode 100644 21.02/_image_tensor_generator_8hpp.xhtml (limited to '21.02/_image_tensor_generator_8hpp.xhtml') diff --git a/21.02/_image_tensor_generator_8hpp.xhtml b/21.02/_image_tensor_generator_8hpp.xhtml new file mode 100644 index 0000000000..b6d3abe349 --- /dev/null +++ b/21.02/_image_tensor_generator_8hpp.xhtml @@ -0,0 +1,580 @@ + + + + + + + + + + + + + +ArmNN: tests/ImageTensorGenerator/ImageTensorGenerator.hpp File Reference + + + + + + + + + + + + + + + + +
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+  21.02 +
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+Classes | +Enumerations | +Functions
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ImageTensorGenerator.hpp File Reference
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+
#include "../InferenceTestImage.hpp"
+#include <armnn/TypesUtils.hpp>
+#include <armnnUtils/Permute.hpp>
+#include <algorithm>
+#include <fstream>
+#include <iterator>
+#include <string>
+
+

Go to the source code of this file.

+ + + + +

+Classes

struct  NormalizationParameters
 
+ + + +

+Enumerations

enum  SupportedFrontend { Caffe = 0, +TensorFlow = 1, +TFLite = 2 + }
 
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+Functions

NormalizationParameters GetNormalizationParameters (const SupportedFrontend &modelFormat, const armnn::DataType &outputType)
 Get normalization parameters. More...
 
template<typename ElemType >
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. More...
 
template<>
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)
 
template<>
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)
 
template<>
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)
 
template<typename ElemType >
void WriteImageTensorImpl (const std::vector< ElemType > &imageData, std::ofstream &imageTensorFile)
 Write image tensor to ofstream. More...
 
template<>
void WriteImageTensorImpl< uint8_t > (const std::vector< uint8_t > &imageData, std::ofstream &imageTensorFile)
 
+

Enumeration Type Documentation

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◆ SupportedFrontend

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enum SupportedFrontend
+ 		+strong
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Enumerator
Caffe 
TensorFlow 
TFLite 
+ +

Definition at line 25 of file ImageTensorGenerator.hpp.

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26 {
27  Caffe = 0,
28  TensorFlow = 1,
29  TFLite = 2,
30 };
SupportedFrontend::Caffe
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SupportedFrontend::TFLite
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SupportedFrontend::TensorFlow
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Function Documentation

+ +

◆ GetNormalizationParameters()

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NormalizationParameters GetNormalizationParameters (const SupportedFrontend & modelFormat,
const armnn::DataType & outputType 
)
+
+ +

Get normalization parameters.

+

Note that different flavours of models and different model data types have different normalization methods. This tool currently only supports Caffe, TF and TFLite models

+
Parameters
+ + + +
[in]modelFormatOne of the supported frontends
[in]outputTypeOutput type of the image tensor, also the type of the intended model
+
+
+ +

Definition at line 39 of file ImageTensorGenerator.hpp.

+ +

References Caffe, armnn::Float32, NormalizationParameters::mean, armnn::NHWC, PrepareImageTensor(), armnn::QAsymmU8, NormalizationParameters::scale, armnn::Signed32, NormalizationParameters::stddev, TensorFlow, and TFLite.

+ +

Referenced by main().

+
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 }
SupportedFrontend::Caffe
+
SupportedFrontend::TFLite
+ +
SupportedFrontend::TensorFlow
+
NormalizationParameters::stddev
std::array< float, 3 > stddev
Definition: ImageTensorGenerator.hpp:22
+ + +
NormalizationParameters::mean
std::array< float, 3 > mean
Definition: ImageTensorGenerator.hpp:21
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+
+ +

◆ PrepareImageTensor()

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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.

+
Parameters
+ + + + + + + +
[in]imagePathPath to the image file
[in]newWidthThe new width of the output image tensor
[in]newHeightThe new height of the output image tensor
[in]normParamsNormalization parameters for the normalization of the image
[in]batchSizeBatch size
[in]outputLayoutData layout of the output image tensor
+
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+ +

Referenced by GetNormalizationParameters().

+ +
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+ +

◆ PrepareImageTensor< float >()

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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 at line 91 of file ImageTensorGenerator.hpp.

+ +

References InferenceTestImage::BilinearAndNormalized, CHECK_LOCATION, InferenceTestImage::GetWidth(), NormalizationParameters::mean, armnn::NCHW, armnnUtils::NHWCToArmNN, armnnUtils::Permute(), NormalizationParameters::scale, and NormalizationParameters::stddev.

+ +

Referenced by main(), PrepareImageTensor< int >(), and PrepareImageTensor< uint8_t >().

+
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 }
+
NormalizationParameters::stddev
std::array< float, 3 > stddev
Definition: ImageTensorGenerator.hpp:22
+ +
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:131
+
InferenceTestImage::GetWidth
unsigned int GetWidth() const
Definition: InferenceTestImage.hpp:75
+
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:197
+ + +
NormalizationParameters::mean
std::array< float, 3 > mean
Definition: ImageTensorGenerator.hpp:21
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◆ PrepareImageTensor< int >()

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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 at line 128 of file ImageTensorGenerator.hpp.

+ +

References PrepareImageTensor< float >().

+ +

Referenced by main().

+
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 }
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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◆ PrepareImageTensor< uint8_t >()

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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 at line 148 of file ImageTensorGenerator.hpp.

+ +

References PrepareImageTensor< float >().

+ +

Referenced by main().

+
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 }
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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◆ WriteImageTensorImpl()

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void WriteImageTensorImpl (const std::vector< ElemType > & imageData,
std::ofstream & imageTensorFile 
)
+
+ +

Write image tensor to ofstream.

+
Parameters
+ + + +
[in]imageDataImage tensor data
[in]imageTensorFileOutput filestream (ofstream) to which the image tensor data is written
+
+
+ +

Definition at line 172 of file ImageTensorGenerator.hpp.

+ +

Referenced by main().

+
173 {
174  std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<ElemType>(imageTensorFile, " "));
175 }
+
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◆ WriteImageTensorImpl< uint8_t >()

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void WriteImageTensorImpl< uint8_t > (const std::vector< uint8_t > & imageData,
std::ofstream & imageTensorFile 
)
+
+ +

Definition at line 180 of file ImageTensorGenerator.hpp.

+
181 {
182  std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<int>(imageTensorFile, " "));
183 }
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