diff options
Diffstat (limited to 'tests/ImageTensorGenerator/ImageTensorGenerator.hpp')
| -rw-r--r-- | tests/ImageTensorGenerator/ImageTensorGenerator.hpp | 183 |
1 files changed, 0 insertions, 183 deletions
diff --git a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp b/tests/ImageTensorGenerator/ImageTensorGenerator.hpp deleted file mode 100644 index 4793f822fb..0000000000 --- a/tests/ImageTensorGenerator/ImageTensorGenerator.hpp +++ /dev/null @@ -1,183 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "../InferenceTestImage.hpp" - -#include <armnn/TypesUtils.hpp> - -#include <armnnUtils/Permute.hpp> - -#include <algorithm> -#include <fstream> -#include <iterator> -#include <string> - -// Parameters used in normalizing images -struct NormalizationParameters -{ - float scale{ 1.0 }; - std::array<float, 3> mean{ { 0.0, 0.0, 0.0 } }; - std::array<float, 3> stddev{ { 1.0, 1.0, 1.0 } }; -}; - -enum class SupportedFrontend -{ - Caffe = 0, - TensorFlow = 1, - TFLite = 2, -}; - -/** 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 - * - * @param[in] modelFormat One of the supported frontends - * @param[in] outputType Output type of the image tensor, also the type of the intended model - */ -NormalizationParameters GetNormalizationParameters(const SupportedFrontend& modelFormat, - const armnn::DataType& outputType) -{ - NormalizationParameters normParams; - // Explicitly set default parameters - normParams.scale = 1.0; - normParams.mean = { 0.0, 0.0, 0.0 }; - normParams.stddev = { 1.0, 1.0, 1.0 }; - switch (modelFormat) - { - case SupportedFrontend::Caffe: - break; - case SupportedFrontend::TensorFlow: - case SupportedFrontend::TFLite: - default: - switch (outputType) - { - case armnn::DataType::Float32: - normParams.scale = 127.5; - normParams.mean = { 1.0, 1.0, 1.0 }; - break; - case armnn::DataType::Signed32: - normParams.mean = { 128.0, 128.0, 128.0 }; - break; - case armnn::DataType::QAsymmU8: - default: - break; - } - break; - } - return normParams; -} - -/** Prepare raw image tensor data by loading the image from imagePath and preprocessing it. - * - * @param[in] imagePath Path to the image file - * @param[in] newWidth The new width of the output image tensor - * @param[in] newHeight The new height of the output image tensor - * @param[in] normParams Normalization parameters for the normalization of the image - * @param[in] batchSize Batch size - * @param[in] outputLayout Data layout of the output image tensor - */ -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 float32 image tensor -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) -{ - // Generate image tensor - std::vector<float> imageData; - InferenceTestImage testImage(imagePath.c_str()); - if (newWidth == 0) - { - newWidth = testImage.GetWidth(); - } - if (newHeight == 0) - { - newHeight = testImage.GetHeight(); - } - // Resize the image to new width and height or keep at original dimensions if the new width and height are specified - // as 0 Centre/Normalise the image. - imageData = testImage.Resize(newWidth, newHeight, CHECK_LOCATION(), - InferenceTestImage::ResizingMethods::BilinearAndNormalized, normParams.mean, - normParams.stddev, normParams.scale); - if (outputLayout == armnn::DataLayout::NCHW) - { - // Convert to NCHW format - const armnn::PermutationVector NHWCToArmNN = { 0, 2, 3, 1 }; - armnn::TensorShape dstShape({ batchSize, 3, newHeight, newWidth }); - std::vector<float> tempImage(imageData.size()); - armnnUtils::Permute(dstShape, NHWCToArmNN, imageData.data(), tempImage.data(), sizeof(float)); - imageData.swap(tempImage); - } - return imageData; -} - -// Prepare int32 image tensor -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) -{ - // Get float32 image tensor - std::vector<float> imageDataFloat = - PrepareImageTensor<float>(imagePath, newWidth, newHeight, normParams, batchSize, outputLayout); - // Convert to int32 image tensor with static cast - std::vector<int> imageDataInt; - imageDataInt.reserve(imageDataFloat.size()); - std::transform(imageDataFloat.begin(), imageDataFloat.end(), std::back_inserter(imageDataInt), - [](float val) { return static_cast<int>(val); }); - return imageDataInt; -} - -// Prepare qasymm8 image tensor -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) -{ - // Get float32 image tensor - std::vector<float> imageDataFloat = - PrepareImageTensor<float>(imagePath, newWidth, newHeight, normParams, batchSize, outputLayout); - std::vector<uint8_t> imageDataQasymm8; - imageDataQasymm8.reserve(imageDataFloat.size()); - // Convert to uint8 image tensor with static cast - std::transform(imageDataFloat.begin(), imageDataFloat.end(), std::back_inserter(imageDataQasymm8), - [](float val) { return static_cast<uint8_t>(val); }); - return imageDataQasymm8; -} - -/** Write image tensor to ofstream - * - * @param[in] imageData Image tensor data - * @param[in] imageTensorFile Output filestream (ofstream) to which the image tensor data is written - */ -template <typename ElemType> -void WriteImageTensorImpl(const std::vector<ElemType>& imageData, std::ofstream& imageTensorFile) -{ - std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<ElemType>(imageTensorFile, " ")); -} - -// For uint8_t image tensor, cast it to int before writing it to prevent writing data as characters instead of -// numerical values -template <> -void WriteImageTensorImpl<uint8_t>(const std::vector<uint8_t>& imageData, std::ofstream& imageTensorFile) -{ - std::copy(imageData.begin(), imageData.end(), std::ostream_iterator<int>(imageTensorFile, " ")); -} |