diff options
author | SiCong Li <sicong.li@arm.com> | 2019-06-24 16:03:33 +0100 |
---|---|---|
committer | sicong.li <sicong.li@arm.com> | 2019-07-15 11:05:36 +0000 |
commit | 898a324d4e5c09e53bbc5925d70577b2f45f753d (patch) | |
tree | 6bc8e8629948959ef3c7c8f1d33ac8abb2d6f6c8 /src/armnnUtils/ModelAccuracyChecker.hpp | |
parent | 454d1f5d5ad2b63ba21cc1ed4a59ac9710991f55 (diff) | |
download | armnn-898a324d4e5c09e53bbc5925d70577b2f45f753d.tar.gz |
MLCE-103 Add necessary enhancements to ModelAccuracyTool
* Evaluate model accuracy using category names instead of numerical
labels.
* Add blacklist support
* Add range selection support
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I7b1d2d298cfcaa56a27a028147169404b73580bb
Diffstat (limited to 'src/armnnUtils/ModelAccuracyChecker.hpp')
-rw-r--r-- | src/armnnUtils/ModelAccuracyChecker.hpp | 93 |
1 files changed, 62 insertions, 31 deletions
diff --git a/src/armnnUtils/ModelAccuracyChecker.hpp b/src/armnnUtils/ModelAccuracyChecker.hpp index cdd2af0ac5..c4dd4f1b05 100644 --- a/src/armnnUtils/ModelAccuracyChecker.hpp +++ b/src/armnnUtils/ModelAccuracyChecker.hpp @@ -5,39 +5,81 @@ #pragma once +#include <algorithm> +#include <armnn/Types.hpp> +#include <boost/assert.hpp> +#include <boost/variant/apply_visitor.hpp> #include <cstddef> -#include <string> +#include <functional> +#include <iostream> #include <map> +#include <string> #include <vector> -#include <boost/variant/apply_visitor.hpp> -#include <iostream> -#include <armnn/Types.hpp> -#include <functional> -#include <algorithm> namespace armnnUtils { using namespace armnn; +// Category names associated with a label +using LabelCategoryNames = std::vector<std::string>; + +/** Split a string into tokens by a delimiter + * + * @param[in] originalString Original string to be split + * @param[in] delimiter Delimiter used to split \p originalString + * @param[in] includeEmptyToekn If true, include empty tokens in the result + * @return A vector of tokens split from \p originalString by \delimiter + */ +std::vector<std::string> + SplitBy(const std::string& originalString, const std::string& delimiter = " ", bool includeEmptyToken = false); + +/** Remove any preceding and trailing character specified in the characterSet. + * + * @param[in] originalString Original string to be stripped + * @param[in] characterSet Set of characters to be stripped from \p originalString + * @return A string stripped of all characters specified in \p characterSet from \p originalString + */ +std::string Strip(const std::string& originalString, const std::string& characterSet = " "); + class ModelAccuracyChecker { public: - ModelAccuracyChecker(const std::map<std::string, int>& validationLabelSet); - + /** Constructor for a model top k accuracy checker + * + * @param[in] validationLabelSet Mapping from names of images to be validated, to category names of their + corresponding ground-truth labels. + * @param[in] modelOutputLabels Mapping from output nodes to the category names of their corresponding labels + Note that an output node can have multiple category names. + */ + ModelAccuracyChecker(const std::map<std::string, std::string>& validationLabelSet, + const std::vector<LabelCategoryNames>& modelOutputLabels); + + /** Get Top K accuracy + * + * @param[in] k The number of top predictions to use for validating the ground-truth label. For example, if \p k is + 3, then a prediction is considered correct as long as the ground-truth appears in the top 3 + predictions. + * @return The accuracy, according to the top \p k th predictions. + */ float GetAccuracy(unsigned int k); - template<typename TContainer> + /** Record the prediction result of an image + * + * @param[in] imageName Name of the image. + * @param[in] outputTensor Output tensor of the network running \p imageName. + */ + template <typename TContainer> void AddImageResult(const std::string& imageName, std::vector<TContainer> outputTensor) { // Increment the total number of images processed ++m_ImagesProcessed; std::map<int, float> confidenceMap; - auto & output = outputTensor[0]; + auto& output = outputTensor[0]; // Create a map of all predictions - boost::apply_visitor([&](auto && value) + boost::apply_visitor([&confidenceMap](auto && value) { int index = 0; for (const auto & o : value) @@ -64,8 +106,7 @@ public: std::set<std::pair<int, float>, Comparator> setOfPredictions( confidenceMap.begin(), confidenceMap.end(), compFunctor); - std::string trimmedName = GetTrimmedImageName(imageName); - int value = m_GroundTruthLabelSet.find(trimmedName)->second; + const std::string correctLabel = m_GroundTruthLabelSet.at(imageName); unsigned int index = 1; for (std::pair<int, float> element : setOfPredictions) @@ -74,7 +115,10 @@ public: { break; } - if (element.first == value) + // Check if the ground truth label value is included in the topi prediction. + // Note that a prediction can have multiple prediction labels. + const LabelCategoryNames predictionLabels = m_ModelOutputLabels[static_cast<size_t>(element.first)]; + if (std::find(predictionLabels.begin(), predictionLabels.end(), correctLabel) != predictionLabels.end()) { ++m_TopK[index]; break; @@ -83,24 +127,11 @@ public: } } - std::string GetTrimmedImageName(const std::string& imageName) const - { - std::string trimmedName; - size_t lastindex = imageName.find_last_of("."); - if(lastindex != std::string::npos) - { - trimmedName = imageName.substr(0, lastindex); - } else - { - trimmedName = imageName; - } - return trimmedName; - } - private: - const std::map<std::string, int> m_GroundTruthLabelSet; - std::vector<unsigned int> m_TopK = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; - unsigned int m_ImagesProcessed = 0; + const std::map<std::string, std::string> m_GroundTruthLabelSet; + const std::vector<LabelCategoryNames> m_ModelOutputLabels; + std::vector<unsigned int> m_TopK = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; + unsigned int m_ImagesProcessed = 0; }; } //namespace armnnUtils |