IVGCVSW-2900 Adding the Accuracy Checker Tool and tests

Change-Id: I4ac325e45f2236b8e0757d21046f117024ce3979
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>

3 files changed, 232 insertions, 0 deletions

diff --git a/src/armnn/test/ModelAccuracyCheckerTest.cpp b/src/armnn/test/ModelAccuracyCheckerTest.cpp
new file mode 100644
index 0000000000..f3a6c9d81d
--- /dev/null
+++ b/src/armnn/test/ModelAccuracyCheckerTest.cpp
@@ -0,0 +1,98 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#include "ModelAccuracyChecker.hpp"
+
+#include <boost/algorithm/string.hpp>
+#include <boost/test/unit_test.hpp>
+
+#include <iostream>
+#include <string>
+#include <boost/log/core/core.hpp>
+#include <boost/filesystem.hpp>
+#include <boost/optional.hpp>
+#include <boost/variant.hpp>
+
+using namespace armnnUtils;
+
+struct TestHelper {
+    const std::map<std::string, int> GetValidationLabelSet()
+    {
+        std::map<std::string, int> validationLabelSet;
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000001", 2));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000002", 9));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000003", 1));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000004", 6));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000005", 5));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000006", 0));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000007", 8));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000008", 4));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000009", 3));
+        validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000009", 7));
+
+        return validationLabelSet;
+    }
+};
+
+BOOST_AUTO_TEST_SUITE(ModelAccuracyCheckerTest)
+
+using TContainer = boost::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>>;
+
+BOOST_FIXTURE_TEST_CASE(TestFloat32OutputTensorAccuracy, TestHelper)
+{
+    ModelAccuracyChecker checker(GetValidationLabelSet());
+
+    // Add image 1 and check accuracy
+    std::vector<float> inferenceOutputVector1 = {0.05f, 0.10f, 0.70f, 0.15f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f};
+    TContainer inference1Container(inferenceOutputVector1);
+    std::vector<TContainer> outputTensor1;
+    outputTensor1.push_back(inference1Container);
+
+    std::string imageName = "ILSVRC2012_val_00000001.JPEG";
+    checker.AddImageResult<TContainer>(imageName, outputTensor1);
+
+    // Top 1 Accuracy
+    float totalAccuracy = checker.GetAccuracy(1);
+    BOOST_CHECK(totalAccuracy == 100.0f);
+
+    // Add image 2 and check accuracy
+    std::vector<float> inferenceOutputVector2 = {0.10f, 0.0f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
+    TContainer inference2Container(inferenceOutputVector2);
+    std::vector<TContainer> outputTensor2;
+    outputTensor2.push_back(inference2Container);
+
+    imageName = "ILSVRC2012_val_00000002.JPEG";
+    checker.AddImageResult<TContainer>(imageName, outputTensor2);
+
+    // Top 1 Accuracy
+    totalAccuracy = checker.GetAccuracy(1);
+    BOOST_CHECK(totalAccuracy == 50.0f);
+
+    // Top 2 Accuracy
+    totalAccuracy = checker.GetAccuracy(2);
+    BOOST_CHECK(totalAccuracy == 100.0f);
+
+    // Add image 3 and check accuracy
+    std::vector<float> inferenceOutputVector3 = {0.0f, 0.10f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
+    TContainer inference3Container(inferenceOutputVector3);
+    std::vector<TContainer> outputTensor3;
+    outputTensor3.push_back(inference3Container);
+
+    imageName = "ILSVRC2012_val_00000003.JPEG";
+    checker.AddImageResult<TContainer>(imageName, outputTensor3);
+
+    // Top 1 Accuracy
+    totalAccuracy = checker.GetAccuracy(1);
+    BOOST_CHECK(totalAccuracy == 33.3333321f);
+
+    // Top 2 Accuracy
+    totalAccuracy = checker.GetAccuracy(2);
+    BOOST_CHECK(totalAccuracy == 66.6666641f);
+
+    // Top 3 Accuracy
+    totalAccuracy = checker.GetAccuracy(3);
+    BOOST_CHECK(totalAccuracy == 100.0f);
+}
+
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnUtils/ModelAccuracyChecker.cpp b/src/armnnUtils/ModelAccuracyChecker.cpp
new file mode 100644
index 0000000000..bee5ca2365
--- /dev/null
+++ b/src/armnnUtils/ModelAccuracyChecker.cpp
@@ -0,0 +1,31 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <vector>
+#include <map>
+#include <boost/log/trivial.hpp>
+#include "ModelAccuracyChecker.hpp"
+
+namespace armnnUtils
+{
+
+armnnUtils::ModelAccuracyChecker::ModelAccuracyChecker(const std::map<std::string, int>& validationLabels)
+    : m_GroundTruthLabelSet(validationLabels){}
+
+float ModelAccuracyChecker::GetAccuracy(unsigned int k)
+{
+    if(k > 10) {
+        BOOST_LOG_TRIVIAL(info) << "Accuracy Tool only supports a maximum of Top 10 Accuracy. "
+                                   "Printing Top 10 Accuracy result!";
+        k = 10;
+    }
+    unsigned int total = 0;
+    for (unsigned int i = k; i > 0; --i)
+    {
+        total += m_TopK[i];
+    }
+    return static_cast<float>(total * 100) / static_cast<float>(m_ImagesProcessed);
+}
+}
\ No newline at end of file
diff --git a/src/armnnUtils/ModelAccuracyChecker.hpp b/src/armnnUtils/ModelAccuracyChecker.hpp
new file mode 100644
index 0000000000..abf994b5e1
--- /dev/null
+++ b/src/armnnUtils/ModelAccuracyChecker.hpp
@@ -0,0 +1,103 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <cstddef>
+#include <string>
+#include <map>
+#include <vector>
+#include <boost/variant/apply_visitor.hpp>
+#include <iostream>
+#include <armnn/Types.hpp>
+#include <functional>
+#include <algorithm>
+
+namespace armnnUtils
+{
+
+using namespace armnn;
+
+class ModelAccuracyChecker
+{
+public:
+    ModelAccuracyChecker(const std::map<std::string, int>& validationLabelSet);
+
+    float GetAccuracy(unsigned int k);
+
+    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];
+
+        // Create a map of all predictions
+        boost::apply_visitor([&](auto && value)
+                             {
+                                 int index = 0;
+                                 for (const auto & o : value)
+                                 {
+                                     if (o > 0)
+                                     {
+                                         confidenceMap.insert(std::pair<int, float>(index, static_cast<float>(o)));
+                                     }
+                                     ++index;
+                                 }
+                             },
+                             output);
+
+        // Create a comparator for sorting the map in order of highest probability
+        typedef std::function<bool(std::pair<int, float>, std::pair<int, float>)> Comparator;
+
+        Comparator compFunctor =
+            [](std::pair<int, float> element1, std::pair<int, float> element2)
+            {
+                return element1.second > element2.second;
+            };
+
+        // Do the sorting and store in an ordered set
+        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;
+
+        unsigned int index = 1;
+        for (std::pair<int, float> element : setOfPredictions)
+        {
+            if(element.first == value)
+            {
+                ++m_TopK[index];
+            } else
+            {
+                ++index;
+            }
+        }
+    }
+
+    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;
+};
+} //namespace armnnUtils
+