IVGCVSW-2559 End to end tests for Detection PostProcess

* end to end tests for Detection PostProcess float and uint8
* add anchors to AddDetectionPostProcessLayer
* add anchors to VisitDetectionPostProcessLayer
* refactor code

Change-Id: I3c5a9a4a60b74c2246b4a27692bbf3c235163f90
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>

3 files changed, 167 insertions, 1 deletions

diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 80a9cfeaa9..4a1d467bb7 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -14,6 +14,7 @@ list(APPEND armnnBackendsCommonUnitTests_sources
     ConvertFp16ToFp32TestImpl.hpp
     ConvertFp32ToFp16TestImpl.hpp
     DebugTestImpl.hpp
+    DetectionPostProcessTestImpl.hpp
     EndToEndTestImpl.hpp
     FullyConnectedTestImpl.hpp
     GatherTestImpl.hpp
diff --git a/src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp b/src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp
new file mode 100644
index 0000000000..5f4d2a480f
--- /dev/null
+++ b/src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp
@@ -0,0 +1,162 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/INetwork.hpp>
+#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <TypeUtils.hpp>
+
+namespace{
+
+template<typename T>
+armnn::INetworkPtr CreateDetectionPostProcessNetwork(const armnn::TensorInfo& boxEncodingsInfo,
+                                                     const armnn::TensorInfo& scoresInfo,
+                                                     const armnn::TensorInfo& anchorsInfo,
+                                                     const std::vector<T>& anchors,
+                                                     bool useRegularNms)
+{
+    armnn::TensorInfo detectionBoxesInfo({ 1, 3, 4 }, armnn::DataType::Float32);
+    armnn::TensorInfo detectionScoresInfo({ 1, 3 }, armnn::DataType::Float32);
+    armnn::TensorInfo detectionClassesInfo({ 1, 3 }, armnn::DataType::Float32);
+    armnn::TensorInfo numDetectionInfo({ 1 }, armnn::DataType::Float32);
+
+    armnn::DetectionPostProcessDescriptor desc;
+    desc.m_UseRegularNms = useRegularNms;
+    desc.m_MaxDetections = 3;
+    desc.m_MaxClassesPerDetection = 1;
+    desc.m_DetectionsPerClass =1;
+    desc.m_NmsScoreThreshold = 0.0;
+    desc.m_NmsIouThreshold = 0.5;
+    desc.m_NumClasses = 2;
+    desc.m_ScaleY = 10.0;
+    desc.m_ScaleX = 10.0;
+    desc.m_ScaleH = 5.0;
+    desc.m_ScaleW = 5.0;
+
+    armnn::INetworkPtr net(armnn::INetwork::Create());
+
+    armnn::IConnectableLayer* boxesLayer = net->AddInputLayer(0);
+    armnn::IConnectableLayer* scoresLayer = net->AddInputLayer(1);
+    armnn::ConstTensor anchorsTensor(anchorsInfo, anchors.data());
+    armnn::IConnectableLayer* detectionLayer = net->AddDetectionPostProcessLayer(desc, anchorsTensor,
+                                                                                 "DetectionPostProcess");
+    armnn::IConnectableLayer* detectionBoxesLayer = net->AddOutputLayer(0, "detectionBoxes");
+    armnn::IConnectableLayer* detectionClassesLayer = net->AddOutputLayer(1, "detectionClasses");
+    armnn::IConnectableLayer* detectionScoresLayer = net->AddOutputLayer(2, "detectionScores");
+    armnn::IConnectableLayer* numDetectionLayer = net->AddOutputLayer(3, "numDetection");
+    Connect(boxesLayer, detectionLayer, boxEncodingsInfo, 0, 0);
+    Connect(scoresLayer, detectionLayer, scoresInfo, 0, 1);
+    Connect(detectionLayer, detectionBoxesLayer, detectionBoxesInfo, 0, 0);
+    Connect(detectionLayer, detectionClassesLayer, detectionClassesInfo, 1, 0);
+    Connect(detectionLayer, detectionScoresLayer, detectionScoresInfo, 2, 0);
+    Connect(detectionLayer, numDetectionLayer, numDetectionInfo, 3, 0);
+
+    return net;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DetectionPostProcessEndToEnd(const std::vector<BackendId>& backends, bool useRegularNms,
+                                  const std::vector<T>& boxEncodings,
+                                  const std::vector<T>& scores,
+                                  const std::vector<T>& anchors,
+                                  const std::vector<float>& expectedDetectionBoxes,
+                                  const std::vector<float>& expectedDetectionClasses,
+                                  const std::vector<float>& expectedDetectionScores,
+                                  const std::vector<float>& expectedNumDetections,
+                                  float boxScale = 1.0f,
+                                  int32_t boxOffset = 0,
+                                  float scoreScale = 1.0f,
+                                  int32_t scoreOffset = 0,
+                                  float anchorScale = 1.0f,
+                                  int32_t anchorOffset = 0)
+{
+    armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, ArmnnType);
+    armnn::TensorInfo scoresInfo({ 1, 6, 3}, ArmnnType);
+    armnn::TensorInfo anchorsInfo({ 6, 4 }, ArmnnType);
+
+    boxEncodingsInfo.SetQuantizationScale(boxScale);
+    boxEncodingsInfo.SetQuantizationOffset(boxOffset);
+    scoresInfo.SetQuantizationScale(scoreScale);
+    scoresInfo.SetQuantizationOffset(scoreOffset);
+    anchorsInfo.SetQuantizationScale(anchorScale);
+    anchorsInfo.SetQuantizationOffset(anchorOffset);
+
+    // Builds up the structure of the network
+    armnn::INetworkPtr net = CreateDetectionPostProcessNetwork<T>(boxEncodingsInfo, scoresInfo,
+                                                                  anchorsInfo, anchors, useRegularNms);
+
+    BOOST_TEST_CHECKPOINT("create a network");
+
+    std::map<int, std::vector<T>> inputTensorData = {{ 0, boxEncodings }, { 1, scores }};
+    std::map<int, std::vector<float>> expectedOutputData = {{ 0, expectedDetectionBoxes },
+                                                            { 1, expectedDetectionClasses },
+                                                            { 2, expectedDetectionScores },
+                                                            { 3, expectedNumDetections }};
+
+    EndToEndLayerTestImpl<ArmnnType, armnn::DataType::Float32>(
+        move(net), inputTensorData, expectedOutputData, backends);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DetectionPostProcessRegularNmsEndToEnd(const std::vector<BackendId>& backends,
+                                            const std::vector<T>& boxEncodings,
+                                            const std::vector<T>& scores,
+                                            const std::vector<T>& anchors,
+                                            float boxScale = 1.0f,
+                                            int32_t boxOffset = 0,
+                                            float scoreScale = 1.0f,
+                                            int32_t scoreOffset = 0,
+                                            float anchorScale = 1.0f,
+                                            int32_t anchorOffset = 0)
+{
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 0.0f, 0.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 2.0f });
+
+    DetectionPostProcessEndToEnd<ArmnnType>(backends, true, boxEncodings, scores, anchors,
+                                            expectedDetectionBoxes, expectedDetectionClasses,
+                                            expectedDetectionScores, expectedNumDetections,
+                                            boxScale, boxOffset, scoreScale, scoreOffset,
+                                            anchorScale, anchorOffset);
+
+};
+
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+void DetectionPostProcessFastNmsEndToEnd(const std::vector<BackendId>& backends,
+                                         const std::vector<T>& boxEncodings,
+                                         const std::vector<T>& scores,
+                                         const std::vector<T>& anchors,
+                                         float boxScale = 1.0f,
+                                         int32_t boxOffset = 0,
+                                         float scoreScale = 1.0f,
+                                          int32_t scoreOffset = 0,
+                                         float anchorScale = 1.0f,
+                                         int32_t anchorOffset = 0)
+{
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 1.0f, 1.0f,
+        0.0f, 100.0f, 1.0f, 101.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 3.0f });
+
+    DetectionPostProcessEndToEnd<ArmnnType>(backends, false, boxEncodings, scores, anchors,
+                                            expectedDetectionBoxes, expectedDetectionClasses,
+                                            expectedDetectionScores, expectedNumDetections,
+                                            boxScale, boxOffset, scoreScale, scoreOffset,
+                                            anchorScale, anchorOffset);
+
+};
+
+} // anonymous namespace
diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
index d17b61e8fb..a04fdf72e7 100644
--- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
@@ -163,7 +163,10 @@ void EndToEndLayerTestImpl(INetworkPtr network,
         }
         else
         {
-            BOOST_TEST(it.second == out);
+            for (unsigned int i = 0; i < out.size(); ++i)
+            {
+                BOOST_TEST(it.second[i] == out[i], boost::test_tools::tolerance(0.000001f));
+            }
         }
     }
 }