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>
diff --git a/src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp b/src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp
new file mode 100644
index 0000000..5f4d2a4
--- /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