diff options
Diffstat (limited to 'src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/DetectionPostProcessTestImpl.hpp | 162 |
1 files changed, 162 insertions, 0 deletions
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 |