ArmNN
 21.02
DetectionPostProcessEndToEndTestImpl.hpp
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1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #pragma once
7 
8 #include "CommonTestUtils.hpp"
9 
10 #include <armnn/INetwork.hpp>
11 #include <ResolveType.hpp>
12 
13 namespace{
14 
15 template<typename T>
16 armnn::INetworkPtr CreateDetectionPostProcessNetwork(const armnn::TensorInfo& boxEncodingsInfo,
17  const armnn::TensorInfo& scoresInfo,
18  const armnn::TensorInfo& anchorsInfo,
19  const std::vector<T>& anchors,
20  bool useRegularNms)
21 {
22  armnn::TensorInfo detectionBoxesInfo({ 1, 3, 4 }, armnn::DataType::Float32);
23  armnn::TensorInfo detectionScoresInfo({ 1, 3 }, armnn::DataType::Float32);
24  armnn::TensorInfo detectionClassesInfo({ 1, 3 }, armnn::DataType::Float32);
25  armnn::TensorInfo numDetectionInfo({ 1 }, armnn::DataType::Float32);
26 
27  armnn::DetectionPostProcessDescriptor desc;
28  desc.m_UseRegularNms = useRegularNms;
29  desc.m_MaxDetections = 3;
30  desc.m_MaxClassesPerDetection = 1;
31  desc.m_DetectionsPerClass =1;
32  desc.m_NmsScoreThreshold = 0.0;
33  desc.m_NmsIouThreshold = 0.5;
34  desc.m_NumClasses = 2;
35  desc.m_ScaleY = 10.0;
36  desc.m_ScaleX = 10.0;
37  desc.m_ScaleH = 5.0;
38  desc.m_ScaleW = 5.0;
39 
40  armnn::INetworkPtr net(armnn::INetwork::Create());
41 
42  armnn::IConnectableLayer* boxesLayer = net->AddInputLayer(0);
43  armnn::IConnectableLayer* scoresLayer = net->AddInputLayer(1);
44  armnn::ConstTensor anchorsTensor(anchorsInfo, anchors.data());
45  armnn::IConnectableLayer* detectionLayer = net->AddDetectionPostProcessLayer(desc, anchorsTensor,
46  "DetectionPostProcess");
47  armnn::IConnectableLayer* detectionBoxesLayer = net->AddOutputLayer(0, "detectionBoxes");
48  armnn::IConnectableLayer* detectionClassesLayer = net->AddOutputLayer(1, "detectionClasses");
49  armnn::IConnectableLayer* detectionScoresLayer = net->AddOutputLayer(2, "detectionScores");
50  armnn::IConnectableLayer* numDetectionLayer = net->AddOutputLayer(3, "numDetection");
51  Connect(boxesLayer, detectionLayer, boxEncodingsInfo, 0, 0);
52  Connect(scoresLayer, detectionLayer, scoresInfo, 0, 1);
53  Connect(detectionLayer, detectionBoxesLayer, detectionBoxesInfo, 0, 0);
54  Connect(detectionLayer, detectionClassesLayer, detectionClassesInfo, 1, 0);
55  Connect(detectionLayer, detectionScoresLayer, detectionScoresInfo, 2, 0);
56  Connect(detectionLayer, numDetectionLayer, numDetectionInfo, 3, 0);
57 
58  return net;
59 }
60 
61 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
62 void DetectionPostProcessEndToEnd(const std::vector<BackendId>& backends, bool useRegularNms,
63  const std::vector<T>& boxEncodings,
64  const std::vector<T>& scores,
65  const std::vector<T>& anchors,
66  const std::vector<float>& expectedDetectionBoxes,
67  const std::vector<float>& expectedDetectionClasses,
68  const std::vector<float>& expectedDetectionScores,
69  const std::vector<float>& expectedNumDetections,
70  float boxScale = 1.0f,
71  int32_t boxOffset = 0,
72  float scoreScale = 1.0f,
73  int32_t scoreOffset = 0,
74  float anchorScale = 1.0f,
75  int32_t anchorOffset = 0)
76 {
77  armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, ArmnnType);
78  armnn::TensorInfo scoresInfo({ 1, 6, 3}, ArmnnType);
79  armnn::TensorInfo anchorsInfo({ 6, 4 }, ArmnnType);
80 
81  boxEncodingsInfo.SetQuantizationScale(boxScale);
82  boxEncodingsInfo.SetQuantizationOffset(boxOffset);
83  scoresInfo.SetQuantizationScale(scoreScale);
84  scoresInfo.SetQuantizationOffset(scoreOffset);
85  anchorsInfo.SetQuantizationScale(anchorScale);
86  anchorsInfo.SetQuantizationOffset(anchorOffset);
87 
88  // Builds up the structure of the network
89  armnn::INetworkPtr net = CreateDetectionPostProcessNetwork<T>(boxEncodingsInfo, scoresInfo,
90  anchorsInfo, anchors, useRegularNms);
91 
92  BOOST_TEST_CHECKPOINT("create a network");
93 
94  std::map<int, std::vector<T>> inputTensorData = {{ 0, boxEncodings }, { 1, scores }};
95  std::map<int, std::vector<float>> expectedOutputData = {{ 0, expectedDetectionBoxes },
96  { 1, expectedDetectionClasses },
97  { 2, expectedDetectionScores },
98  { 3, expectedNumDetections }};
99 
100  EndToEndLayerTestImpl<ArmnnType, armnn::DataType::Float32>(
101  move(net), inputTensorData, expectedOutputData, backends);
102 }
103 
104 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
105 void DetectionPostProcessRegularNmsEndToEnd(const std::vector<BackendId>& backends,
106  const std::vector<T>& boxEncodings,
107  const std::vector<T>& scores,
108  const std::vector<T>& anchors,
109  float boxScale = 1.0f,
110  int32_t boxOffset = 0,
111  float scoreScale = 1.0f,
112  int32_t scoreOffset = 0,
113  float anchorScale = 1.0f,
114  int32_t anchorOffset = 0)
115 {
116  std::vector<float> expectedDetectionBoxes({
117  0.0f, 10.0f, 1.0f, 11.0f,
118  0.0f, 10.0f, 1.0f, 11.0f,
119  0.0f, 0.0f, 0.0f, 0.0f
120  });
121  std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });
122  std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
123  std::vector<float> expectedNumDetections({ 2.0f });
124 
125  DetectionPostProcessEndToEnd<ArmnnType>(backends, true, boxEncodings, scores, anchors,
126  expectedDetectionBoxes, expectedDetectionClasses,
127  expectedDetectionScores, expectedNumDetections,
128  boxScale, boxOffset, scoreScale, scoreOffset,
129  anchorScale, anchorOffset);
130 
131 };
132 
133 
134 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
135 void DetectionPostProcessFastNmsEndToEnd(const std::vector<BackendId>& backends,
136  const std::vector<T>& boxEncodings,
137  const std::vector<T>& scores,
138  const std::vector<T>& anchors,
139  float boxScale = 1.0f,
140  int32_t boxOffset = 0,
141  float scoreScale = 1.0f,
142  int32_t scoreOffset = 0,
143  float anchorScale = 1.0f,
144  int32_t anchorOffset = 0)
145 {
146  std::vector<float> expectedDetectionBoxes({
147  0.0f, 10.0f, 1.0f, 11.0f,
148  0.0f, 0.0f, 1.0f, 1.0f,
149  0.0f, 100.0f, 1.0f, 101.0f
150  });
151  std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });
152  std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
153  std::vector<float> expectedNumDetections({ 3.0f });
154 
155  DetectionPostProcessEndToEnd<ArmnnType>(backends, false, boxEncodings, scores, anchors,
156  expectedDetectionBoxes, expectedDetectionClasses,
157  expectedDetectionScores, expectedNumDetections,
158  boxScale, boxOffset, scoreScale, scoreOffset,
159  anchorScale, anchorOffset);
160 
161 };
162 
163 } // anonymous namespace
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:62
anchorsInfo
armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)
ResolveType.hpp
boxEncodings
std::vector< float > boxEncodings({ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, -1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f })
CommonTestUtils.hpp
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::TensorInfo::SetQuantizationScale
void SetQuantizationScale(float scale)
Definition: Tensor.cpp:464
armnn::DetectionPostProcessDescriptor::m_UseRegularNms
bool m_UseRegularNms
Use Regular NMS.
Definition: Descriptors.hpp:555
INetwork.hpp
scores
std::vector< float > scores({ 0.0f, 0.9f, 0.8f, 0.0f, 0.75f, 0.72f, 0.0f, 0.6f, 0.5f, 0.0f, 0.93f, 0.95f, 0.0f, 0.5f, 0.4f, 0.0f, 0.3f, 0.2f })
scoresInfo
armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)
armnn::TensorInfo::SetQuantizationOffset
void SetQuantizationOffset(int32_t offset)
Definition: Tensor.cpp:480
Connect
void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)
Definition: TestUtils.cpp:12
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::DetectionPostProcessDescriptor
Definition: Descriptors.hpp:511
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
anchors
std::vector< float > anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })