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>
CreateDetectionPostProcessNetwork(const armnn::TensorInfo & boxEncodingsInfo,const armnn::TensorInfo & scoresInfo,const armnn::TensorInfo & anchorsInfo,const std::vector<T> & anchors,bool useRegularNms)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>>
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)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>>
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)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>>
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)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
164