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<div class="title">DetectionPostProcessEndToEndTestImpl.hpp</div> </div>
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<a href="_detection_post_process_end_to_end_test_impl_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">namespace</span>{</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateDetectionPostProcessNetwork(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& boxEncodingsInfo,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a>,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> std::vector<T>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keywordtype">bool</span> useRegularNms)</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionBoxesInfo({ 1, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionScoresInfo({ 1, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionClassesInfo({ 1, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> numDetectionInfo({ 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> desc;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  desc.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = useRegularNms;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  desc.m_MaxDetections = 3;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  desc.m_MaxClassesPerDetection = 1;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  desc.m_DetectionsPerClass =1;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  desc.m_NmsScoreThreshold = 0.0;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  desc.m_NmsIouThreshold = 0.5;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  desc.m_NumClasses = 2;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  desc.m_ScaleY = 10.0;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  desc.m_ScaleX = 10.0;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  desc.m_ScaleH = 5.0;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  desc.m_ScaleW = 5.0;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>());</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* boxesLayer = net->AddInputLayer(0);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* scoresLayer = net->AddInputLayer(1);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> anchorsTensor(anchorsInfo, anchors.data());</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionLayer = net->AddDetectionPostProcessLayer(desc, anchorsTensor,</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="stringliteral">"DetectionPostProcess"</span>);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionBoxesLayer = net->AddOutputLayer(0, <span class="stringliteral">"detectionBoxes"</span>);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionClassesLayer = net->AddOutputLayer(1, <span class="stringliteral">"detectionClasses"</span>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionScoresLayer = net->AddOutputLayer(2, <span class="stringliteral">"detectionScores"</span>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* numDetectionLayer = net->AddOutputLayer(3, <span class="stringliteral">"numDetection"</span>);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(boxesLayer, detectionLayer, boxEncodingsInfo, 0, 0);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(scoresLayer, detectionLayer, scoresInfo, 0, 1);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(detectionLayer, detectionBoxesLayer, detectionBoxesInfo, 0, 0);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(detectionLayer, detectionClassesLayer, detectionClassesInfo, 1, 0);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(detectionLayer, detectionScoresLayer, detectionScoresInfo, 2, 0);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(detectionLayer, numDetectionLayer, numDetectionInfo, 3, 0);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">return</span> net;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> }</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="keywordtype">void</span> DetectionPostProcessEndToEnd(<span class="keyword">const</span> std::vector<BackendId>& backends, <span class="keywordtype">bool</span> useRegularNms,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">const</span> std::vector<T>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a>,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> std::vector<T>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a>,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> std::vector<T>& anchors,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">const</span> std::vector<float>& expectedDetectionBoxes,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">const</span> std::vector<float>& expectedDetectionClasses,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> std::vector<float>& expectedDetectionScores,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> std::vector<float>& expectedNumDetections,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  int32_t boxOffset = 0,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  int32_t scoreOffset = 0,</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  int32_t anchorOffset = 0)</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> {</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> boxEncodingsInfo({ 1, 6, 4 }, ArmnnType);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>({ 1, 6, 3}, ArmnnType);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a>({ 6, 4 }, ArmnnType);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  boxEncodingsInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(boxScale);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  boxEncodingsInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(boxOffset);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  scoresInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(scoreScale);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  scoresInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(scoreOffset);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  anchorsInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(anchorScale);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  anchorsInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(anchorOffset);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="comment">// Builds up the structure of the network</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net = CreateDetectionPostProcessNetwork<T>(boxEncodingsInfo, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a>,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>, useRegularNms);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  BOOST_TEST_CHECKPOINT(<span class="stringliteral">"create a network"</span>);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::map<int, std::vector<T>> inputTensorData = {{ 0, boxEncodings }, { 1, scores }};</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  std::map<int, std::vector<float>> expectedOutputData = {{ 0, expectedDetectionBoxes },</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  { 1, expectedDetectionClasses },</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  { 2, expectedDetectionScores },</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  { 3, expectedNumDetections }};</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  EndToEndLayerTestImpl<ArmnnType, armnn::DataType::Float32>(</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  move(net), inputTensorData, expectedOutputData, backends);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="keywordtype">void</span> DetectionPostProcessRegularNmsEndToEnd(<span class="keyword">const</span> std::vector<BackendId>& backends,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> std::vector<T>& boxEncodings,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> std::vector<T>& scores,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keyword">const</span> std::vector<T>& anchors,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  int32_t boxOffset = 0,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  int32_t scoreOffset = 0,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  int32_t anchorOffset = 0)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  std::vector<float> expectedDetectionBoxes({</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  });</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  std::vector<float> expectedNumDetections({ 2.0f });</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  DetectionPostProcessEndToEnd<ArmnnType>(backends, <span class="keyword">true</span>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  expectedDetectionBoxes, expectedDetectionClasses,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  expectedDetectionScores, expectedNumDetections,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  boxScale, boxOffset, scoreScale, scoreOffset,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  anchorScale, anchorOffset);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> };</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="keywordtype">void</span> DetectionPostProcessFastNmsEndToEnd(<span class="keyword">const</span> std::vector<BackendId>& backends,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keyword">const</span> std::vector<T>& boxEncodings,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">const</span> std::vector<T>& scores,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keyword">const</span> std::vector<T>& anchors,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  int32_t boxOffset = 0,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  int32_t scoreOffset = 0,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  int32_t anchorOffset = 0)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::vector<float> expectedDetectionBoxes({</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  0.0f, 0.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  0.0f, 100.0f, 1.0f, 101.0f</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  });</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  std::vector<float> expectedNumDetections({ 3.0f });</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  DetectionPostProcessEndToEnd<ArmnnType>(backends, <span class="keyword">false</span>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a>, <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  expectedDetectionBoxes, expectedDetectionClasses,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  expectedDetectionScores, expectedNumDetections,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  boxScale, boxOffset, scoreScale, scoreOffset,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  anchorScale, anchorOffset);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> };</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> } <span class="comment">// anonymous namespace</span></div><div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a358cb7cd3c0647b25be049fd734b8c22"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a></div><div class="ttdeci">armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)</div></div>
<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ada422a73ac4e68bcb1b1b1f0b44028d9"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a></div><div class="ttdeci">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 })</div></div>
<div class="ttc" id="_common_test_utils_8hpp_xhtml"><div class="ttname"><a href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00555">Descriptors.hpp:555</a></div></div>
<div class="ttc" id="_i_network_8hpp_xhtml"><div class="ttname"><a href="_i_network_8hpp.xhtml">INetwork.hpp</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a0348e6bb67ace72535bd105219bb6237"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a></div><div class="ttdeci">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 })</div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a64c1dd1b6dd60be9f4a16db9c8f427a5"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a64c1dd1b6dd60be9f4a16db9c8f427a5">scoresInfo</a></div><div class="ttdeci">armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::Float32)</div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00480">Tensor.cpp:480</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00511">Descriptors.hpp:511</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">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 })</div></div>
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