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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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">namespace</span>{</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<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>&amp; boxEncodingsInfo,</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;                                                     <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&amp; <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>&#160;                                                     <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&amp; <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>&#160;                                                     <span class="keyword">const</span> std::vector&lt;T&gt;&amp; <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>&#160;                                                     <span class="keywordtype">bool</span> useRegularNms)</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;{</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;    <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>&#160;    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>&#160;    desc.m_MaxDetections = 3;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    desc.m_MaxClassesPerDetection = 1;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    desc.m_DetectionsPerClass =1;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    desc.m_NmsScoreThreshold = 0.0;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    desc.m_NmsIouThreshold = 0.5;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    desc.m_NumClasses = 2;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    desc.m_ScaleY = 10.0;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    desc.m_ScaleX = 10.0;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    desc.m_ScaleH = 5.0;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    desc.m_ScaleW = 5.0;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a>());</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* boxesLayer = net-&gt;AddInputLayer(0);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* scoresLayer = net-&gt;AddInputLayer(1);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <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>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionLayer = net-&gt;AddDetectionPostProcessLayer(desc, anchorsTensor,</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;                                                                                 <span class="stringliteral">&quot;DetectionPostProcess&quot;</span>);</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionBoxesLayer = net-&gt;AddOutputLayer(0, <span class="stringliteral">&quot;detectionBoxes&quot;</span>);</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionClassesLayer = net-&gt;AddOutputLayer(1, <span class="stringliteral">&quot;detectionClasses&quot;</span>);</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* detectionScoresLayer = net-&gt;AddOutputLayer(2, <span class="stringliteral">&quot;detectionScores&quot;</span>);</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* numDetectionLayer = net-&gt;AddOutputLayer(3, <span class="stringliteral">&quot;numDetection&quot;</span>);</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keywordflow">return</span> net;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;}</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="keywordtype">void</span> DetectionPostProcessEndToEnd(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; backends, <span class="keywordtype">bool</span> useRegularNms,</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;T&gt;&amp; <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>&#160;                                  <span class="keyword">const</span> std::vector&lt;T&gt;&amp; <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>&#160;                                  <span class="keyword">const</span> std::vector&lt;T&gt;&amp; anchors,</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;float&gt;&amp; expectedDetectionBoxes,</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;float&gt;&amp; expectedDetectionClasses,</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;float&gt;&amp; expectedDetectionScores,</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;                                  <span class="keyword">const</span> std::vector&lt;float&gt;&amp; expectedNumDetections,</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;                                  <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;                                  int32_t boxOffset = 0,</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;                                  <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;                                  int32_t scoreOffset = 0,</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;                                  <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;                                  int32_t anchorOffset = 0)</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;{</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    <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>&#160;    <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>&#160;    <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>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    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>&#160;    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>&#160;    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>&#160;    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>&#160;    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>&#160;    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>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="comment">// Builds up the structure of the network</span></div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net = CreateDetectionPostProcessNetwork&lt;T&gt;(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>&#160;                                                                  <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>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    BOOST_TEST_CHECKPOINT(<span class="stringliteral">&quot;create a network&quot;</span>);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    std::map&lt;int, std::vector&lt;T&gt;&gt; inputTensorData = {{ 0, boxEncodings }, { 1, scores }};</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    std::map&lt;int, std::vector&lt;float&gt;&gt; expectedOutputData = {{ 0, expectedDetectionBoxes },</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;                                                            { 1, expectedDetectionClasses },</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;                                                            { 2, expectedDetectionScores },</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;                                                            { 3, expectedNumDetections }};</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    EndToEndLayerTestImpl&lt;ArmnnType, armnn::DataType::Float32&gt;(</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        move(net), inputTensorData, expectedOutputData, backends);</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;}</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;<span class="keywordtype">void</span> DetectionPostProcessRegularNmsEndToEnd(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; backends,</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                                            <span class="keyword">const</span> std::vector&lt;T&gt;&amp; boxEncodings,</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;                                            <span class="keyword">const</span> std::vector&lt;T&gt;&amp; scores,</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;                                            <span class="keyword">const</span> std::vector&lt;T&gt;&amp; anchors,</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;                                            <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;                                            int32_t boxOffset = 0,</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                                            <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;                                            int32_t scoreOffset = 0,</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;                                            <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;                                            int32_t anchorOffset = 0)</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;{</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    std::vector&lt;float&gt; expectedDetectionBoxes({</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;        0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    });</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    std::vector&lt;float&gt; expectedDetectionScores({ 0.95f, 0.93f, 0.0f });</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    std::vector&lt;float&gt; expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    std::vector&lt;float&gt; expectedNumDetections({ 2.0f });</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    DetectionPostProcessEndToEnd&lt;ArmnnType&gt;(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>&#160;                                            expectedDetectionBoxes, expectedDetectionClasses,</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                                            expectedDetectionScores, expectedNumDetections,</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;                                            boxScale, boxOffset, scoreScale, scoreOffset,</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;                                            anchorScale, anchorOffset);</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;};</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;<span class="keywordtype">void</span> DetectionPostProcessFastNmsEndToEnd(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; backends,</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;                                         <span class="keyword">const</span> std::vector&lt;T&gt;&amp; boxEncodings,</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;                                         <span class="keyword">const</span> std::vector&lt;T&gt;&amp; scores,</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;                                         <span class="keyword">const</span> std::vector&lt;T&gt;&amp; anchors,</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;                                         <span class="keywordtype">float</span> boxScale = 1.0f,</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;                                         int32_t boxOffset = 0,</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                                         <span class="keywordtype">float</span> scoreScale = 1.0f,</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;                                          int32_t scoreOffset = 0,</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;                                         <span class="keywordtype">float</span> anchorScale = 1.0f,</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                                         int32_t anchorOffset = 0)</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;{</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    std::vector&lt;float&gt; expectedDetectionBoxes({</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;        0.0f, 0.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        0.0f, 100.0f, 1.0f, 101.0f</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    });</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    std::vector&lt;float&gt; expectedDetectionScores({ 0.95f, 0.9f, 0.3f });</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    std::vector&lt;float&gt; expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    std::vector&lt;float&gt; expectedNumDetections({ 3.0f });</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    DetectionPostProcessEndToEnd&lt;ArmnnType&gt;(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>&#160;                                            expectedDetectionBoxes, expectedDetectionClasses,</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                                            expectedDetectionScores, expectedNumDetections,</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;                                            boxScale, boxOffset, scoreScale, scoreOffset,</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                                            anchorScale, anchorOffset);</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;};</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;} <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#l00061">INetwork.hpp:61</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#l00053">Tensor.hpp:53</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&lt; float &gt; 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#l00199">Tensor.hpp:199</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#l00259">Tensor.cpp:259</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#l00539">Descriptors.hpp:539</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&lt; float &gt; 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#l00275">Tensor.cpp:275</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 &amp;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&lt; INetwork, void(*)(INetwork *network)&gt; INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00101">INetwork.hpp:101</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#l00495">Descriptors.hpp:495</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00049">Network.cpp:49</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&lt; float &gt; 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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+    <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="_detection_post_process_end_to_end_test_impl_8hpp.xhtml">DetectionPostProcessEndToEndTestImpl.hpp</a></li>
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