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<div class="title">DetectionPostProcess.cpp</div> </div>
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<a href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.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">#include "../TfLiteParser.hpp"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_parser_prototxt_fixture_8hpp.xhtml">ParserPrototxtFixture.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_parser_helper_8hpp.xhtml">ParserHelper.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_graph_utils_8hpp.xhtml">test/GraphUtils.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a>></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="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(TensorflowLiteParser)</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword">struct </span>DetectionPostProcessFixture : <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> {</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keyword">explicit</span> DetectionPostProcessFixture(<span class="keyword">const</span> std::string& custom_options)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="comment">/*</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"> The following values were used for the custom_options:</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"> use_regular_nms = true</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> max_classes_per_detection = 1</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> detections_per_class = 1</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> nms_score_threshold = 0.0</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> nms_iou_threshold = 0.5</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"> max_detections = 3</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> max_detections = 3</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> num_classes = 2</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> h_scale = 5</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> w_scale = 5</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"> x_scale = 10</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> y_scale = 10</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> */</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">m_JsonString</a> = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> "operator_codes": [{</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> "builtin_code": "CUSTOM",</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> "custom_code": "TFLite_Detection_PostProcess"</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> "subgraphs": [{</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> "tensors": [{</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> "shape": [1, 6, 4],</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> "name": "box_encodings",</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> "min": [0.0],</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> "max": [255.0],</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> "scale": [1.0],</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> "zero_point": [ 1 ]</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> "shape": [1, 6, 3],</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> "name": "scores",</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> "min": [0.0],</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> "max": [255.0],</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> "scale": [0.01],</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="stringliteral"> "zero_point": [0]</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="stringliteral"> "shape": [6, 4],</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="stringliteral"> "name": "anchors",</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> "min": [0.0],</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> "max": [255.0],</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> "scale": [0.5],</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> "zero_point": [0]</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="stringliteral"> "buffer": 3,</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="stringliteral"> "name": "detection_boxes",</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"> "quantization": {}</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> "buffer": 4,</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> "name": "detection_classes",</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> "quantization": {}</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="stringliteral"> "buffer": 5,</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="stringliteral"> "name": "detection_scores",</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="stringliteral"> "quantization": {}</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> "type": "FLOAT32",</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"> "buffer": 6,</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> "name": "num_detections",</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="stringliteral"> "quantization": {}</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="stringliteral"> "inputs": [0, 1, 2],</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="stringliteral"> "outputs": [3, 4, 5, 6],</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="stringliteral"> "operators": [{</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> "inputs": [0, 1, 2],</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> "outputs": [3, 4, 5, 6],</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> "builtin_options_type": 0,</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> "custom_options": [)" + custom_options + R</span><span class="stringliteral">"(],</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> }]</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="stringliteral"> "buffers": [{},</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="stringliteral"> {},</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> { "data": [ 1, 1, 2, 2,</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"> 1, 1, 2, 2,</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> 1, 1, 2, 2,</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="stringliteral"> 1, 21, 2, 2,</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="stringliteral"> 1, 21, 2, 2,</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="stringliteral"> 1, 201, 2, 2]},</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="stringliteral"> {},</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="stringliteral"> {},</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="stringliteral"> {},</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> {},</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="stringliteral"> )";</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral">};</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="stringliteral"></span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="stringliteral"></span><span class="keyword">struct </span>ParseDetectionPostProcessCustomOptions : DetectionPostProcessFixture</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">static</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> GenerateDescriptor()</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">static</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3u;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = 1u;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> = 1u;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = 2u;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = 0.0f;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = 0.5f;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a> = 5.0f;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">m_ScaleW</a> = 5.0f;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a> = 10.0f;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a> = 10.0f;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">return</span> descriptor;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  }</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  ParseDetectionPostProcessCustomOptions()</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  : DetectionPostProcessFixture(</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  GenerateDetectionPostProcessJsonString(GenerateDescriptor()))</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> </div><div class="line"><a name="l00164"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.xhtml#a04100371674f0cea5e0cc32a9a5ad7b1"> 164</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.xhtml#a04100371674f0cea5e0cc32a9a5ad7b1">BOOST_FIXTURE_TEST_CASE</a>( ParseDetectionPostProcess, ParseDetectionPostProcessCustomOptions )</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  Setup();</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// Inputs</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">using</span> UnquantizedContainer = std::vector<float>;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  UnquantizedContainer <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a> =</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  {</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  0.0f, 1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  0.0f, -1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  0.0f, 1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  };</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  UnquantizedContainer <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a> =</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  0.0f, 0.9f, 0.8f,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  0.0f, 0.75f, 0.72f,</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  0.0f, 0.6f, 0.5f,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  0.0f, 0.93f, 0.95f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  0.0f, 0.5f, 0.4f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  0.0f, 0.3f, 0.2f</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  };</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// Outputs</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  UnquantizedContainer detectionBoxes =</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  {</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  0.0f, 10.0f, 1.0f, 11.0f,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  };</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  UnquantizedContainer detectionClasses = { 1.0f, 0.0f, 0.0f };</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  UnquantizedContainer detectionScores = { 0.95f, 0.93f, 0.0f };</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  UnquantizedContainer numDetections = { 2.0f };</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="comment">// Quantize inputs and outputs</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">using</span> QuantizedContainer = std::vector<uint8_t>;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  QuantizedContainer quantBoxEncodings = armnnUtils::QuantizedVector<uint8_t>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a>, 1.00f, 1);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  QuantizedContainer quantScores = armnnUtils::QuantizedVector<uint8_t>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a>, 0.01f, 0);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  std::map<std::string, QuantizedContainer> input =</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  { <span class="stringliteral">"box_encodings"</span>, quantBoxEncodings },</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  { <span class="stringliteral">"scores"</span>, quantScores }</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  };</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  std::map<std::string, UnquantizedContainer> output =</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  { <span class="stringliteral">"detection_boxes"</span>, detectionBoxes},</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  { <span class="stringliteral">"detection_classes"</span>, detectionClasses},</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  { <span class="stringliteral">"detection_scores"</span>, detectionScores},</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  { <span class="stringliteral">"num_detections"</span>, numDetections}</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  };</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  RunTest<armnn::DataType::QAsymmU8, armnn::DataType::Float32>(0, input, output);</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> }</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.xhtml#a1b421e50a520d2a52d6cdef8b84ef26f"> 226</a></span> <a class="code" href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.xhtml#a04100371674f0cea5e0cc32a9a5ad7b1">BOOST_FIXTURE_TEST_CASE</a>(DetectionPostProcessGraphStructureTest, ParseDetectionPostProcessCustomOptions)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="comment">/*</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="comment"> Inputs: box_encodings scores</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="comment"> \ /</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="comment"> DetectionPostProcess</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="comment"> / / \ \</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> <span class="comment"> / / \ \</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="comment"> Outputs: detection detection detection num_detections</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="comment"> boxes classes scores</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="comment"> */</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  ReadStringToBinary();</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = m_Parser->CreateNetworkFromBinary(m_GraphBinary);</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keyword">auto</span> optimized = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> }, m_Runtime->GetDeviceSpec());</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optimized.get());</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="comment">// Check the number of layers in the graph</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  BOOST_TEST((graph.GetNumInputs() == 2));</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  BOOST_TEST((graph.GetNumOutputs() == 4));</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  BOOST_TEST((graph.GetNumLayers() == 7));</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="comment">// Input layers</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* boxEncodingLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"box_encodings"</span>);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  BOOST_TEST((boxEncodingLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>));</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(boxEncodingLayer, 0));</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(boxEncodingLayer, 1));</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> </div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* scoresLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"scores"</span>);</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  BOOST_TEST((scoresLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>));</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(scoresLayer, 0));</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(scoresLayer, 1));</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="comment">// DetectionPostProcess layer</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* detectionPostProcessLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"DetectionPostProcess:0:0"</span>);</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  BOOST_TEST((detectionPostProcessLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">armnn::LayerType::DetectionPostProcess</a>));</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(detectionPostProcessLayer, 2));</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(detectionPostProcessLayer, 4));</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="comment">// Output layers</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* detectionBoxesLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"detection_boxes"</span>);</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  BOOST_TEST((detectionBoxesLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>));</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(detectionBoxesLayer, 1));</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(detectionBoxesLayer, 0));</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* detectionClassesLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"detection_classes"</span>);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  BOOST_TEST((detectionClassesLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>));</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(detectionClassesLayer, 1));</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(detectionClassesLayer, 0));</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* detectionScoresLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"detection_scores"</span>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  BOOST_TEST((detectionScoresLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>));</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(detectionScoresLayer, 1));</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(detectionScoresLayer, 0));</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* numDetectionsLayer = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"num_detections"</span>);</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  BOOST_TEST((numDetectionsLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>));</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a>(numDetectionsLayer, 1));</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a>(numDetectionsLayer, 0));</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="comment">// Check the connections</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> boxEncodingTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1, 6, 4 }), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>, 1, 1);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> scoresTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1, 6, 3 }), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  0.00999999978f, 0);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionBoxesTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1, 3, 4 }), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, 0, 0);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionClassesTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1, 3 }), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, 0, 0);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> detectionScoresTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1, 3 }), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, 0, 0);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> numDetectionsTensor(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>({ 1} ), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, 0, 0);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(boxEncodingLayer, detectionPostProcessLayer, 0, 0, boxEncodingTensor));</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(scoresLayer, detectionPostProcessLayer, 0, 1, scoresTensor));</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(detectionPostProcessLayer, detectionBoxesLayer, 0, 0, detectionBoxesTensor));</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(detectionPostProcessLayer, detectionClassesLayer, 1, 0, detectionClassesTensor));</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(detectionPostProcessLayer, detectionScoresLayer, 2, 0, detectionScoresTensor));</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a>(detectionPostProcessLayer, numDetectionsLayer, 3, 0, numDetectionsTensor));</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a803c86dca3acef653c1cc481a27be7a9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">ParserFlatbuffersFixture::m_JsonString</a></div><div class="ttdeci">std::string m_JsonString</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00051">ParserFlatbuffersFixture.hpp:51</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ab509802c659de19929f18bad14a35c58"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">armnn::DetectionPostProcessDescriptor::m_ScaleW</a></div><div class="ttdeci">float m_ScaleW</div><div class="ttdoc">Center size encoding scale weight. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00561">Descriptors.hpp:561</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</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="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00557">Descriptors.hpp:557</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00547">Descriptors.hpp:547</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="struct_parser_flatbuffers_fixture_xhtml"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00036">ParserFlatbuffersFixture.hpp:36</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a9ae2c9796692ebeafe19a4d3f09c8ea8"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection</a></div><div class="ttdeci">uint32_t m_MaxClassesPerDetection</div><div class="ttdoc">Maximum numbers of classes per detection, used in Fast NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00545">Descriptors.hpp:545</a></div></div>
<div class="ttc" id="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">armnn::LayerType::DetectionPostProcess</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a53c8a7f33a40e1e240256bcfcf41b101"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">armnn::DetectionPostProcessDescriptor::m_NmsIouThreshold</a></div><div class="ttdeci">float m_NmsIouThreshold</div><div class="ttdoc">Intersection over union threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00551">Descriptors.hpp:551</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00553">Descriptors.hpp:553</a></div></div>
<div class="ttc" id="_parser_prototxt_fixture_8hpp_xhtml"><div class="ttname"><a href="_parser_prototxt_fixture_8hpp.xhtml">ParserPrototxtFixture.hpp</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="_graph_utils_8hpp_xhtml"><div class="ttname"><a href="_graph_utils_8hpp.xhtml">GraphUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="_parser_helper_8hpp_xhtml"><div class="ttname"><a href="_parser_helper_8hpp.xhtml">ParserHelper.hpp</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_afd518dba3d52728670459e4ad3bed5e1"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#afd518dba3d52728670459e4ad3bed5e1">IsConnected</a></div><div class="ttdeci">bool IsConnected(armnn::Layer *srcLayer, armnn::Layer *destLayer, unsigned int srcSlot, unsigned int destSlot, const armnn::TensorInfo &expectedTensorInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00044">GraphUtils.cpp:44</a></div></div>
<div class="ttc" id="_parser_flatbuffers_fixture_8hpp_xhtml"><div class="ttname"><a href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00563">Descriptors.hpp:563</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div>
<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></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="_graph_utils_8cpp_xhtml_a4c04337db4d5f380219a005657a8223b"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a4c04337db4d5f380219a005657a8223b">CheckNumberOfInputSlot</a></div><div class="ttdeci">bool CheckNumberOfInputSlot(armnn::Layer *layer, unsigned int num)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00034">GraphUtils.cpp:34</a></div></div>
<div class="ttc" id="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp_xhtml_a04100371674f0cea5e0cc32a9a5ad7b1"><div class="ttname"><a href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp.xhtml#a04100371674f0cea5e0cc32a9a5ad7b1">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(ParseDetectionPostProcess, ParseDetectionPostProcessCustomOptions)</div><div class="ttdef"><b>Definition:</b> <a href="armnn_tf_lite_parser_2test_2_detection_post_process_8cpp_source.xhtml#l00164">DetectionPostProcess.cpp:164</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_aada2e27f100807f5786eecb03390ba58"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#aada2e27f100807f5786eecb03390ba58">CheckNumberOfOutputSlot</a></div><div class="ttdeci">bool CheckNumberOfOutputSlot(armnn::Layer *layer, unsigned int num)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00039">GraphUtils.cpp:39</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00559">Descriptors.hpp:559</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a4392dd6b4862cc9cf95ae8f1001ba592"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">armnn::DetectionPostProcessDescriptor::m_NmsScoreThreshold</a></div><div class="ttdeci">float m_NmsScoreThreshold</div><div class="ttdoc">NMS score threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00549">Descriptors.hpp:549</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_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
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