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101<a href="_tf_lite_mobilenet_quantized-_armnn_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>&#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;<span class="preprocessor">#include &quot;../InferenceTest.hpp&quot;</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;../ImagePreprocessor.hpp&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_i_tf_lite_parser_8hpp.xhtml">armnnTfLiteParser/ITfLiteParser.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &quot;boost/program_options.hpp&quot;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;fstream&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_tf_lite_parser.xhtml">armnnTfLiteParser</a>;</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno"><a class="line" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a07654cb9e58314e3c617689d40b105fa"> 14</a></span>&#160;std::vector&lt;ImageSet&gt; <a class="code" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a07654cb9e58314e3c617689d40b105fa">ParseDataset</a>(<span class="keyword">const</span> std::string&amp; filename)</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;{</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; std::ifstream read(filename);</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; std::vector&lt;ImageSet&gt; imageSet;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keywordflow">if</span> (read.is_open())</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="comment">// Get the images and the correct corresponding label from the given file</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="keywordflow">for</span> (std::string line; std::getline(read, line);)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; stringstream ss(line);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; std::string image_name;</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; std::string label;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; getline(ss, image_name, <span class="charliteral">&#39; &#39;</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; getline(ss, label, <span class="charliteral">&#39; &#39;</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; imageSet.push_back(<a class="code" href="_caffe_preprocessor_8hpp.xhtml#aaf2811634c15da39d0966a444b780a55">ImageSet</a>(image_name, std::stoi(label)));</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; }</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; }</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="comment">// Use the default images</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; imageSet.push_back(<a class="code" href="_caffe_preprocessor_8hpp.xhtml#aaf2811634c15da39d0966a444b780a55">ImageSet</a>(<span class="stringliteral">&quot;Dog.jpg&quot;</span>, 209));</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="comment">// top five predictions in tensorflow:</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="comment">// -----------------------------------</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="comment">// 209:Labrador retriever 0.949995</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="comment">// 160:Rhodesian ridgeback 0.0270182</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="comment">// 208:golden retriever 0.0192866</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">// 853:tennis ball 0.000470382</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// 239:Greater Swiss Mountain dog 0.000464451</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; imageSet.push_back(<a class="code" href="_caffe_preprocessor_8hpp.xhtml#aaf2811634c15da39d0966a444b780a55">ImageSet</a>(<span class="stringliteral">&quot;Cat.jpg&quot;</span>, 283));</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="comment">// top five predictions in tensorflow:</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="comment">// -----------------------------------</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="comment">// 283:tiger cat 0.579016</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="comment">// 286:Egyptian cat 0.319676</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="comment">// 282:tabby, tabby cat 0.0873346</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="comment">// 288:lynx, catamount 0.011163</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="comment">// 289:leopard, Panthera pardus 0.000856755</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; imageSet.push_back(<a class="code" href="_caffe_preprocessor_8hpp.xhtml#aaf2811634c15da39d0966a444b780a55">ImageSet</a>(<span class="stringliteral">&quot;shark.jpg&quot;</span>, 3));</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="comment">// top five predictions in tensorflow:</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// -----------------------------------</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="comment">// 3:great white shark, white shark, ... 0.996926</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="comment">// 4:tiger shark, Galeocerdo cuvieri 0.00270528</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="comment">// 149:killer whale, killer, orca, ... 0.000121848</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="comment">// 395:sturgeon 7.78977e-05</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="comment">// 5:hammerhead, hammerhead shark 6.44127e-055</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; };</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">return</span> imageSet;</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;</div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a53f4919d2fd18eccaa17afc9994f002a"> 62</a></span>&#160;std::string <a class="code" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a53f4919d2fd18eccaa17afc9994f002a">GetLabelsFilenameFromOptions</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;{</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keyword">namespace </span>po = boost::program_options;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; po::options_description desc(<span class="stringliteral">&quot;Validation Options&quot;</span>);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; std::string fn(<span class="stringliteral">&quot;&quot;</span>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; desc.add_options()</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; (<span class="stringliteral">&quot;labels&quot;</span>, po::value&lt;std::string&gt;(&amp;fn), <span class="stringliteral">&quot;Filename of a text file where in each line contains an image &quot;</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="stringliteral">&quot;filename and the correct label the network should predict when fed that image&quot;</span>);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; po::variables_map vm;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; po::parsed_options parsed = po::command_line_parser(argc, argv).options(desc).allow_unregistered().run();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; po::store(parsed, vm);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keywordflow">if</span> (vm.count(<span class="stringliteral">&quot;labels&quot;</span>))</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; fn = vm[<span class="stringliteral">&quot;labels&quot;</span>].as&lt;std::string&gt;();</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; <span class="keywordflow">return</span> fn;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;}</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;</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"><a class="line" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97"> 81</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;{</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordtype">int</span> retVal = EXIT_FAILURE;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">try</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="comment">// Coverity fix: The following code may throw an exception of type std::length_error.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keyword">const</span> std::string labels_file = <a class="code" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a53f4919d2fd18eccaa17afc9994f002a">GetLabelsFilenameFromOptions</a>(argc,argv);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; std::vector&lt;ImageSet&gt; imageSet = <a class="code" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a07654cb9e58314e3c617689d40b105fa">ParseDataset</a>(labels_file);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; std::vector&lt;unsigned int&gt; indices(imageSet.size());</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; std::generate(indices.begin(), indices.end(), [n = 0] () <span class="keyword">mutable</span> { <span class="keywordflow">return</span> n++; });</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; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputTensorShape({ 1, 224, 224, 3 });</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; <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> = uint8_t;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keyword">using</span> DatabaseType = <a class="code" href="class_image_preprocessor.xhtml">ImagePreprocessor&lt;DataType&gt;</a>;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keyword">using</span> ParserType = <a class="code" href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml">armnnTfLiteParser::ITfLiteParser</a>;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keyword">using</span> ModelType = <a class="code" href="class_inference_model.xhtml">InferenceModel&lt;ParserType, DataType&gt;</a>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="comment">// Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; retVal = <a class="code" href="namespacearmnn_1_1test.xhtml#a47dfae02e22fcca1b6b784873b0328d9">armnn::test::ClassifierInferenceTestMain</a>&lt;DatabaseType,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; ParserType&gt;(</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; argc, argv,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="stringliteral">&quot;mobilenet_v1_1.0_224_quant.tflite&quot;</span>, <span class="comment">// model name</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">true</span>, <span class="comment">// model is binary</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="stringliteral">&quot;input&quot;</span>, <span class="comment">// input tensor name</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="stringliteral">&quot;MobilenetV1/Predictions/Reshape_1&quot;</span>, <span class="comment">// output tensor name</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; indices, <span class="comment">// vector of indices to select which images to validate</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; [&amp;imageSet](<span class="keyword">const</span> <span class="keywordtype">char</span>* dataDir, <span class="keyword">const</span> ModelType &amp;) {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="comment">// we need to get the input quantization parameters from</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="comment">// the parsed model</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">return</span> DatabaseType(</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; dataDir,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; 224,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; 224,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; imageSet,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; 1);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; },</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; &amp;inputTensorShape);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; }</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception&amp; e)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <span class="comment">// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">// exception of type std::length_error.</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="comment">// Using stderr instead in this context as there is no point in nesting try-catch blocks here.</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; std::cerr &lt;&lt; <span class="stringliteral">&quot;WARNING: &quot;</span> &lt;&lt; *argv &lt;&lt; <span class="stringliteral">&quot;: An error has occurred when running &quot;</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="stringliteral">&quot;the classifier inference tests: &quot;</span> &lt;&lt; e.what() &lt;&lt; std::endl;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; }</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="keywordflow">return</span> retVal;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;}</div><div class="ttc" id="_caffe_preprocessor_8hpp_xhtml_aaf2811634c15da39d0966a444b780a55"><div class="ttname"><a href="_caffe_preprocessor_8hpp.xhtml#aaf2811634c15da39d0966a444b780a55">ImageSet</a></div><div class="ttdeci">std::pair&lt; const std::string, unsigned int &gt; ImageSet</div><div class="ttdoc">Caffe requires BGR images, not normalized, mean adjusted and resized using smooth resize of STB libra...</div><div class="ttdef"><b>Definition:</b> <a href="_caffe_preprocessor_8hpp_source.xhtml#l00016">CaffePreprocessor.hpp:16</a></div></div>
102<div class="ttc" id="class_inference_model_xhtml"><div class="ttname"><a href="class_inference_model.xhtml">InferenceModel</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00316">InferenceModel.hpp:316</a></div></div>
103<div class="ttc" id="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser_xhtml"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml">armnnTfLiteParser::ITfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.xhtml#l00025">ITfLiteParser.hpp:25</a></div></div>
104<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>
105<div class="ttc" id="_i_tf_lite_parser_8hpp_xhtml"><div class="ttname"><a href="_i_tf_lite_parser_8hpp.xhtml">ITfLiteParser.hpp</a></div></div>
106<div class="ttc" id="_tf_lite_mobilenet_quantized-_armnn_8cpp_xhtml_a07654cb9e58314e3c617689d40b105fa"><div class="ttname"><a href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a07654cb9e58314e3c617689d40b105fa">ParseDataset</a></div><div class="ttdeci">std::vector&lt; ImageSet &gt; ParseDataset(const std::string &amp;filename)</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_mobilenet_quantized-_armnn_8cpp_source.xhtml#l00014">TfLiteMobilenetQuantized-Armnn.cpp:14</a></div></div>
107<div class="ttc" id="_tf_lite_mobilenet_quantized-_armnn_8cpp_xhtml_a53f4919d2fd18eccaa17afc9994f002a"><div class="ttname"><a href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a53f4919d2fd18eccaa17afc9994f002a">GetLabelsFilenameFromOptions</a></div><div class="ttdeci">std::string GetLabelsFilenameFromOptions(int argc, char *argv[])</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_mobilenet_quantized-_armnn_8cpp_source.xhtml#l00062">TfLiteMobilenetQuantized-Armnn.cpp:62</a></div></div>
108<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
109<div class="ttc" id="_tf_lite_mobilenet_quantized-_armnn_8cpp_xhtml_a0ddf1224851353fc92bfbff6f499fa97"><div class="ttname"><a href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97">main</a></div><div class="ttdeci">int main(int argc, char *argv[])</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_mobilenet_quantized-_armnn_8cpp_source.xhtml#l00081">TfLiteMobilenetQuantized-Armnn.cpp:81</a></div></div>
110<div class="ttc" id="namespacearmnn_1_1test_xhtml_a47dfae02e22fcca1b6b784873b0328d9"><div class="ttname"><a href="namespacearmnn_1_1test.xhtml#a47dfae02e22fcca1b6b784873b0328d9">armnn::test::ClassifierInferenceTestMain</a></div><div class="ttdeci">int ClassifierInferenceTestMain(int argc, char *argv[], const char *modelFilename, bool isModelBinary, const char *inputBindingName, const char *outputBindingName, const std::vector&lt; unsigned int &gt; &amp;defaultTestCaseIds, TConstructDatabaseCallable constructDatabase, const armnn::TensorShape *inputTensorShape=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_inference_test_8inl_source.xhtml#l00352">InferenceTest.inl:352</a></div></div>
111<div class="ttc" id="namespacearmnn_tf_lite_parser_xhtml"><div class="ttname"><a href="namespacearmnn_tf_lite_parser.xhtml">armnnTfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.xhtml#l00017">ITfLiteParser.hpp:17</a></div></div>
112<div class="ttc" id="class_image_preprocessor_xhtml"><div class="ttname"><a href="class_image_preprocessor.xhtml">ImagePreprocessor</a></div><div class="ttdef"><b>Definition:</b> <a href="_image_preprocessor_8hpp_source.xhtml#l00020">ImagePreprocessor.hpp:20</a></div></div>
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118 <li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_660eb08a01451f3d7d39c9d8f2c054f4.xhtml">TfLiteMobilenetQuantized-Armnn</a></li><li class="navelem"><a class="el" href="_tf_lite_mobilenet_quantized-_armnn_8cpp.xhtml">TfLiteMobilenetQuantized-Armnn.cpp</a></li>
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