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| <a href="_image_preprocessor_8cpp.html">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 "<a class="code" href="_inference_test_image_8hpp.html">InferenceTestImage.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_image_preprocessor_8hpp.html">ImagePreprocessor.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.html">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_permute_8hpp.html">armnnUtils/Permute.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <boost/format.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> <span class="preprocessor">#include <iostream></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <fcntl.h></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <array></span></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">template</span> <<span class="keyword">typename</span> TDataType></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="class_image_preprocessor.html">ImagePreprocessor<TDataType>::GetLabelAndResizedImageAsFloat</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> testCaseId,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  std::vector<float> & result)</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> {</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  testCaseId = testCaseId % boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(m_ImageSet.size());</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> <a class="code" href="_caffe_preprocessor_8hpp.html#aaf2811634c15da39d0966a444b780a55">ImageSet</a>& imageSet = m_ImageSet[testCaseId];</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">const</span> std::string fullPath = m_BinaryDirectory + imageSet.first;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <a class="code" href="class_inference_test_image.html">InferenceTestImage</a> image(fullPath.c_str());</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="comment">// this ResizeBilinear result is closer to the tensorflow one than STB.</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="comment">// there is still some difference though, but the inference results are</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="comment">// similar to tensorflow for MobileNet</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  result = image.<a class="code" href="class_inference_test_image.html#a4a6637c2a2952a14cb3a426133b67a73">Resize</a>(m_Width, m_Height, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>(),</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="class_inference_test_image.html#ae7a403f69a7717c1eaae1d74b7bb7bcea773b27aa8d21604182ba90d029ad2e13">InferenceTestImage::ResizingMethods::BilinearAndNormalized</a>,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  m_Mean, m_Stddev, m_Scale);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// duplicate data across the batch</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i < m_BatchSize; i++)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  result.insert(result.end(), result.begin(), result.begin() + boost::numeric_cast<<span class="keywordtype">int</span>>(GetNumImageElements()));</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">if</span> (m_DataFormat == DataFormat::NCHW)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> <a class="code" href="namespacearmnn_utils.html#a12124184ac6aec018beb98b9715330c7">NHWCToArmNN</a> = { 0, 2, 3, 1 };</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> dstShape({m_BatchSize, 3, m_Height, m_Width});</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  std::vector<float> tempImage(result.size());</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(dstShape, NHWCToArmNN, result.data(), tempImage.data(), <span class="keyword">sizeof</span>(float));</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  result.swap(tempImage);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">return</span> imageSet.second;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> std::unique_ptr<ImagePreprocessor<float>::TTestCaseData></div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="class_image_preprocessor.html#afc05b2b7e914f9737812e66f5583b04c"> 59</a></span> <a class="code" href="class_image_preprocessor.html#ac2bd5628ca0535f9e8af78e65685d62f">ImagePreprocessor<float>::GetTestCaseData</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> testCaseId)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> {</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::vector<float> resized;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">auto</span> label = GetLabelAndResizedImageAsFloat(testCaseId, resized);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">return</span> std::make_unique<TTestCaseData>(label, std::move(resized));</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> }</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> std::unique_ptr<ImagePreprocessor<uint8_t>::TTestCaseData></div><div class="line"><a name="l00068"></a><span class="lineno"><a class="line" href="class_image_preprocessor.html#a0859c20682ecfa660d0da13de7998029"> 68</a></span> <a class="code" href="class_image_preprocessor.html#ac2bd5628ca0535f9e8af78e65685d62f">ImagePreprocessor<uint8_t>::GetTestCaseData</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> testCaseId)</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  std::vector<float> resized;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">auto</span> label = GetLabelAndResizedImageAsFloat(testCaseId, resized);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordtype">size_t</span> resizedSize = resized.size();</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  std::vector<uint8_t> quantized(resized.size());</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i=0; i<resizedSize; ++i)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  quantized[i] = <span class="keyword">static_cast<</span>uint8_t<span class="keyword">></span>(resized[i]);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  }</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">return</span> std::make_unique<TTestCaseData>(label, std::move(quantized));</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> }</div><div class="ttc" id="namespacearmnn_utils_html_af3c74017185773dd61d8ca6662d65d43"><div class="ttname"><a href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a></div><div class="ttdeci">void Permute(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)</div><div class="ttdef"><b>Definition:</b> <a href="_permute_8cpp_source.html#l00121">Permute.cpp:121</a></div></div> |
| <div class="ttc" id="classarmnn_1_1_permutation_vector_html"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00170">Types.hpp:170</a></div></div> |
| <div class="ttc" id="_permute_8hpp_html"><div class="ttname"><a href="_permute_8hpp.html">Permute.hpp</a></div></div> |
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| <div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div> |
| <div class="ttc" id="class_inference_test_image_html_a4a6637c2a2952a14cb3a426133b67a73"><div class="ttname"><a href="class_inference_test_image.html#a4a6637c2a2952a14cb3a426133b67a73">InferenceTestImage::Resize</a></div><div class="ttdeci">std::vector< float > Resize(unsigned int newWidth, unsigned int newHeight, const armnn::CheckLocation &location, const ResizingMethods meth=ResizingMethods::STB, const std::array< float, 3 > &mean={{0.0, 0.0, 0.0}}, const std::array< float, 3 > &stddev={{1.0, 1.0, 1.0}}, const float scale=255.0f)</div><div class="ttdef"><b>Definition:</b> <a href="_inference_test_image_8cpp_source.html#l00209">InferenceTestImage.cpp:209</a></div></div> |
| <div class="ttc" id="namespacearmnn_utils_html_a12124184ac6aec018beb98b9715330c7"><div class="ttname"><a href="namespacearmnn_utils.html#a12124184ac6aec018beb98b9715330c7">armnnUtils::NHWCToArmNN</a></div><div class="ttdeci">const armnn::PermutationVector NHWCToArmNN</div><div class="ttdef"><b>Definition:</b> <a href="_parser_helper_8cpp_source.html#l00016">ParserHelper.cpp:16</a></div></div> |
| <div class="ttc" id="class_image_preprocessor_html_ac2bd5628ca0535f9e8af78e65685d62f"><div class="ttname"><a href="class_image_preprocessor.html#ac2bd5628ca0535f9e8af78e65685d62f">ImagePreprocessor::GetTestCaseData</a></div><div class="ttdeci">std::unique_ptr< TTestCaseData > GetTestCaseData(unsigned int testCaseId)</div></div> |
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