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 <div class="header">
   <div class="summary">
 <a href="#pub-methods">Public Member Functions</a>  </div>
   <div class="headertitle">
 <div class="title">CLHOGMultiDetection Class Reference</div>  </div>
 </div><!--header-->
 <div class="contents">

 <p>Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a>.
  <a href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#details">More...</a></p>

 <p><code>#include &lt;<a class="el" href="_c_l_h_o_g_multi_detection_8h_source.xhtml">CLHOGMultiDetection.h</a>&gt;</code></p>
 <div class="dynheader">
 Collaboration diagram for CLHOGMultiDetection:</div>
 <div class="dyncontent">
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 <table class="memberdecls">
 <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
 Public Member Functions</h2></td></tr>
 <tr class="memitem:ab42a47bafe78d7e3329c0a070aa310ff"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#ab42a47bafe78d7e3329c0a070aa310ff">CLHOGMultiDetection</a> (std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt; memory_manager=nullptr)</td></tr>
 <tr class="memdesc:ab42a47bafe78d7e3329c0a070aa310ff"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor.  <a href="#ab42a47bafe78d7e3329c0a070aa310ff">More...</a><br /></td></tr>
 <tr class="separator:ab42a47bafe78d7e3329c0a070aa310ff"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a7e022875c81970c79bc689562561ae51"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#a7e022875c81970c79bc689562561ae51">CLHOGMultiDetection</a> (const <a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> &amp;)=delete</td></tr>
 <tr class="memdesc:a7e022875c81970c79bc689562561ae51"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#a7e022875c81970c79bc689562561ae51">More...</a><br /></td></tr>
 <tr class="separator:a7e022875c81970c79bc689562561ae51"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a4dc60a1da8bf41adb6c4d3c428a17415"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#a4dc60a1da8bf41adb6c4d3c428a17415">operator=</a> (const <a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> &amp;)=delete</td></tr>
 <tr class="memdesc:a4dc60a1da8bf41adb6c4d3c428a17415"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers)  <a href="#a4dc60a1da8bf41adb6c4d3c428a17415">More...</a><br /></td></tr>
 <tr class="separator:a4dc60a1da8bf41adb6c4d3c428a17415"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ab5d20af02c277cdfdb18dc5ead27ffb7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#ab5d20af02c277cdfdb18dc5ead27ffb7">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, const <a class="el" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml">ICLMultiHOG</a> *multi_hog, <a class="el" href="namespacearm__compute.xhtml#a4cc908807b0a45ccc6ce7ba340ae2259">ICLDetectionWindowArray</a> *detection_windows, <a class="el" href="namespacearm__compute.xhtml#a68396eee600b3d23bf7f95a802e65dff">ICLSize2DArray</a> *detection_window_strides, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value=0, float threshold=0.0f, bool non_maxima_suppression=false, float min_distance=1.0f)</td></tr>
 <tr class="memdesc:ab5d20af02c277cdfdb18dc5ead27ffb7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression.  <a href="#ab5d20af02c277cdfdb18dc5ead27ffb7">More...</a><br /></td></tr>
 <tr class="separator:ab5d20af02c277cdfdb18dc5ead27ffb7"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
 <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run the kernels contained in the function.  <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr>
 <tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr>
 <tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr>
 <tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor.  <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr>
 <tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
 <tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">prepare</a> ()</td></tr>
 <tr class="memdesc:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prepare the function for executing.  <a href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">More...</a><br /></td></tr>
 <tr class="separator:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
 </table>
 <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
 <div class="textblock"><p>Basic function to detect multiple objects (or the same object at different scales) on the same input image using <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a>. </p>
 <p>This function calls the following kernels:</p>
 <ol type="1">
 <li><a class="el" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml">CLHOGGradient</a></li>
 <li><a class="el" href="classarm__compute_1_1_c_l_h_o_g_orientation_binning_kernel.xhtml">CLHOGOrientationBinningKernel</a></li>
 <li><a class="el" href="classarm__compute_1_1_c_l_h_o_g_block_normalization_kernel.xhtml">CLHOGBlockNormalizationKernel</a></li>
 <li><a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector.xhtml">CLHOGDetector</a></li>
 <li><a class="el" href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml">CPPDetectionWindowNonMaximaSuppressionKernel</a> (executed if non_maxima_suppression == true)</li>
 </ol>
 <dl class="section note"><dt>Note</dt><dd>This implementation works if all the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-objects within the <a class="el" href="classarm__compute_1_1_i_multi_h_o_g.xhtml" title="Interface for storing multiple HOG data-objects.">IMultiHOG</a> container have the same:<ol type="1">
 <li>Phase type</li>
 <li>Normalization type</li>
 <li>L2 hysteresis threshold if the normalization type is L2HYS_NORM </li>
 </ol>
 </dd></dl>

 <p class="definition">Definition at line <a class="el" href="_c_l_h_o_g_multi_detection_8h_source.xhtml#l00056">56</a> of file <a class="el" href="_c_l_h_o_g_multi_detection_8h_source.xhtml">CLHOGMultiDetection.h</a>.</p>
 </div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
 <a id="ab42a47bafe78d7e3329c0a070aa310ff"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#ab42a47bafe78d7e3329c0a070aa310ff">&#9670;&nbsp;</a></span>CLHOGMultiDetection() <span class="overload">[1/2]</span></h2>

 <div class="memitem">
 <div class="memproto">
       <table class="memname">
         <tr>
           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> </td>
           <td>(</td>
           <td class="paramtype">std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt;&#160;</td>
           <td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td>
           <td></td>
         </tr>
       </table>
 </div><div class="memdoc">

 <p>Default constructor. </p>

 <p class="definition">Definition at line <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml">CLHOGMultiDetection.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    : _memory_group(std::move(memory_manager)),</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;      _gradient_kernel(),</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;      _orient_bin_kernel(),</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;      _block_norm_kernel(),</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;      _hog_detect_kernel(),</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;      _non_maxima_kernel(),</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;      _hog_space(),</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;      _hog_norm_space(),</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;      _detection_windows(),</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;      _mag(),</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;      _phase(),</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;      _non_maxima_suppression(<span class="keyword">false</span>),</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;      _num_orient_bin_kernel(0),</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;      _num_block_norm_kernel(0),</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;      _num_hog_detect_kernel(0)</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;{</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;}</div></div><!-- fragment -->
 </div>
 </div>
 <a id="a7e022875c81970c79bc689562561ae51"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#a7e022875c81970c79bc689562561ae51">&#9670;&nbsp;</a></span>CLHOGMultiDetection() <span class="overload">[2/2]</span></h2>

 <div class="memitem">
 <div class="memproto">
 <table class="mlabels">
   <tr>
   <td class="mlabels-left">
       <table class="memname">
         <tr>
           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> </td>
           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> &amp;&#160;</td>
           <td class="paramname"></td><td>)</td>
           <td></td>
         </tr>
       </table>
   </td>
   <td class="mlabels-right">
 <span class="mlabels"><span class="mlabel">delete</span></span>  </td>
   </tr>
 </table>
 </div><div class="memdoc">

 <p>Prevent instances of this class from being copied (As this class contains pointers) </p>

 </div>
 </div>
 <h2 class="groupheader">Member Function Documentation</h2>
 <a id="ab5d20af02c277cdfdb18dc5ead27ffb7"></a>
 <h2 class="memtitle"><span class="permalink"><a href="#ab5d20af02c277cdfdb18dc5ead27ffb7">&#9670;&nbsp;</a></span>configure()</h2>

 <div class="memitem">
 <div class="memproto">
       <table class="memname">
         <tr>
           <td class="memname">void configure </td>
           <td>(</td>
           <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
           <td class="paramname"><em>input</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml">ICLMultiHOG</a> *&#160;</td>
           <td class="paramname"><em>multi_hog</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a4cc908807b0a45ccc6ce7ba340ae2259">ICLDetectionWindowArray</a> *&#160;</td>
           <td class="paramname"><em>detection_windows</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a68396eee600b3d23bf7f95a802e65dff">ICLSize2DArray</a> *&#160;</td>
           <td class="paramname"><em>detection_window_strides</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a>&#160;</td>
           <td class="paramname"><em>border_mode</em>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">uint8_t&#160;</td>
           <td class="paramname"><em>constant_border_value</em> = <code>0</code>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">float&#160;</td>
           <td class="paramname"><em>threshold</em> = <code>0.0f</code>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">bool&#160;</td>
           <td class="paramname"><em>non_maxima_suppression</em> = <code>false</code>, </td>
         </tr>
         <tr>
           <td class="paramkey"></td>
           <td></td>
           <td class="paramtype">float&#160;</td>
           <td class="paramname"><em>min_distance</em> = <code>1.0f</code>&#160;</td>
         </tr>
         <tr>
           <td></td>
           <td>)</td>
           <td></td><td></td>
         </tr>
       </table>
 </div><div class="memdoc">

 <p>Initialise the function's source, destination, detection window strides, border mode, threshold and non-maxima suppression. </p>
 <dl class="params"><dt>Parameters</dt><dd>
   <table class="params">
     <tr><td class="paramdir">[in,out]</td><td class="paramname">input</td><td>Input tensor. Data type supported: U8 (Written to only for <code>border_mode</code> != UNDEFINED) </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">multi_hog</td><td>Container of multiple <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data object. Each <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data object describes one <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> model to detect. This container should store the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-objects in descending or ascending cell_size width order. This will help to understand if the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> descriptor computation can be skipped for some <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-objects </td></tr>
     <tr><td class="paramdir">[out]</td><td class="paramname">detection_windows</td><td><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values.">Array</a> of <a class="el" href="struct_detection_window.xhtml">DetectionWindow</a> used for locating the detected objects </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">detection_window_strides</td><td><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values.">Array</a> of <a class="el" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> used to specify the distance in pixels between 2 consecutive detection windows in x and y directions for each <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-object The dimension of this array must be the same of multi_hog-&gt;num_models() The i-th detection_window_stride of this array must be multiple of the block_stride stored in the i-th multi_hog array </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">border_mode</td><td>Border mode to use. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">constant_border_value</td><td>(Optional) Constant value to use for borders if border_mode is set to CONSTANT. </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>(Optional) Threshold for the distance between features and SVM classifying plane </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">non_maxima_suppression</td><td>(Optional) Flag to specify whether the non-maxima suppression is required or not. True if the non-maxima suppression stage has to be computed </td></tr>
     <tr><td class="paramdir">[in]</td><td class="paramname">min_distance</td><td>(Optional) Radial Euclidean distance to use for the non-maxima suppression stage </td></tr>
   </table>
   </dd>
 </dl>

 <p class="definition">Definition at line <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml#l00056">56</a> of file <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml">CLHOGMultiDetection.cpp</a>.</p>
 <div class="fragment"><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;    <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="_validate_8h.xhtml#abced8d9603a5927ebad9de2528f48962">ARM_COMPUTE_ERROR_ON_INVALID_MULTI_HOG</a>(multi_hog);</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<span class="keyword">nullptr</span> == detection_windows);</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(detection_window_strides-&gt;<a class="code" href="classarm__compute_1_1_i_array.xhtml#aac8e28a698cd201286d75eb3f5ad3e1c">num_values</a>() != multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_multi_h_o_g.xhtml#a36ab43f5c3606001dcd2468b955f3e02">num_models</a>());</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">const</span> <span class="keywordtype">size_t</span>       width      = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;dimension(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span>       height     = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;dimension(<a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape_img  = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span>       num_models = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_multi_h_o_g.xhtml#a36ab43f5c3606001dcd2468b955f3e02">num_models</a>();</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#af00a42ecad444bbda75cde1b64bd7e72">PhaseType</a>          phase_type = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(0)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a039b8ebcdd462041d3988e6d2c145323">phase_type</a>();</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="keywordtype">size_t</span> prev_num_bins     = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(0)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ad96530ddba514601d376f991b568b346">num_bins</a>();</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> prev_cell_size    = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(0)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#aaefa291ad3cc3e3210c8b8ef2ffde476">cell_size</a>();</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> prev_block_size   = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(0)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ae561964ccc0e0a5750676b9c7dd7cd44">block_size</a>();</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> prev_block_stride = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(0)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a207391d3ac69d9a0839104f784f888fd">block_stride</a>();</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;    <span class="comment">/* Check if CLHOGOrientationBinningKernel and CLHOGBlockNormalizationKernel kernels can be skipped for a specific HOG data-object</span></div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="comment">     *</span></div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;<span class="comment">     * 1) CLHOGOrientationBinningKernel and CLHOGBlockNormalizationKernel are skipped if the cell size and the number of bins don&#39;t change.</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="comment">     *        Since &quot;multi_hog&quot; is sorted,it is enough to check the HOG descriptors at level &quot;ith&quot; and level &quot;(i-1)th</span></div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;<span class="comment">     * 2) CLHOGBlockNormalizationKernel is skipped if the cell size, the number of bins and block size do not change.</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="comment">     *         Since &quot;multi_hog&quot; is sorted,it is enough to check the HOG descriptors at level &quot;ith&quot; and level &quot;(i-1)th</span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="comment">     *</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;<span class="comment">     * @note Since the orientation binning and block normalization kernels can be skipped, we need to keep track of the input to process for each kernel</span></div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;<span class="comment">     *       with &quot;input_orient_bin&quot;, &quot;input_hog_detect&quot; and &quot;input_block_norm&quot;</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="comment">     */</span></div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    std::vector&lt;size_t&gt; input_orient_bin;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    std::vector&lt;size_t&gt; input_hog_detect;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    std::vector&lt;std::pair&lt;size_t, size_t&gt;&gt; input_block_norm;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    input_orient_bin.push_back(0);</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    input_hog_detect.push_back(0);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    input_block_norm.emplace_back(0, 0);</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 1; i &lt; num_models; ++i)</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    {</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        <span class="keywordtype">size_t</span> cur_num_bins     = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(i)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ad96530ddba514601d376f991b568b346">num_bins</a>();</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> cur_cell_size    = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(i)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#aaefa291ad3cc3e3210c8b8ef2ffde476">cell_size</a>();</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> cur_block_size   = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(i)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ae561964ccc0e0a5750676b9c7dd7cd44">block_size</a>();</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;        <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> cur_block_stride = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(i)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a207391d3ac69d9a0839104f784f888fd">block_stride</a>();</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        <span class="keywordflow">if</span>((cur_num_bins != prev_num_bins) || (cur_cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a> != prev_cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>) || (cur_cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a> != prev_cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>))</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        {</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;            prev_num_bins     = cur_num_bins;</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;            prev_cell_size    = cur_cell_size;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;            prev_block_size   = cur_block_size;</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;            prev_block_stride = cur_block_stride;</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;            <span class="comment">// Compute orientation binning and block normalization kernels. Update input to process</span></div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;            input_orient_bin.push_back(i);</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;            input_block_norm.emplace_back(i, input_orient_bin.size() - 1);</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        }</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span>((cur_block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a> != prev_block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>) || (cur_block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a> != prev_block_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>) || (cur_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a> != prev_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>)</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;                || (cur_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a> != prev_block_stride.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>))</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        {</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;            prev_block_size   = cur_block_size;</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;            prev_block_stride = cur_block_stride;</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;            <span class="comment">// Compute block normalization kernel. Update input to process</span></div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;            input_block_norm.emplace_back(i, input_orient_bin.size() - 1);</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;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;        <span class="comment">// Update input to process for hog detector kernel</span></div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        input_hog_detect.push_back(input_block_norm.size() - 1);</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    }</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    _detection_windows      = detection_windows;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    _non_maxima_suppression = <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a60e89e48713565425943913adec65294">non_maxima_suppression</a>;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    _num_orient_bin_kernel  = input_orient_bin.size(); <span class="comment">// Number of CLHOGOrientationBinningKernel kernels to compute</span></div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    _num_block_norm_kernel  = input_block_norm.size(); <span class="comment">// Number of CLHOGBlockNormalizationKernel kernels to compute</span></div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    _num_hog_detect_kernel  = input_hog_detect.size(); <span class="comment">// Number of CLHOGDetector functions to compute</span></div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    _orient_bin_kernel.resize(_num_orient_bin_kernel);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    _block_norm_kernel.resize(_num_block_norm_kernel);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    _hog_detect_kernel.resize(_num_hog_detect_kernel);</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    _hog_space.resize(_num_orient_bin_kernel);</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    _hog_norm_space.resize(_num_block_norm_kernel);</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <span class="comment">// Allocate tensors for magnitude and phase</span></div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_mag(shape_img, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">Format::S16</a>);</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    _mag.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(info_mag);</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_phase(shape_img, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">Format::U8</a>);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    _phase.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(info_phase);</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_mag);</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_phase);</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="comment">// Initialise gradient kernel</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    _gradient_kernel.<a class="code" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml#a229bdf53bc1dad3b2408d48db8bcaa96">configure</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, &amp;_mag, &amp;_phase, phase_type, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    <span class="comment">// Configure NETensor for the HOG space and orientation binning kernel</span></div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_orient_bin_kernel; ++i)</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    {</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_multi_hog = input_orient_bin[i];</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;        <span class="comment">// Get the corresponding cell size and number of bins</span></div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> &amp;cell     = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(idx_multi_hog)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#aaefa291ad3cc3e3210c8b8ef2ffde476">cell_size</a>();</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span>  num_bins = multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(idx_multi_hog)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ad96530ddba514601d376f991b568b346">num_bins</a>();</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="comment">// Calculate number of cells along the x and y directions for the hog_space</span></div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_cells_x = width / cell.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_cells_y = height / cell.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        <span class="comment">// TensorShape of hog space</span></div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape_hog_space = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>-&gt;info()-&gt;tensor_shape();</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;        shape_hog_space.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>, num_cells_x);</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;        shape_hog_space.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>, num_cells_y);</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;        <span class="comment">// Allocate HOG space</span></div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_space(shape_hog_space, num_bins, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;        _hog_space[i].allocator()-&gt;init(info_space);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_hog_space[i]);</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        <span class="comment">// Initialise orientation binning kernel</span></div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        _orient_bin_kernel[i].configure(&amp;_mag, &amp;_phase, &amp;_hog_space[i], multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(idx_multi_hog)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>());</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    }</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;    <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    _mag.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    _phase.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="comment">// Configure CLTensor for the normalized HOG space and block normalization kernel</span></div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_block_norm_kernel; ++i)</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    {</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_multi_hog  = input_block_norm[i].first;</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_orient_bin = input_block_norm[i].second;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;        <span class="comment">// Allocate normalized HOG space</span></div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;        <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tensor_info(*(multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(idx_multi_hog)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>()), width, height);</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        _hog_norm_space[i].allocator()-&gt;init(tensor_info);</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;        _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&amp;_hog_norm_space[i]);</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;        <span class="comment">// Initialize block normalization kernel</span></div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        _block_norm_kernel[i].configure(&amp;_hog_space[idx_orient_bin], &amp;_hog_norm_space[i], multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">model</a>(idx_multi_hog)-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>());</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    }</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_orient_bin_kernel; ++i)</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    {</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;        _hog_space[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    }</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    detection_window_strides-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">map</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue(), <span class="keyword">true</span>);</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="comment">// Configure HOG detector kernel</span></div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_hog_detect_kernel; ++i)</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    {</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_block_norm = input_hog_detect[i];</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;        _hog_detect_kernel[i].configure(&amp;_hog_norm_space[idx_block_norm], multi_hog-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a5ae9e122f1b39908b8602cc0acc035c8">cl_model</a>(i), detection_windows, detection_window_strides-&gt;<a class="code" href="classarm__compute_1_1_i_array.xhtml#a9deaea40b2409ee68d354bdb9d3f8443">at</a>(i), <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a6cae310822a46019ba25a00ddb0f7e62">threshold</a>, i);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    }</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    detection_window_strides-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml#af974a2360069c2ef8df4496d00e4f6cc">unmap</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    <span class="comment">// Configure non maxima suppression kernel</span></div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    _non_maxima_kernel.<a class="code" href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml#ad56ff9909955d92abeabbe43c1a21bd9">configure</a>(_detection_windows, min_distance);</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_block_norm_kernel; ++i)</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    {</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        _hog_norm_space[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    }</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_ad96530ddba514601d376f991b568b346"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#ad96530ddba514601d376f991b568b346">arm_compute::HOGInfo::num_bins</a></div><div class="ttdeci">size_t num_bins() const</div><div class="ttdoc">The number of histogram bins for each cell.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8cpp_source.xhtml#l00111">HOGInfo.cpp:111</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_aaefa291ad3cc3e3210c8b8ef2ffde476"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#aaefa291ad3cc3e3210c8b8ef2ffde476">arm_compute::HOGInfo::cell_size</a></div><div class="ttdeci">const Size2D &amp; cell_size() const</div><div class="ttdoc">The cell size in pixels.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8cpp_source.xhtml#l00091">HOGInfo.cpp:91</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00099">CLScheduler.cpp:99</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_af00a42ecad444bbda75cde1b64bd7e72"><div class="ttname"><a href="namespacearm__compute.xhtml#af00a42ecad444bbda75cde1b64bd7e72">arm_compute::PhaseType</a></div><div class="ttdeci">PhaseType</div><div class="ttdoc">Phase calculation type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00406">Types.h:406</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_h_o_g_gradient_xhtml_a229bdf53bc1dad3b2408d48db8bcaa96"><div class="ttname"><a href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml#a229bdf53bc1dad3b2408d48db8bcaa96">arm_compute::CLHOGGradient::configure</a></div><div class="ttdeci">void configure(ICLTensor *input, ICLTensor *output_magnitude, ICLTensor *output_phase, PhaseType phase_type, BorderMode border_mode, uint8_t constant_border_value=0)</div><div class="ttdoc">Initialise the function's source, destinations, phase type and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_h_o_g_gradient_8cpp_source.xhtml#l00037">CLHOGGradient.cpp:37</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel</div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml_ac0abc7a5c0d172947f0e6a0c0dde3df0"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">arm_compute::ICLArray::map</a></div><div class="ttdeci">void map(cl::CommandQueue &amp;q, bool blocking=true)</div><div class="ttdoc">Enqueue a map operation of the allocated buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_array_8h_source.xhtml#l00072">ICLArray.h:72</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00466">Error.h:466</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00061">CLTensor.cpp:61</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a039b8ebcdd462041d3988e6d2c145323"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a039b8ebcdd462041d3988e6d2c145323">arm_compute::HOGInfo::phase_type</a></div><div class="ttdeci">PhaseType phase_type() const</div><div class="ttdoc">The type of PhaseType.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8cpp_source.xhtml#l00126">HOGInfo.cpp:126</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_multi_h_o_g_xhtml_a5ae9e122f1b39908b8602cc0acc035c8"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a5ae9e122f1b39908b8602cc0acc035c8">arm_compute::ICLMultiHOG::cl_model</a></div><div class="ttdeci">virtual ICLHOG * cl_model(size_t index)=0</div><div class="ttdoc">Return a pointer to the requested OpenCL HOG model.</div></div>
 <div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_a207391d3ac69d9a0839104f784f888fd"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#a207391d3ac69d9a0839104f784f888fd">arm_compute::HOGInfo::block_stride</a></div><div class="ttdeci">const Size2D &amp; block_stride() const</div><div class="ttdoc">The block stride in pixels.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8cpp_source.xhtml#l00106">HOGInfo.cpp:106</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_tensor_allocator_xhtml_af36143939a43fa124312e395975091ed"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">arm_compute::ITensorAllocator::init</a></div><div class="ttdeci">void init(const TensorInfo &amp;input, size_t alignment=0)</div><div class="ttdoc">Initialize a tensor based on the passed TensorInfo.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator.cpp:38</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02afeaaf8574e7a78d6b466ff2695052"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">arm_compute::Size2D::height</a></div><div class="ttdeci">size_t height</div><div class="ttdoc">Height of the image region or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00093">Size2D.h:93</a></div></div>
 <div class="ttc" id="_validate_8h_xhtml_abced8d9603a5927ebad9de2528f48962"><div class="ttname"><a href="_validate_8h.xhtml#abced8d9603a5927ebad9de2528f48962">ARM_COMPUTE_ERROR_ON_INVALID_MULTI_HOG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_INVALID_MULTI_HOG(m)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00925">Validate.h:925</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_multi_h_o_g_xhtml_a36ab43f5c3606001dcd2468b955f3e02"><div class="ttname"><a href="classarm__compute_1_1_i_multi_h_o_g.xhtml#a36ab43f5c3606001dcd2468b955f3e02">arm_compute::IMultiHOG::num_models</a></div><div class="ttdeci">virtual size_t num_models() const =0</div><div class="ttdoc">The number of HOG models stored.</div></div>
 <div class="ttc" id="classarm__compute_1_1_memory_group_xhtml_a6fc0a49304c152c20a0f6df0634fb3cd"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">arm_compute::MemoryGroup::manage</a></div><div class="ttdeci">void manage(IMemoryManageable *obj) override</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_8h_source.xhtml#l00079">MemoryGroup.h:79</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5471e46933e7a9c4709972d91fc4ea65"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">arm_compute::test::validation::border_mode</a></div><div class="ttdeci">border_mode</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00118">Convolution.cpp:118</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_multi_h_o_g_xhtml_a6b7b27202983e6c2aadffae4527aea78"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a6b7b27202983e6c2aadffae4527aea78">arm_compute::ICLMultiHOG::model</a></div><div class="ttdeci">IHOG * model(size_t index) override</div><div class="ttdoc">Return a pointer to the requested HOG model.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_multi_h_o_g_8cpp_source.xhtml#l00030">ICLMultiHOG.cpp:30</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_array_xhtml_aac8e28a698cd201286d75eb3f5ad3e1c"><div class="ttname"><a href="classarm__compute_1_1_i_array.xhtml#aac8e28a698cd201286d75eb3f5ad3e1c">arm_compute::IArray::num_values</a></div><div class="ttdeci">size_t num_values() const</div><div class="ttdoc">Number of values currently stored in the array.</div><div class="ttdef"><b>Definition:</b> <a href="_i_array_8h_source.xhtml#l00068">IArray.h:68</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml_ae561964ccc0e0a5750676b9c7dd7cd44"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml#ae561964ccc0e0a5750676b9c7dd7cd44">arm_compute::HOGInfo::block_size</a></div><div class="ttdeci">const Size2D &amp; block_size() const</div><div class="ttdoc">The block size in pixels.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8cpp_source.xhtml#l00096">HOGInfo.cpp:96</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel_xhtml_ad56ff9909955d92abeabbe43c1a21bd9"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_detection_window_non_maxima_suppression_kernel.xhtml#ad56ff9909955d92abeabbe43c1a21bd9">arm_compute::CPPDetectionWindowNonMaximaSuppressionKernel::configure</a></div><div class="ttdeci">void configure(IDetectionWindowArray *input_output, float min_distance)</div><div class="ttdoc">Initialise the kernel's input, output and the euclidean minimum distance.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_detection_window_non_maxima_suppression_kernel_8cpp_source.xhtml#l00071">CPPDetectionWindowNonMaximaSuppressionKernel.cpp:71</a></div></div>
 <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel</div></div>
 <div class="ttc" id="_validate_8h_xhtml_aadf5c9cff86327b96d88d04649d9715e"><div class="ttname"><a href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00790">Validate.h:790</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml_af974a2360069c2ef8df4496d00e4f6cc"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml#af974a2360069c2ef8df4496d00e4f6cc">arm_compute::ICLArray::unmap</a></div><div class="ttdeci">void unmap(cl::CommandQueue &amp;q)</div><div class="ttdoc">Enqueue an unmap operation of the allocated and mapped buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_array_8h_source.xhtml#l00083">ICLArray.h:83</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00127">CLTensorAllocator.cpp:127</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml_a02bed8590a9ddf520e58a060059518ec"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">arm_compute::Size2D::width</a></div><div class="ttdeci">size_t width</div><div class="ttdoc">Width of the image region or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00092">Size2D.h:92</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a60e89e48713565425943913adec65294"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a60e89e48713565425943913adec65294">arm_compute::test::validation::reference::non_maxima_suppression</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; non_maxima_suppression(const SimpleTensor&lt; T &gt; &amp;src, BorderMode border_mode, T constant_border_value)</div><div class="ttdef"><b>Definition:</b> <a href="_non_maxima_suppression_8cpp_source.xhtml#l00038">NonMaximaSuppression.cpp:38</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_size2_d_xhtml"><div class="ttname"><a href="classarm__compute_1_1_size2_d.xhtml">arm_compute::Size2D</a></div><div class="ttdoc">Class for specifying the size of an image or rectangle.</div><div class="ttdef"><b>Definition:</b> <a href="_size2_d_8h_source.xhtml#l00034">Size2D.h:34</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a9c54fb6cea3557692fe7c00c40bb40ad"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">arm_compute::TensorShape::set</a></div><div class="ttdeci">TensorShape &amp; set(size_t dimension, size_t value, bool apply_dim_correction=true)</div><div class="ttdoc">Accessor to set the value of one of the dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00078">TensorShape.h:78</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_h_o_g_xhtml_a4e9b5d4ab15fd9009b463861c1a19dbd"><div class="ttname"><a href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">arm_compute::IHOG::info</a></div><div class="ttdeci">virtual const HOGInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the HOG's metadata.</div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a6cae310822a46019ba25a00ddb0f7e62"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a6cae310822a46019ba25a00ddb0f7e62">arm_compute::test::validation::reference::threshold</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; threshold(const SimpleTensor&lt; T &gt; &amp;src, T threshold, T false_value, T true_value, ThresholdType type, T upper)</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_threshold_8cpp_source.xhtml#l00035">Threshold.cpp:35</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_array_xhtml_a9deaea40b2409ee68d354bdb9d3f8443"><div class="ttname"><a href="classarm__compute_1_1_i_array.xhtml#a9deaea40b2409ee68d354bdb9d3f8443">arm_compute::IArray::at</a></div><div class="ttdeci">virtual T &amp; at(size_t index) const</div><div class="ttdoc">Reference to the element of the array located at the given index.</div><div class="ttdef"><b>Definition:</b> <a href="_i_array_8h_source.xhtml#l00117">IArray.h:117</a></div></div>
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 <p class="reference">References <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00127">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00061">CLTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00466">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00790">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_validate_8h_source.xhtml#l00925">ARM_COMPUTE_ERROR_ON_INVALID_MULTI_HOG</a>, <a class="el" href="_i_array_8h_source.xhtml#l00117">IArray&lt; T &gt;::at()</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00096">HOGInfo::block_size()</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00106">HOGInfo::block_stride()</a>, <a class="el" href="_c_l_2_convolution_8cpp_source.xhtml#l00118">arm_compute::test::validation::border_mode</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00091">HOGInfo::cell_size()</a>, <a class="el" href="classarm__compute_1_1_i_c_l_multi_h_o_g.xhtml#a5ae9e122f1b39908b8602cc0acc035c8">ICLMultiHOG::cl_model()</a>, <a class="el" href="_c_l_h_o_g_gradient_8cpp_source.xhtml#l00037">CLHOGGradient::configure()</a>, <a class="el" href="_c_p_p_detection_window_non_maxima_suppression_kernel_8cpp_source.xhtml#l00071">CPPDetectionWindowNonMaximaSuppressionKernel::configure()</a>, <a class="el" href="_window_8h_source.xhtml#l00043">Window::DimX</a>, <a class="el" href="_window_8h_source.xhtml#l00045">Window::DimY</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00099">CLScheduler::get()</a>, <a class="el" href="_size2_d_8h_source.xhtml#l00093">Size2D::height</a>, <a class="el" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">IHOG::info()</a>, <a class="el" href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator::init()</a>, <a class="el" href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">arm_compute::test::validation::input</a>, <a class="el" href="_memory_group_8h_source.xhtml#l00079">MemoryGroup::manage()</a>, <a class="el" href="_i_c_l_array_8h_source.xhtml#l00072">ICLArray&lt; T &gt;::map()</a>, <a class="el" href="_i_c_l_multi_h_o_g_8cpp_source.xhtml#l00030">ICLMultiHOG::model()</a>, <a class="el" href="_non_maxima_suppression_8cpp_source.xhtml#l00038">arm_compute::test::validation::reference::non_maxima_suppression()</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00111">HOGInfo::num_bins()</a>, <a class="el" href="classarm__compute_1_1_i_multi_h_o_g.xhtml#a36ab43f5c3606001dcd2468b955f3e02">IMultiHOG::num_models()</a>, <a class="el" href="_i_array_8h_source.xhtml#l00068">IArray&lt; T &gt;::num_values()</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00126">HOGInfo::phase_type()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00078">TensorShape::set()</a>, <a class="el" href="reference_2_threshold_8cpp_source.xhtml#l00035">arm_compute::test::validation::reference::threshold()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>, <a class="el" href="_i_c_l_array_8h_source.xhtml#l00083">ICLArray&lt; T &gt;::unmap()</a>, and <a class="el" href="_size2_d_8h_source.xhtml#l00092">Size2D::width</a>.</p>

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 <h2 class="memtitle"><span class="permalink"><a href="#a4dc60a1da8bf41adb6c4d3c428a17415">&#9670;&nbsp;</a></span>operator=()</h2>

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           <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a>&amp; operator= </td>
           <td>(</td>
           <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_h_o_g_multi_detection.xhtml">CLHOGMultiDetection</a> &amp;&#160;</td>
           <td class="paramname"></td><td>)</td>
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 <p>Prevent instances of this class from being copied (As this class contains pointers) </p>

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 <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">&#9670;&nbsp;</a></span>run()</h2>

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           <td class="memname">void run </td>
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 <p>Run the kernels contained in the function. </p>
 <p>For NEON kernels:</p><ul>
 <li>Multi-threading is used for the kernels which are parallelisable.</li>
 <li>By default std::thread::hardware_concurrency() threads are used.</li>
 </ul>
 <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl>
 <p>For OpenCL kernels:</p><ul>
 <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li>
 <li>The queue is then flushed.</li>
 </ul>
 <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd>
 <dd>
 Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl>

 <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>

 <p class="definition">Definition at line <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml#l00229">229</a> of file <a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml">CLHOGMultiDetection.cpp</a>.</p>
 <div class="fragment"><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;{</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <a class="code" href="_error_8h.xhtml#a0b0eb3235749a2909dc5a101afe59a1b">ARM_COMPUTE_ERROR_ON_MSG</a>(_detection_windows == <span class="keyword">nullptr</span>, <span class="stringliteral">&quot;Unconfigured function&quot;</span>);</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    <span class="comment">// Reset detection window</span></div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    _detection_windows-&gt;<a class="code" href="classarm__compute_1_1_i_array.xhtml#ac8bb3912a3ce86b15842e79d0b421204">clear</a>();</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    <span class="comment">// Run gradient</span></div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    _gradient_kernel.<a class="code" href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="comment">// Run orientation binning kernel</span></div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_orient_bin_kernel; ++i)</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    {</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;        <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_orient_bin_kernel[i], <span class="keyword">false</span>);</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    }</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    <span class="comment">// Run block normalization kernel</span></div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_block_norm_kernel; ++i)</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    {</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;        <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_block_norm_kernel[i], <span class="keyword">false</span>);</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    }</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <span class="comment">// Run HOG detector kernel</span></div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; _num_hog_detect_kernel; ++i)</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    {</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        _hog_detect_kernel[i].run();</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    }</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;    <span class="comment">// Run non-maxima suppression kernel if enabled</span></div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    <span class="keywordflow">if</span>(_non_maxima_suppression)</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    {</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;        <span class="comment">// Map detection windows array before computing non maxima suppression</span></div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        _detection_windows-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">map</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue(), <span class="keyword">true</span>);</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;        <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">Scheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_non_maxima_kernel, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        _detection_windows-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml#af974a2360069c2ef8df4496d00e4f6cc">unmap</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;    }</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_i_array_xhtml_ac8bb3912a3ce86b15842e79d0b421204"><div class="ttname"><a href="classarm__compute_1_1_i_array.xhtml#ac8bb3912a3ce86b15842e79d0b421204">arm_compute::IArray::clear</a></div><div class="ttdeci">void clear()</div><div class="ttdoc">Clear all the points from the array.</div><div class="ttdef"><b>Definition:</b> <a href="_i_array_8h_source.xhtml#l00091">IArray.h:91</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00099">CLScheduler.cpp:99</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml_ac0abc7a5c0d172947f0e6a0c0dde3df0"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">arm_compute::ICLArray::map</a></div><div class="ttdeci">void map(cl::CommandQueue &amp;q, bool blocking=true)</div><div class="ttdoc">Enqueue a map operation of the allocated buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_array_8h_source.xhtml#l00072">ICLArray.h:72</a></div></div>
 <div class="ttc" id="_error_8h_xhtml_a0b0eb3235749a2909dc5a101afe59a1b"><div class="ttname"><a href="_error_8h.xhtml#a0b0eb3235749a2909dc5a101afe59a1b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond, msg)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00456">Error.h:456</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &amp;kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00154">CLScheduler.cpp:154</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml_af974a2360069c2ef8df4496d00e4f6cc"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml#af974a2360069c2ef8df4496d00e4f6cc">arm_compute::ICLArray::unmap</a></div><div class="ttdeci">void unmap(cl::CommandQueue &amp;q)</div><div class="ttdoc">Enqueue an unmap operation of the allocated and mapped buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_array_8h_source.xhtml#l00083">ICLArray.h:83</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00082">IMemoryGroup.h:82</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_i_scheduler_xhtml_a4e58f95544bd5ac6559a421671bd9842"><div class="ttname"><a href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">arm_compute::IScheduler::schedule</a></div><div class="ttdeci">virtual void schedule(ICPPKernel *kernel, const Hints &amp;hints)=0</div><div class="ttdoc">Runs the kernel in the same thread as the caller synchronously.</div></div>
 <div class="ttc" id="classarm__compute_1_1_c_l_h_o_g_gradient_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_l_h_o_g_gradient.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CLHOGGradient::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_h_o_g_gradient_8cpp_source.xhtml#l00072">CLHOGGradient.cpp:72</a></div></div>
 <div class="ttc" id="classarm__compute_1_1_scheduler_xhtml_a0d63ca713bab377aabcfb63c192b8429"><div class="ttname"><a href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">arm_compute::Scheduler::get</a></div><div class="ttdeci">static IScheduler &amp; get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_scheduler_8cpp_source.xhtml#l00095">Scheduler.cpp:95</a></div></div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00456">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_i_array_8h_source.xhtml#l00091">IArray&lt; T &gt;::clear()</a>, <a class="el" href="_window_8h_source.xhtml#l00045">Window::DimY</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00154">CLScheduler::enqueue()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00099">CLScheduler::get()</a>, <a class="el" href="_scheduler_8cpp_source.xhtml#l00095">Scheduler::get()</a>, <a class="el" href="_i_c_l_array_8h_source.xhtml#l00072">ICLArray&lt; T &gt;::map()</a>, <a class="el" href="_c_l_h_o_g_gradient_8cpp_source.xhtml#l00072">CLHOGGradient::run()</a>, <a class="el" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">IScheduler::schedule()</a>, and <a class="el" href="_i_c_l_array_8h_source.xhtml#l00083">ICLArray&lt; T &gt;::unmap()</a>.</p>

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 <hr/>The documentation for this class was generated from the following files:<ul>
 <li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_h_o_g_multi_detection_8h_source.xhtml">CLHOGMultiDetection.h</a></li>
 <li>src/runtime/CL/functions/<a class="el" href="_c_l_h_o_g_multi_detection_8cpp_source.xhtml">CLHOGMultiDetection.cpp</a></li>
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