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<a href="#pub-methods">Public Member Functions</a> </div>
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<div class="title">NEHOGDescriptor Class Reference</div> </div>
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<p>Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> descriptor.
<a href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_n_e_h_o_g_descriptor_8h_source.xhtml">NEHOGDescriptor.h</a>&gt;</code></p>
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Collaboration diagram for NEHOGDescriptor:</div>
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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:acd99c8cb08517ab807be56293aac5bec"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml#acd99c8cb08517ab807be56293aac5bec">NEHOGDescriptor</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:acd99c8cb08517ab807be56293aac5bec"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default constructor. <a href="#acd99c8cb08517ab807be56293aac5bec">More...</a><br /></td></tr>
<tr class="separator:acd99c8cb08517ab807be56293aac5bec"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af3e91dd25d2bd7d3f3a0c74cdc77d7c4"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml#af3e91dd25d2bd7d3f3a0c74cdc77d7c4">configure</a> (<a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, const <a class="el" href="classarm__compute_1_1_i_h_o_g.xhtml">IHOG</a> *hog, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value=0)</td></tr>
<tr class="memdesc:af3e91dd25d2bd7d3f3a0c74cdc77d7c4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialise the function's source, destination, <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-object and border mode. <a href="#af3e91dd25d2bd7d3f3a0c74cdc77d7c4">More...</a><br /></td></tr>
<tr class="separator:af3e91dd25d2bd7d3f3a0c74cdc77d7c4"><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_n_e_h_o_g_descriptor.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>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Basic function to calculate <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> descriptor. </p>
<p>This function calls the following NEON kernels:</p>
<ol type="1">
<li><a class="el" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml">NEHOGGradient</a></li>
<li><a class="el" href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml">NEHOGOrientationBinningKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml">NEHOGBlockNormalizationKernel</a> </li>
</ol>
<p class="definition">Definition at line <a class="el" href="_n_e_h_o_g_descriptor_8h_source.xhtml#l00046">46</a> of file <a class="el" href="_n_e_h_o_g_descriptor_8h_source.xhtml">NEHOGDescriptor.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="acd99c8cb08517ab807be56293aac5bec"></a>
<h2 class="memtitle"><span class="permalink"><a href="#acd99c8cb08517ab807be56293aac5bec">&#9670;&nbsp;</a></span>NEHOGDescriptor()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname"><a class="el" href="classarm__compute_1_1_n_e_h_o_g_descriptor.xhtml">NEHOGDescriptor</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="_n_e_h_o_g_descriptor_8cpp_source.xhtml#l00034">34</a> of file <a class="el" href="_n_e_h_o_g_descriptor_8cpp_source.xhtml">NEHOGDescriptor.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; : _memory_group(std::move(memory_manager)), _gradient(), _orient_bin(), _block_norm(), _mag(), _phase(), _hog_space()</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;{</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;}</div></div><!-- fragment -->
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="af3e91dd25d2bd7d3f3a0c74cdc77d7c4"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af3e91dd25d2bd7d3f3a0c74cdc77d7c4">&#9670;&nbsp;</a></span>configure()</h2>
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<div class="memproto">
<table class="memname">
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<td class="memname">void configure </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>input</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>output</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_h_o_g.xhtml">IHOG</a> *&#160;</td>
<td class="paramname"><em>hog</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>&#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, <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data-object and border mode. </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">[out]</td><td class="paramname">output</td><td>Output tensor which stores the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> descriptor. DataType supported: F32. The number of channels is equal to the number of histogram bins per block </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">hog</td><td><a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> data object which describes the <a class="el" href="classarm__compute_1_1_h_o_g.xhtml" title="CPU implementation of HOG data-object.">HOG</a> descriptor </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>
</table>
</dd>
</dl>
<p class="definition">Definition at line <a class="el" href="_n_e_h_o_g_descriptor_8cpp_source.xhtml#l00039">39</a> of file <a class="el" href="_n_e_h_o_g_descriptor_8cpp_source.xhtml">NEHOGDescriptor.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<span class="keyword">nullptr</span> == output);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<span class="keyword">nullptr</span> == hog);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> *hog_info = hog-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> width = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> height = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_bins = hog_info-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#ad96530ddba514601d376f991b568b346">num_bins</a>();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <a class="code" href="classarm__compute_1_1_size2_d.xhtml">Size2D</a> cell_size = hog_info-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#aaefa291ad3cc3e3210c8b8ef2ffde476">cell_size</a>();</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</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="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_cells_x = width / cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02bed8590a9ddf520e58a060059518ec">width</a>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> num_cells_y = height / cell_size.<a class="code" href="classarm__compute_1_1_size2_d.xhtml#a02afeaaf8574e7a78d6b466ff2695052">height</a>;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="comment">// TensorShape of the input image</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &amp;shape_img = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="comment">// TensorShape of the hog space</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape_hog_space = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</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="l00062"></a><span class="lineno"> 62</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="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="comment">// Allocate memory for magnitude, phase and hog space</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</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="l00066"></a><span class="lineno"> 66</span>&#160; _mag.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(info_mag);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</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="l00069"></a><span class="lineno"> 69</span>&#160; _phase.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(info_phase);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</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="l00072"></a><span class="lineno"> 72</span>&#160; _hog_space.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">init</a>(info_space);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_mag);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_phase);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="comment">// Initialise gradient kernel</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; _gradient.<a class="code" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml#ac6ae2d00f75c768927d9529998608aaa">configure</a>(input, &amp;_mag, &amp;_phase, hog_info-&gt;<a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml#a039b8ebcdd462041d3988e6d2c145323">phase_type</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_hog_space);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="comment">// Initialise orientation binning kernel</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; _orient_bin.<a class="code" href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml#a1ca4abc9d169a56f8469b31bba439f05">configure</a>(&amp;_mag, &amp;_phase, &amp;_hog_space, hog-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="comment">// Initialize HOG norm kernel</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; _block_norm.<a class="code" href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml#abe08b9f8d4a3bd083ebae3d1cb65a2b5">configure</a>(&amp;_hog_space, output, hog-&gt;<a class="code" href="classarm__compute_1_1_i_h_o_g.xhtml#a4e9b5d4ab15fd9009b463861c1a19dbd">info</a>());</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; _mag.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; _phase.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; _hog_space.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</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_tensor_allocator_xhtml_a3fc6adad84b23f10d54d5a7b6928f872"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a3fc6adad84b23f10d54d5a7b6928f872">arm_compute::TensorAllocator::init</a></div><div class="ttdeci">void init(const TensorAllocator &amp;allocator, const Coordinates &amp;coords, TensorInfo &amp;sub_info)</div><div class="ttdoc">Shares the same backing memory with another tensor allocator, while the tensor info might be differen...</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00108">TensorAllocator.cpp:108</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</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="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="classarm__compute_1_1_h_o_g_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml">arm_compute::HOGInfo</a></div><div class="ttdoc">Store the HOG's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8h_source.xhtml#l00035">HOGInfo.h:35</a></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="_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#l00337">Error.h:337</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_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="classarm__compute_1_1_tensor_xhtml_adbd0cf83a8e1b335a9bf405a8e5019fa"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">arm_compute::Tensor::allocator</a></div><div class="ttdeci">TensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor.cpp:48</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_h_o_g_gradient_xhtml_ac6ae2d00f75c768927d9529998608aaa"><div class="ttname"><a href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml#ac6ae2d00f75c768927d9529998608aaa">arm_compute::NEHOGGradient::configure</a></div><div class="ttdeci">void configure(ITensor *input, ITensor *output_magnitude, ITensor *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="_n_e_h_o_g_gradient_8cpp_source.xhtml#l00042">NEHOGGradient.cpp:42</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="validation_2_c_l_2_convolution_8cpp_source.xhtml#l00118">Convolution.cpp:118</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_memory_group_base_xhtml_ac1f67376afb7822f262a0174ef4a3104"><div class="ttname"><a href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">arm_compute::MemoryGroupBase::manage</a></div><div class="ttdeci">void manage(TensorType *obj)</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_base_8h_source.xhtml#l00102">MemoryGroupBase.h:102</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::TensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator.cpp:133</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</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#l00789">Validate.h:789</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel_xhtml_abe08b9f8d4a3bd083ebae3d1cb65a2b5"><div class="ttname"><a href="classarm__compute_1_1_n_e_h_o_g_block_normalization_kernel.xhtml#abe08b9f8d4a3bd083ebae3d1cb65a2b5">arm_compute::NEHOGBlockNormalizationKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output, const HOGInfo *hog_info)</div><div class="ttdoc">Initialise the kernel's input, output and HOG's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_h_o_g_descriptor_kernel_8cpp_source.xhtml#l00714">NEHOGDescriptorKernel.cpp:714</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="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_n_e_h_o_g_orientation_binning_kernel_xhtml_a1ca4abc9d169a56f8469b31bba439f05"><div class="ttname"><a href="classarm__compute_1_1_n_e_h_o_g_orientation_binning_kernel.xhtml#a1ca4abc9d169a56f8469b31bba439f05">arm_compute::NEHOGOrientationBinningKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input_magnitude, const ITensor *input_phase, ITensor *output, const HOGInfo *hog_info)</div><div class="ttdoc">Initialise the kernel's inputs, output and HOG's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_h_o_g_descriptor_kernel_8cpp_source.xhtml#l00632">NEHOGDescriptorKernel.cpp:632</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>
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<p class="reference">References <a class="el" href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator::allocate()</a>, <a class="el" href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00337">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00789">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="validation_2_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="_n_e_h_o_g_gradient_8cpp_source.xhtml#l00042">NEHOGGradient::configure()</a>, <a class="el" href="_n_e_h_o_g_descriptor_kernel_8cpp_source.xhtml#l00632">NEHOGOrientationBinningKernel::configure()</a>, <a class="el" href="_n_e_h_o_g_descriptor_kernel_8cpp_source.xhtml#l00714">NEHOGBlockNormalizationKernel::configure()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</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="_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="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00108">TensorAllocator::init()</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase&lt; TensorType &gt;::manage()</a>, <a class="el" href="_h_o_g_info_8cpp_source.xhtml#l00111">HOGInfo::num_bins()</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="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</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="#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>
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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="_n_e_h_o_g_descriptor_8cpp_source.xhtml#l00096">96</a> of file <a class="el" href="_n_e_h_o_g_descriptor_8cpp_source.xhtml">NEHOGDescriptor.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;{</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</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="l00099"></a><span class="lineno"> 99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="comment">// Run gradient</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; _gradient.<a class="code" href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="comment">// Run orientation binning kernel</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_orient_bin, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="comment">// Run block normalization kernel</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <a class="code" href="classarm__compute_1_1_scheduler.xhtml#a0d63ca713bab377aabcfb63c192b8429">NEScheduler::get</a>().<a class="code" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">schedule</a>(&amp;_block_norm, <a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_n_e_h_o_g_gradient_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_n_e_h_o_g_gradient.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::NEHOGGradient::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="_n_e_h_o_g_gradient_8cpp_source.xhtml#l00081">NEHOGGradient.cpp:81</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#l00046">IMemoryGroup.h:46</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_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#l00096">Scheduler.cpp:96</a></div></div>
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<p class="reference">References <a class="el" href="_window_8h_source.xhtml#l00045">Window::DimY</a>, <a class="el" href="_scheduler_8cpp_source.xhtml#l00096">Scheduler::get()</a>, <a class="el" href="_n_e_h_o_g_gradient_8cpp_source.xhtml#l00081">NEHOGGradient::run()</a>, and <a class="el" href="classarm__compute_1_1_i_scheduler.xhtml#a4e58f95544bd5ac6559a421671bd9842">IScheduler::schedule()</a>.</p>
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<hr/>The documentation for this class was generated from the following files:<ul>
<li>arm_compute/runtime/NEON/functions/<a class="el" href="_n_e_h_o_g_descriptor_8h_source.xhtml">NEHOGDescriptor.h</a></li>
<li>src/runtime/NEON/functions/<a class="el" href="_n_e_h_o_g_descriptor_8cpp_source.xhtml">NEHOGDescriptor.cpp</a></li>
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