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<a href="#pub-methods">Public Member Functions</a> </div>
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<div class="title">CLCannyEdge Class Reference</div> </div>
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<p>Basic function to execute canny edge on OpenCL.
<a href="classarm__compute_1_1_c_l_canny_edge.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_c_l_canny_edge_8h_source.xhtml">CLCannyEdge.h</a>&gt;</code></p>
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Collaboration diagram for CLCannyEdge:</div>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:aa5e675eaa99bc8c86a1aed1089326c3b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml#aa5e675eaa99bc8c86a1aed1089326c3b">CLCannyEdge</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:aa5e675eaa99bc8c86a1aed1089326c3b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#aa5e675eaa99bc8c86a1aed1089326c3b">More...</a><br /></td></tr>
<tr class="separator:aa5e675eaa99bc8c86a1aed1089326c3b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac7d8d6eeca4596ff4d3fe4be919ec740"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml#ac7d8d6eeca4596ff4d3fe4be919ec740">CLCannyEdge</a> (const <a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> &amp;)=delete</td></tr>
<tr class="memdesc:ac7d8d6eeca4596ff4d3fe4be919ec740"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#ac7d8d6eeca4596ff4d3fe4be919ec740">More...</a><br /></td></tr>
<tr class="separator:ac7d8d6eeca4596ff4d3fe4be919ec740"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a390de29c61d4843b56ae0d39fe1f139d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml#a390de29c61d4843b56ae0d39fe1f139d">operator=</a> (const <a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> &amp;)=delete</td></tr>
<tr class="memdesc:a390de29c61d4843b56ae0d39fe1f139d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a390de29c61d4843b56ae0d39fe1f139d">More...</a><br /></td></tr>
<tr class="separator:a390de29c61d4843b56ae0d39fe1f139d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa874f9e002bdb799f38411a5fef07b1d"><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_canny_edge.xhtml#aa874f9e002bdb799f38411a5fef07b1d">configure</a> (<a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *input, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output, int32_t upper_thr, int32_t lower_thr, int32_t gradient_size, int32_t norm_type, <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327">BorderMode</a> border_mode, uint8_t constant_border_value=0)</td></tr>
<tr class="memdesc:aa874f9e002bdb799f38411a5fef07b1d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Initialise the function's source, destination, thresholds, gradient size, normalization type and border mode. <a href="#aa874f9e002bdb799f38411a5fef07b1d">More...</a><br /></td></tr>
<tr class="separator:aa874f9e002bdb799f38411a5fef07b1d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.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 execute canny edge on OpenCL. </p>
<p>This function calls the following OpenCL kernels and functions:</p>
<ol type="1">
<li><a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml">CLFillBorderKernel</a> (if border_mode == REPLICATE or border_mode == CONSTANT)</li>
<li><a class="el" href="classarm__compute_1_1_c_l_sobel3x3.xhtml">CLSobel3x3</a> (if gradient_size == 3) or <a class="el" href="classarm__compute_1_1_c_l_sobel5x5.xhtml">CLSobel5x5</a> (if gradient_size == 5) or <a class="el" href="classarm__compute_1_1_c_l_sobel7x7.xhtml">CLSobel7x7</a> (if gradient_size == 7)</li>
<li><a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml">CLGradientKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml">CLEdgeNonMaxSuppressionKernel</a></li>
<li><a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml">CLEdgeTraceKernel</a> </li>
</ol>
<p class="definition">Definition at line <a class="el" href="_c_l_canny_edge_8h_source.xhtml#l00050">50</a> of file <a class="el" href="_c_l_canny_edge_8h_source.xhtml">CLCannyEdge.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="aa5e675eaa99bc8c86a1aed1089326c3b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa5e675eaa99bc8c86a1aed1089326c3b">&#9670;&nbsp;</a></span>CLCannyEdge() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
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<td class="memname"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</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>
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<p>Constructor. </p>
<p class="definition">Definition at line <a class="el" href="_c_l_canny_edge_8cpp_source.xhtml#l00038">38</a> of file <a class="el" href="_c_l_canny_edge_8cpp_source.xhtml">CLCannyEdge.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; : _memory_group(std::move(memory_manager)),</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; _sobel(),</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; _gradient(),</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; _border_mag_gradient(),</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; _non_max_suppr(),</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; _edge_trace(),</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; _gx(),</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; _gy(),</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; _nonmax(),</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; _visited(),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; _recorded(),</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; _l1_list_counter(),</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; _l1_stack(),</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; _output(<span class="keyword">nullptr</span>)</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;}</div></div><!-- fragment -->
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<a id="ac7d8d6eeca4596ff4d3fe4be919ec740"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac7d8d6eeca4596ff4d3fe4be919ec740">&#9670;&nbsp;</a></span>CLCannyEdge() <span class="overload">[2/2]</span></h2>
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<td class="memname"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> &amp;&#160;</td>
<td class="paramname"></td><td>)</td>
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</td>
<td class="mlabels-right">
<span class="mlabels"><span class="mlabel">delete</span></span> </td>
</tr>
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<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="aa874f9e002bdb799f38411a5fef07b1d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa874f9e002bdb799f38411a5fef07b1d">&#9670;&nbsp;</a></span>configure()</h2>
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<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"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
<td class="paramname"><em>output</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>upper_thr</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>lower_thr</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>gradient_size</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">int32_t&#160;</td>
<td class="paramname"><em>norm_type</em>, </td>
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<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>
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<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>
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<td>)</td>
<td></td><td></td>
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<p>Initialise the function's source, destination, thresholds, gradient size, normalization type 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>Source tensor. Data types supported: U8. (Written to only for border_mode != UNDEFINED) </td></tr>
<tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data types supported: U8. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">upper_thr</td><td>Upper threshold used for the hysteresis. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">lower_thr</td><td>Lower threshold used for the hysteresis. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">gradient_size</td><td>Gradient size (3, 5 or 7). </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">norm_type</td><td>Normalization type. if 1, L1-Norm otherwise L2-Norm. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">border_mode</td><td>Border mode to use for the convolution. </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>
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</dl>
<p class="definition">Definition at line <a class="el" href="_c_l_canny_edge_8cpp_source.xhtml#l00058">58</a> of file <a class="el" href="_c_l_canny_edge_8cpp_source.xhtml">CLCannyEdge.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;{</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input, output);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</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="l00063"></a><span class="lineno"> 63</span>&#160; <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(output, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((1 != norm_type) &amp;&amp; (2 != norm_type));</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((gradient_size != 3) &amp;&amp; (gradient_size != 5) &amp;&amp; (gradient_size != 7));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((lower_thr &lt; 0) || (lower_thr &gt;= upper_thr));</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; _output = output;</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> L1_hysteresis_stack_size = 8;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a> = 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="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> gradient_info;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="comment">// Initialize images</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordflow">if</span>(gradient_size &lt; 7)</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; {</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; gradient_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::DataType::S16</a>);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.init(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::DataType::U16</a>);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; }</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">else</span></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; gradient_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">init</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::DataType::S32</a>);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.init(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::DataType::U32</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;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; _gx.<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>(gradient_info);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; _gy.<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>(gradient_info);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</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>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; _nonmax.<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>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</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; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_u8(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::DataType::U8</a>);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</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_u8);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; _l1_list_counter.<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_u8);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_u32(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::DataType::U32</a>);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; _visited.<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_u32);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; _recorded.<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_u32);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape_l1_stack = 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="l00102"></a><span class="lineno"> 102</span>&#160; shape_l1_stack.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(0, 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>(0) * L1_hysteresis_stack_size);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> info_s32(shape_l1_stack, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::DataType::S32</a>);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; _l1_stack.<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_s32);</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">// Manage intermediate buffers</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_gx);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_gy);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="comment">// Configure/Init sobelNxN</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">if</span>(gradient_size == 3)</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;CLSobel3x3&gt;();</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; k-&gt;configure(input, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; _sobel = std::move(k);</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="keywordflow">else</span> <span class="keywordflow">if</span>(gradient_size == 5)</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; {</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;CLSobel5x5&gt;();</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; k-&gt;configure(input, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; _sobel = std::move(k);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; }</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(gradient_size == 7)</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; <span class="keyword">auto</span> k = arm_compute::support::cpp14::make_unique&lt;CLSobel7x7&gt;();</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; k-&gt;configure(input, &amp;_gx, &amp;_gy, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a>, constant_border_value);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; _sobel = std::move(k);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; }</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keywordflow">else</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; <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Gradient size %d not supported&quot;</span>, gradient_size);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</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="l00136"></a><span class="lineno"> 136</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="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="comment">// Configure gradient</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; _gradient.<a class="code" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml#ad67340e556964fbc6aee83f7b2ff8101">configure</a>(&amp;_gx, &amp;_gy, &amp;_mag, &amp;_phase, norm_type);</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; <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; _gx.<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="l00143"></a><span class="lineno"> 143</span>&#160; _gy.<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="l00144"></a><span class="lineno"> 144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="comment">// Manage intermediate buffers</span></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_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_nonmax);</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">// Configure non-maxima suppression</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; _non_max_suppr.<a class="code" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a209e05c2e2bf4d5fb2b9e3f75c7d79aa">configure</a>(&amp;_mag, &amp;_phase, &amp;_nonmax, lower_thr, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5471e46933e7a9c4709972d91fc4ea65">border_mode</a> == <a class="code" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">BorderMode::UNDEFINED</a>);</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">// Allocate intermediate buffers</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</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="l00153"></a><span class="lineno"> 153</span>&#160;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="comment">// Fill border around magnitude image as non-maxima suppression will access</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="comment">// it. If border mode is undefined filling the border is a nop.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; _border_mag_gradient.<a class="code" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#ae1b9fe62ed42f469f1de879c33d75c06">configure</a>(&amp;_mag, _non_max_suppr.<a class="code" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">border_size</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="l00157"></a><span class="lineno"> 157</span>&#160;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</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="l00160"></a><span class="lineno"> 160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_visited);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_recorded);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_l1_stack);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_l1_list_counter);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <span class="comment">// Configure edge tracing</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; _edge_trace.<a class="code" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml#af4b40677259a11edd3e83e82c1c6dd9d">configure</a>(&amp;_nonmax, output, upper_thr, lower_thr, &amp;_visited, &amp;_recorded, &amp;_l1_stack, &amp;_l1_list_counter);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="comment">// Allocate intermediate buffers</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; _visited.<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="l00172"></a><span class="lineno"> 172</span>&#160; _recorded.<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="l00173"></a><span class="lineno"> 173</span>&#160; _l1_stack.<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="l00174"></a><span class="lineno"> 174</span>&#160; _l1_list_counter.<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="l00175"></a><span class="lineno"> 175</span>&#160; _nonmax.<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="l00176"></a><span class="lineno"> 176</span>&#160;}</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00261">Error.h:261</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00097">AbsoluteDifference.cpp:97</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel_xhtml_a209e05c2e2bf4d5fb2b9e3f75c7d79aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a209e05c2e2bf4d5fb2b9e3f75c7d79aa">arm_compute::CLEdgeNonMaxSuppressionKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined)</div><div class="ttdoc">Initialise the kernel's sources, destination and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00120">CLCannyEdgeKernel.cpp:120</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_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="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="_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_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#l00055">CLTensor.cpp:55</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 U16 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_fill_border_kernel_xhtml_ae1b9fe62ed42f469f1de879c33d75c06"><div class="ttname"><a href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#ae1b9fe62ed42f469f1de879c33d75c06">arm_compute::CLFillBorderKernel::configure</a></div><div class="ttdeci">void configure(ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &amp;constant_border_value=PixelValue())</div><div class="ttdoc">Initialise the kernel's input, output and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_fill_border_kernel_8cpp_source.xhtml#l00062">CLFillBorderKernel.cpp:62</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="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</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_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="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel</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_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_tensor_info_xhtml_ad6b64f33be1e66dcf7612483ffb8fd63"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ad6b64f33be1e66dcf7612483ffb8fd63">arm_compute::TensorInfo::init</a></div><div class="ttdeci">void init(Format format)</div><div class="ttdoc">Initialize the tensor info with just a format.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00099">TensorInfo.cpp:99</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#l00119">CLTensorAllocator.cpp:119</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_gradient_kernel_xhtml_ad67340e556964fbc6aee83f7b2ff8101"><div class="ttname"><a href="classarm__compute_1_1_c_l_gradient_kernel.xhtml#ad67340e556964fbc6aee83f7b2ff8101">arm_compute::CLGradientKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type)</div><div class="ttdoc">Initialise the kernel's sources, destinations and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00040">CLCannyEdgeKernel.cpp:40</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_edge_trace_kernel_xhtml_af4b40677259a11edd3e83e82c1c6dd9d"><div class="ttname"><a href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml#af4b40677259a11edd3e83e82c1c6dd9d">arm_compute::CLEdgeTraceKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr, ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter)</div><div class="ttdoc">Initialise the kernel's source, destination and border mode.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00194">CLCannyEdgeKernel.cpp:194</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3"><div class="ttname"><a href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::BorderMode::UNDEFINED</a></div><div class="ttdoc">Borders are left undefined.</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="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel_xhtml_a423f9a45a52983b4de5e2b347f4369c7"><div class="ttname"><a href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a423f9a45a52983b4de5e2b347f4369c7">arm_compute::CLEdgeNonMaxSuppressionKernel::border_size</a></div><div class="ttdeci">BorderSize border_size() const override</div><div class="ttdoc">The size of the border for that kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00115">CLCannyEdgeKernel.cpp:115</a></div></div>
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<p class="reference">References <a class="el" href="_c_l_tensor_allocator_8cpp_source.xhtml#l00119">CLTensorAllocator::allocate()</a>, <a class="el" href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor::allocator()</a>, <a class="el" href="_error_8h_source.xhtml#l00261">ARM_COMPUTE_ERROR</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="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</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="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00115">CLEdgeNonMaxSuppressionKernel::border_size()</a>, <a class="el" href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00040">CLGradientKernel::configure()</a>, <a class="el" href="_c_l_fill_border_kernel_8cpp_source.xhtml#l00062">CLFillBorderKernel::configure()</a>, <a class="el" href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00120">CLEdgeNonMaxSuppressionKernel::configure()</a>, <a class="el" href="_c_l_canny_edge_kernel_8cpp_source.xhtml#l00194">CLEdgeTraceKernel::configure()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::info</a>, <a class="el" href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator::init()</a>, <a class="el" href="src_2core_2_tensor_info_8cpp_source.xhtml#l00099">TensorInfo::init()</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase&lt; TensorType &gt;::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00078">TensorShape::set()</a>, <a class="el" href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00097">arm_compute::test::validation::shape</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#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>, and <a class="el" href="namespacearm__compute.xhtml#a15a05537a472ee742404821851529327a0db45d2a4141101bdfe48e3314cfbca3">arm_compute::UNDEFINED</a>.</p>
<p class="reference">Referenced by <a class="el" href="validation_2_c_l_2_canny_edge_8cpp_source.xhtml#l00058">arm_compute::test::validation::DATA_TEST_CASE()</a>.</p>
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<h2 class="memtitle"><span class="permalink"><a href="#a390de29c61d4843b56ae0d39fe1f139d">&#9670;&nbsp;</a></span>operator=()</h2>
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<td class="memname"><a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a>&amp; operator= </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_l_canny_edge.xhtml">CLCannyEdge</a> &amp;&#160;</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>
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<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>
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<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="_c_l_canny_edge_8cpp_source.xhtml#l00178">178</a> of file <a class="el" href="_c_l_canny_edge_8cpp_source.xhtml">CLCannyEdge.cpp</a>.</p>
<div class="fragment"><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; <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="l00181"></a><span class="lineno"> 181</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <span class="comment">// Run sobel</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; _sobel-&gt;run();</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; <span class="comment">// Run phase and magnitude calculation</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</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>(_gradient, <span class="keyword">false</span>);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; <span class="comment">// Fill border before non-maxima suppression. Nop for border mode undefined.</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</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>(_border_mag_gradient, <span class="keyword">false</span>);</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; <span class="comment">// Run non max suppresion</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; _nonmax.<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</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>(_non_max_suppr, <span class="keyword">false</span>);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; <span class="comment">// Clear temporary structures and run edge trace</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; _output-&gt;<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; _visited.<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; _recorded.<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; _l1_list_counter.<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; _l1_stack.<a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">clear</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</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>(_edge_trace, <span class="keyword">true</span>);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160;}</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#l00041">CLScheduler.cpp:41</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml_a7b94593f2b06f00d380ec3a3e6abccb2"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml#a7b94593f2b06f00d380ec3a3e6abccb2">arm_compute::ICLTensor::clear</a></div><div class="ttdeci">void clear(cl::CommandQueue &amp;q)</div><div class="ttdoc">Clear the contents of the tensor synchronously.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8cpp_source.xhtml#l00046">ICLTensor.cpp:46</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#l00095">CLScheduler.cpp:95</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>
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<p class="reference">References <a class="el" href="_i_c_l_tensor_8cpp_source.xhtml#l00046">ICLTensor::clear()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler::enqueue()</a>, and <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</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_canny_edge_8h_source.xhtml">CLCannyEdge.h</a></li>
<li>src/runtime/CL/functions/<a class="el" href="_c_l_canny_edge_8cpp_source.xhtml">CLCannyEdge.cpp</a></li>
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