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| <div class="title">CPPDetectionPostProcessLayer Class Reference</div> </div> |
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| |
| <p>CPP Function to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression. |
| <a href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_c_p_p_detection_post_process_layer_8h_source.xhtml">CPPDetectionPostProcessLayer.h</a>></code></p> |
| <div class="dynheader"> |
| Collaboration diagram for CPPDetectionPostProcessLayer:</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:a39f8e99aae48c88ae3b3d98692c4107f"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#a39f8e99aae48c88ae3b3d98692c4107f">CPPDetectionPostProcessLayer</a> (std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > memory_manager=nullptr)</td></tr> |
| <tr class="memdesc:a39f8e99aae48c88ae3b3d98692c4107f"><td class="mdescLeft"> </td><td class="mdescRight">Constructor. <a href="#a39f8e99aae48c88ae3b3d98692c4107f">More...</a><br /></td></tr> |
| <tr class="separator:a39f8e99aae48c88ae3b3d98692c4107f"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa75ee749d85809114423c208e4a84547"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#aa75ee749d85809114423c208e4a84547">CPPDetectionPostProcessLayer</a> (const <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> &)=delete</td></tr> |
| <tr class="memdesc:aa75ee749d85809114423c208e4a84547"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#aa75ee749d85809114423c208e4a84547">More...</a><br /></td></tr> |
| <tr class="separator:aa75ee749d85809114423c208e4a84547"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a760aa257f0b27cc6e0b32cd2b44c6db3"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#a760aa257f0b27cc6e0b32cd2b44c6db3">operator=</a> (const <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> &)=delete</td></tr> |
| <tr class="memdesc:a760aa257f0b27cc6e0b32cd2b44c6db3"><td class="mdescLeft"> </td><td class="mdescRight">Prevent instances of this class from being copied (As this class contains pointers) <a href="#a760aa257f0b27cc6e0b32cd2b44c6db3">More...</a><br /></td></tr> |
| <tr class="separator:a760aa257f0b27cc6e0b32cd2b44c6db3"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ab8136561c7a7d555b3a2c3bf0614986c"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#ab8136561c7a7d555b3a2c3bf0614986c">configure</a> (const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input_box_encoding, const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input_score, const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input_anchors, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output_boxes, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output_classes, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output_scores, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *num_detection, <a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> info=<a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>())</td></tr> |
| <tr class="memdesc:ab8136561c7a7d555b3a2c3bf0614986c"><td class="mdescLeft"> </td><td class="mdescRight">Configure the detection output layer CPP function. <a href="#ab8136561c7a7d555b3a2c3bf0614986c">More...</a><br /></td></tr> |
| <tr class="separator:ab8136561c7a7d555b3a2c3bf0614986c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr> |
| <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </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"> </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="-"/> 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 </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"> </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"> </td></tr> |
| <tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void </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"> </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"> </td></tr> |
| </table><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> |
| Static Public Member Functions</h2></td></tr> |
| <tr class="memitem:a08744faa3f68379fa82bcbd96bbec691"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#a08744faa3f68379fa82bcbd96bbec691">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input_box_encoding, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input_class_score, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input_anchors, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output_boxes, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output_classes, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output_scores, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *num_detection, <a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> info=<a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>())</td></tr> |
| <tr class="memdesc:a08744faa3f68379fa82bcbd96bbec691"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a>. <a href="#a08744faa3f68379fa82bcbd96bbec691">More...</a><br /></td></tr> |
| <tr class="separator:a08744faa3f68379fa82bcbd96bbec691"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>CPP Function to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression. </p> |
| <dl class="section note"><dt>Note</dt><dd>Intended for use with MultiBox detection method. </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_p_p_detection_post_process_layer_8h_source.xhtml#l00046">46</a> of file <a class="el" href="_c_p_p_detection_post_process_layer_8h_source.xhtml">CPPDetectionPostProcessLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a39f8e99aae48c88ae3b3d98692c4107f"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a39f8e99aae48c88ae3b3d98692c4107f">◆ </a></span>CPPDetectionPostProcessLayer() <span class="overload">[1/2]</span></h2> |
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| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> </td> |
| <td>(</td> |
| <td class="paramtype">std::shared_ptr< <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> > </td> |
| <td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
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| <p>Constructor. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml#l00184">184</a> of file <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml">CPPDetectionPostProcessLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  : _memory_group(std::move(memory_manager)), _nms(), _input_box_encoding(<span class="keyword">nullptr</span>), _input_scores(<span class="keyword">nullptr</span>), _input_anchors(<span class="keyword">nullptr</span>), _output_boxes(<span class="keyword">nullptr</span>), _output_classes(<span class="keyword">nullptr</span>),</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  _output_scores(<span class="keyword">nullptr</span>), _num_detection(<span class="keyword">nullptr</span>), _info(), _num_boxes(), _num_classes_with_background(), _num_max_detected_boxes(), _dequantize_scores(<span class="keyword">false</span>), _decoded_boxes(), _decoded_scores(),</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  _selected_indices(), _class_scores(), _input_scores_to_use(<span class="keyword">nullptr</span>)</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> {</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a id="aa75ee749d85809114423c208e4a84547"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#aa75ee749d85809114423c208e4a84547">◆ </a></span>CPPDetectionPostProcessLayer() <span class="overload">[2/2]</span></h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> & </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">delete</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Prevent instances of this class from being copied (As this class contains pointers) </p> |
| |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="ab8136561c7a7d555b3a2c3bf0614986c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ab8136561c7a7d555b3a2c3bf0614986c">◆ </a></span>configure()</h2> |
| |
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| <td class="memname">void configure </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> * </td> |
| <td class="paramname"><em>input_box_encoding</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> * </td> |
| <td class="paramname"><em>input_score</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> * </td> |
| <td class="paramname"><em>input_anchors</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> * </td> |
| <td class="paramname"><em>output_boxes</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> * </td> |
| <td class="paramname"><em>output_classes</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> * </td> |
| <td class="paramname"><em>output_scores</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> * </td> |
| <td class="paramname"><em>num_detection</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> </td> |
| <td class="paramname"><em>info</em> = <code><a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>()</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Configure the detection output layer CPP function. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_box_encoding</td><td>The bounding box input tensor. Data types supported: F32, QASYMM8. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_score</td><td>The class prediction input tensor. Data types supported: Same as <code>input_box_encoding</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_anchors</td><td>The anchors input tensor. Data types supported: Same as <code>input_box_encoding</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_boxes</td><td>The boxes output tensor. Data types supported: F32. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_classes</td><td>The classes output tensor. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_scores</td><td>The scores output tensor. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">num_detection</td><td>The number of output detection. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">info</td><td>(Optional) <a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml" title="Detection Output layer info.">DetectionPostProcessLayerInfo</a> information.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>Output contains all the detections. Of those, only the ones selected by the valid region are valid. </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml#l00191">191</a> of file <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml">CPPDetectionPostProcessLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> {</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input_box_encoding, input_scores, input_anchors, output_boxes, output_classes, output_scores);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  _num_max_detected_boxes = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_detections() * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_classes_per_detection();</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output_boxes->info(), TensorInfo(TensorShape(_kNumCoordBox, _num_max_detected_boxes, _kBatchSize), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output_classes->info(), TensorInfo(TensorShape(_num_max_detected_boxes, _kBatchSize), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output_scores->info(), TensorInfo(TensorShape(_num_max_detected_boxes, _kBatchSize), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*num_detection->info(), TensorInfo(TensorShape(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Perform validation step</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(validate_arguments(input_box_encoding->info(), input_scores->info(), input_anchors->info(), output_boxes->info(), output_classes->info(), output_scores->info(),</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  num_detection->info(),</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, _kBatchSize, _kNumCoordBox));</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  _input_box_encoding = input_box_encoding;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  _input_scores = input_scores;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  _input_anchors = input_anchors;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  _output_boxes = output_boxes;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  _output_classes = output_classes;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  _output_scores = output_scores;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  _num_detection = num_detection;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  _info = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  _num_boxes = input_box_encoding->info()->dimension(1);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  _num_classes_with_background = _input_scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  _dequantize_scores = (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.dequantize_scores() && <a class="code" href="namespacearm__compute.xhtml#a0bee325b210f81bb89fe1f9e15badf9c">is_data_type_quantized</a>(input_box_encoding->info()->data_type()));</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*_decoded_boxes.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>(), TensorInfo(TensorShape(_kNumCoordBox, _input_box_encoding-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1), _kBatchSize), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*_decoded_scores.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>(), TensorInfo(TensorShape(_input_scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), _input_scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1), _kBatchSize), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*_selected_indices.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>(), TensorInfo(TensorShape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.use_regular_nms() ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.detection_per_class() : <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_detections()), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>));</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_classes_per_box = std::min(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_classes_per_detection(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.num_classes());</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*_class_scores.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">info</a>(), TensorInfo(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.use_regular_nms() ? TensorShape(_num_boxes) : TensorShape(_num_boxes * num_classes_per_box), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>::<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">F32</a>));</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  _input_scores_to_use = _dequantize_scores ? &_decoded_scores : _input_scores;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// Manage intermediate buffers</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_decoded_boxes);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_decoded_scores);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_selected_indices);</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_class_scores);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  _nms.<a class="code" href="classarm__compute_1_1_c_p_p_non_maximum_suppression.xhtml#ad8387a0ef4a1e0f7382c06146857e4be">configure</a>(&_decoded_boxes, &_class_scores, &_selected_indices, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.use_regular_nms() ? <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.detection_per_class() : <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_detections(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.nms_score_threshold(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.iou_threshold());</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="comment">// Allocate and reserve intermediate tensors and vectors</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  _decoded_boxes.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  _decoded_scores.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  _selected_indices.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  _class_scores.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-><a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> }</div><div class="ttc" id="namespacearm__compute_xhtml_a0bee325b210f81bb89fe1f9e15badf9c"><div class="ttname"><a href="namespacearm__compute.xhtml#a0bee325b210f81bb89fe1f9e15badf9c">arm_compute::is_data_type_quantized</a></div><div class="ttdeci">bool is_data_type_quantized(DataType dt)</div><div class="ttdoc">Check if a given data type is of quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01117">Utils.h:1117</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_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_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00455">Error.h:455</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00202">Helpers.inl:202</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_tensor_xhtml_a47d74e4e51f9b1a636c4831bd747a97c"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#a47d74e4e51f9b1a636c4831bd747a97c">arm_compute::Tensor::info</a></div><div class="ttdeci">ITensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00033">Tensor.cpp:33</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="classarm__compute_1_1_memory_group_xhtml_a6fc0a49304c152c20a0f6df0634fb3cd"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">arm_compute::MemoryGroup::manage</a></div><div class="ttdeci">void manage(IMemoryManageable *obj) override</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_8h_source.xhtml#l00079">MemoryGroup.h:79</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel.</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="_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_p_p_non_maximum_suppression_xhtml_ad8387a0ef4a1e0f7382c06146857e4be"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_non_maximum_suppression.xhtml#ad8387a0ef4a1e0f7382c06146857e4be">arm_compute::CPPNonMaximumSuppression::configure</a></div><div class="ttdeci">void configure(const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold)</div><div class="ttdoc">Configure the function to perform non maximal suppression.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_non_maximum_suppression_8cpp_source.xhtml#l00031">CPPNonMaximumSuppression.cpp:31</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="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00075">Types.h:75</a></div></div> |
| </div><!-- fragment --> |
| <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="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00455">ARM_COMPUTE_ERROR_THROW_ON</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00202">arm_compute::auto_init_if_empty()</a>, <a class="el" href="_c_p_p_non_maximum_suppression_8cpp_source.xhtml#l00031">CPPNonMaximumSuppression::configure()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="runtime_2_tensor_8cpp_source.xhtml#l00033">Tensor::info()</a>, <a class="el" href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">arm_compute::test::validation::info</a>, <a class="el" href="arm__compute_2core_2_utils_8h_source.xhtml#l01117">arm_compute::is_data_type_quantized()</a>, <a class="el" href="_memory_group_8h_source.xhtml#l00079">MemoryGroup::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, and <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_n_e_detection_post_process_layer_8cpp_source.xhtml#l00042">NEDetectionPostProcessLayer::configure()</a>.</p> |
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| </div> |
| </div> |
| <a id="a760aa257f0b27cc6e0b32cd2b44c6db3"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a760aa257f0b27cc6e0b32cd2b44c6db3">◆ </a></span>operator=()</h2> |
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| <div class="memitem"> |
| <div class="memproto"> |
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| <td class="mlabels-left"> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a>& operator= </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a> & </td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">delete</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Prevent instances of this class from being copied (As this class contains pointers) </p> |
| |
| </div> |
| </div> |
| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
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| <div class="memitem"> |
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| <td class="memname">void run </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
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| <p>Run the kernels contained in the function. </p> |
| <p>For NEON kernels:</p><ul> |
| <li>Multi-threading is used for the kernels which are parallelisable.</li> |
| <li>By default std::thread::hardware_concurrency() threads are used.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl> |
| <p>For OpenCL kernels:</p><ul> |
| <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li> |
| <li>The queue is then flushed.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd> |
| <dd> |
| Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl> |
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| <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_p_p_detection_post_process_layer_8cpp_source.xhtml#l00257">257</a> of file <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml">CPPDetectionPostProcessLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> {</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_classes = _info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#adda82c28c368106734620f105bb0e1e3">num_classes</a>();</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> max_detections = _info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#a23e83519067d74d4f1855d38741151eb">max_detections</a>();</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  DecodeCenterSizeBoxes(_input_box_encoding, _input_anchors, _info, &_decoded_boxes);</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> </div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="comment">// Decode scores if necessary</span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">if</span>(_dequantize_scores)</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  {</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx_c = 0; idx_c < _num_classes_with_background; ++idx_c)</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  {</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx_b = 0; idx_b < _num_boxes; ++idx_b)</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  {</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  *(reinterpret_cast<float *>(_decoded_scores.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(idx_c, idx_b)))) =</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="namespacearm__compute.xhtml#ac1d8253f8b422e143ab989ad2a4d29dd">dequantize_qasymm8</a>(*(reinterpret_cast<qasymm8_t *>(_input_scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(idx_c, idx_b)))), _input_scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>());</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  }</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="comment">// Regular NMS</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">if</span>(_info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#ae1c2cc7a6c3db74d8be5f6e23aa84476">use_regular_nms</a>())</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  {</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  std::vector<int> result_idx_boxes_after_nms;</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  std::vector<int> result_classes_after_nms;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  std::vector<float> result_scores_after_nms;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  std::vector<unsigned int> sorted_indices;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> </div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> c = 0; c < num_classes; ++c)</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="comment">// For each boxes get scores of the boxes for the class c</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < _num_boxes; ++i)</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  {</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  *(reinterpret_cast<float *>(_class_scores.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(i)))) =</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  *(reinterpret_cast<float *>(_input_scores_to_use-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(c + 1, i)))); <span class="comment">// i * _num_classes_with_background + c + 1</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  }</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="comment">// Run Non-maxima Suppression</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  _nms.<a class="code" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> </div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < _info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#a36e65a7f80a07a2393e6a1cadd974740">detection_per_class</a>(); ++i)</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  {</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keyword">const</span> <span class="keyword">auto</span> selected_index = *(reinterpret_cast<int *>(_selected_indices.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(i))));</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordflow">if</span>(selected_index == -1)</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  {</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="comment">// Nms will return -1 for all the last M-elements not valid</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  }</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  result_idx_boxes_after_nms.emplace_back(selected_index);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  result_scores_after_nms.emplace_back((reinterpret_cast<float *>(_class_scores.<a class="code" href="classarm__compute_1_1_tensor.xhtml#a24954cca5108a24706441fd99a7fb04c">buffer</a>()))[selected_index]);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  result_classes_after_nms.emplace_back(c);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  }</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  }</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> </div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="comment">// We select the max detection numbers of the highest score of all classes</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keyword">const</span> <span class="keyword">auto</span> num_selected = result_scores_after_nms.size();</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keyword">const</span> <span class="keyword">auto</span> num_output = std::min<unsigned int>(max_detections, num_selected);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="comment">// Sort selected indices based on result scores</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  sorted_indices.resize(num_selected);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  std::iota(sorted_indices.begin(), sorted_indices.end(), 0);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  std::partial_sort(sorted_indices.data(),</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  sorted_indices.data() + num_output,</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  sorted_indices.data() + num_selected,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  [&](<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> first, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> second)</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  {</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">return</span> result_scores_after_nms[first] > result_scores_after_nms[second];</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  });</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  SaveOutputs(&_decoded_boxes, result_idx_boxes_after_nms, result_scores_after_nms, result_classes_after_nms, sorted_indices,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  num_output, max_detections, _output_boxes, _output_classes, _output_scores, _num_detection);</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  }</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">// Fast NMS</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  {</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_classes_per_box = std::min<unsigned int>(_info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#ad54d768454ff1000504546898078d0de">max_classes_per_detection</a>(), _info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#adda82c28c368106734620f105bb0e1e3">num_classes</a>());</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  std::vector<float> max_scores;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  std::vector<int> box_indices;</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  std::vector<int> max_score_classes;</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> = 0; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> < _num_boxes; ++<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>)</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  std::vector<float> box_scores;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> c = 0; c < num_classes; ++c)</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  {</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  box_scores.emplace_back(*(reinterpret_cast<float *>(_input_scores_to_use-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(c + 1, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>)))));</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  std::vector<unsigned int> max_score_indices;</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  max_score_indices.resize(_info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#adda82c28c368106734620f105bb0e1e3">num_classes</a>());</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  std::iota(max_score_indices.data(), max_score_indices.data() + _info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#adda82c28c368106734620f105bb0e1e3">num_classes</a>(), 0);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  std::partial_sort(max_score_indices.data(),</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  max_score_indices.data() + num_classes_per_box,</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  max_score_indices.data() + num_classes,</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  [&](<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> first, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> second)</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  {</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> box_scores[first] > box_scores[second];</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  });</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < num_classes_per_box; ++i)</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  {</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> score_to_add = box_scores[max_score_indices[i]];</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  *(reinterpret_cast<float *>(_class_scores.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a> * num_classes_per_box + i)))) = score_to_add;</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  max_scores.emplace_back(score_to_add);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  box_indices.emplace_back(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">b</a>);</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  max_score_classes.emplace_back(max_score_indices[i]);</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  }</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="comment">// Run Non-maxima Suppression</span></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  _nms.<a class="code" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  std::vector<unsigned int> selected_indices;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < max_detections; ++i)</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  {</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="comment">// NMS returns M valid indices, the not valid tail is filled with -1</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">if</span>(*(reinterpret_cast<int *>(_selected_indices.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(i)))) == -1)</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  {</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Nms will return -1 for all the last M-elements not valid</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  }</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  selected_indices.emplace_back(*(reinterpret_cast<int *>(_selected_indices.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(Coordinates(i)))));</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  }</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="comment">// We select the max detection numbers of the highest score of all classes</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">const</span> <span class="keyword">auto</span> num_output = std::min<unsigned int>(_info.<a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#a23e83519067d74d4f1855d38741151eb">max_detections</a>(), selected_indices.size());</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  SaveOutputs(&_decoded_boxes, box_indices, max_scores, max_score_classes, selected_indices,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  num_output, max_detections, _output_boxes, _output_classes, _output_scores, _num_detection);</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  }</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> }</div><div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_adbd73147d41e8a640bc299d12613c31e"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">arm_compute::ITensor::ptr_to_element</a></div><div class="ttdeci">uint8_t * ptr_to_element(const Coordinates &id) const</div><div class="ttdoc">Return a pointer to the element at the passed coordinates.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00063">ITensor.h:63</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ac1d8253f8b422e143ab989ad2a4d29dd"><div class="ttname"><a href="namespacearm__compute.xhtml#ac1d8253f8b422e143ab989ad2a4d29dd">arm_compute::dequantize_qasymm8</a></div><div class="ttdeci">float dequantize_qasymm8(uint8_t value, const INFO_TYPE &qinfo)</div><div class="ttdoc">Dequantize a value given an unsigned 8-bit asymmetric quantization scheme.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00338">QuantizationInfo.h:338</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_aa76b4a6e74940dabc5b7fc6b2dab3545"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aa76b4a6e74940dabc5b7fc6b2dab3545">arm_compute::test::validation::b</a></div><div class="ttdeci">SimpleTensor< float > b</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_d_f_t_8cpp_source.xhtml#l00157">DFT.cpp:157</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_detection_post_process_layer_info_xhtml_a23e83519067d74d4f1855d38741151eb"><div class="ttname"><a href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#a23e83519067d74d4f1855d38741151eb">arm_compute::DetectionPostProcessLayerInfo::max_detections</a></div><div class="ttdeci">unsigned int max_detections() const</div><div class="ttdoc">Get max detections.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01134">Types.h:1134</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_detection_post_process_layer_info_xhtml_ae1c2cc7a6c3db74d8be5f6e23aa84476"><div class="ttname"><a href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#ae1c2cc7a6c3db74d8be5f6e23aa84476">arm_compute::DetectionPostProcessLayerInfo::use_regular_nms</a></div><div class="ttdeci">bool use_regular_nms() const</div><div class="ttdoc">Get if use regular nms.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01164">Types.h:1164</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="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_detection_post_process_layer_info_xhtml_ad54d768454ff1000504546898078d0de"><div class="ttname"><a href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#ad54d768454ff1000504546898078d0de">arm_compute::DetectionPostProcessLayerInfo::max_classes_per_detection</a></div><div class="ttdeci">unsigned int max_classes_per_detection() const</div><div class="ttdoc">Get max_classes per detection.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01139">Types.h:1139</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_detection_post_process_layer_info_xhtml_a36e65a7f80a07a2393e6a1cadd974740"><div class="ttname"><a href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#a36e65a7f80a07a2393e6a1cadd974740">arm_compute::DetectionPostProcessLayerInfo::detection_per_class</a></div><div class="ttdeci">unsigned int detection_per_class() const</div><div class="ttdoc">Get detection per class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01144">Types.h:1144</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_detection_post_process_layer_info_xhtml_adda82c28c368106734620f105bb0e1e3"><div class="ttname"><a href="classarm__compute_1_1_detection_post_process_layer_info.xhtml#adda82c28c368106734620f105bb0e1e3">arm_compute::DetectionPostProcessLayerInfo::num_classes</a></div><div class="ttdeci">unsigned int num_classes() const</div><div class="ttdoc">Get num classes.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01159">Types.h:1159</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml_a24954cca5108a24706441fd99a7fb04c"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#a24954cca5108a24706441fd99a7fb04c">arm_compute::Tensor::buffer</a></div><div class="ttdeci">uint8_t * buffer() const override</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00043">Tensor.cpp:43</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_p_p_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICPPSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_p_p_simple_function_8cpp_source.xhtml#l00035">ICPPSimpleFunction.cpp:35</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_p_p_2_d_f_t_8cpp_source.xhtml#l00157">arm_compute::test::validation::b</a>, <a class="el" href="runtime_2_tensor_8cpp_source.xhtml#l00043">Tensor::buffer()</a>, <a class="el" href="_quantization_info_8h_source.xhtml#l00338">arm_compute::dequantize_qasymm8()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l01144">DetectionPostProcessLayerInfo::detection_per_class()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l01139">DetectionPostProcessLayerInfo::max_classes_per_detection()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l01134">DetectionPostProcessLayerInfo::max_detections()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l01159">DetectionPostProcessLayerInfo::num_classes()</a>, <a class="el" href="_i_tensor_8h_source.xhtml#l00063">ITensor::ptr_to_element()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">ITensorInfo::quantization_info()</a>, <a class="el" href="_i_c_p_p_simple_function_8cpp_source.xhtml#l00035">ICPPSimpleFunction::run()</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l01164">DetectionPostProcessLayerInfo::use_regular_nms()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_n_e_detection_post_process_layer_8cpp_source.xhtml#l00087">NEDetectionPostProcessLayer::run()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a08744faa3f68379fa82bcbd96bbec691"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a08744faa3f68379fa82bcbd96bbec691">◆ </a></span>validate()</h2> |
| |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input_box_encoding</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input_class_score</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>input_anchors</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output_boxes</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output_classes</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output_scores</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>num_detection</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> </td> |
| <td class="paramname"><em>info</em> = <code><a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>()</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml">CPPDetectionPostProcessLayer</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_box_encoding</td><td>The bounding box input tensor info. Data types supported: F32, QASYMM8. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_class_score</td><td>The class prediction input tensor info. Data types supported: F32, QASYMM8. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">input_anchors</td><td>The anchors input tensor. Data types supported: F32, QASYMM8. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_boxes</td><td>The output tensor. Data types supported: F32. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_classes</td><td>The output tensor. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output_scores</td><td>The output tensor. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">num_detection</td><td>The number of output detection. Data types supported: Same as <code>output_boxes</code>. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">info</td><td>(Optional) <a class="el" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml" title="Detection Output layer info.">DetectionPostProcessLayerInfo</a> information.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml#l00241">241</a> of file <a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml">CPPDetectionPostProcessLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> {</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kBatchSize = 1;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kNumCoordBox = 4;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keyword">const</span> TensorInfo _decoded_boxes_info = TensorInfo(TensorShape(kNumCoordBox, input_box_encoding->dimension(1)), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keyword">const</span> TensorInfo _decoded_scores_info = TensorInfo(TensorShape(input_box_encoding->dimension(1)), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keyword">const</span> TensorInfo _selected_indices_info = TensorInfo(TensorShape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_detections()), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>);</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_p_p_non_maximum_suppression.xhtml#ac36104d178e32cb6e30af07e69d978d4">CPPNonMaximumSuppression::validate</a>(&_decoded_boxes_info, &_decoded_scores_info, &_selected_indices_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.max_detections(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.nms_score_threshold(),</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.iou_threshold()));</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(validate_arguments(input_box_encoding, input_class_score, input_anchors, output_boxes, output_classes, output_scores, num_detection, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, kBatchSize, kNumCoordBox));</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">return</span> Status{};</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> }</div><div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00204">Error.h:204</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="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="classarm__compute_1_1_c_p_p_non_maximum_suppression_xhtml_ac36104d178e32cb6e30af07e69d978d4"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_non_maximum_suppression.xhtml#ac36104d178e32cb6e30af07e69d978d4">arm_compute::CPPNonMaximumSuppression::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *bboxes, const ITensorInfo *scores, const ITensorInfo *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold)</div><div class="ttdoc">Static function to check if given arguments will lead to a valid configuration of CPPNonMaximumSuppre...</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_non_maximum_suppression_8cpp_source.xhtml#l00040">CPPNonMaximumSuppression.cpp:40</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="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00204">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">arm_compute::test::validation::info</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, and <a class="el" href="_c_p_p_non_maximum_suppression_8cpp_source.xhtml#l00040">CPPNonMaximumSuppression::validate()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_n_e_detection_post_process_layer_8cpp_source.xhtml#l00073">NEDetectionPostProcessLayer::validate()</a>.</p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>arm_compute/runtime/CPP/functions/<a class="el" href="_c_p_p_detection_post_process_layer_8h_source.xhtml">CPPDetectionPostProcessLayer.h</a></li> |
| <li>src/runtime/CPP/functions/<a class="el" href="_c_p_p_detection_post_process_layer_8cpp_source.xhtml">CPPDetectionPostProcessLayer.cpp</a></li> |
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