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develop/doc/_sources/api/v2/config/layer.rst.txt
浏览文件 @ 05219ffb
......@@ -445,6 +445,11 @@ smooth_l1_cost
.. autoclass:: paddle.v2.layer.smooth_l1_cost
:noindex:
multibox_loss
--------------
.. autoclass:: paddle.v2.layer.multibox_loss
:noindex:
Check Layer
============
......@@ -468,3 +473,11 @@ prelu
--------
.. autoclass:: paddle.v2.layer.prelu
:noindex:
Detection output Layer
======================
detection_output
----------------
.. autoclass:: paddle.v2.layer.detection_output
:noindex:
develop/doc/api/v2/config/layer.html
浏览文件 @ 05219ffb
......@@ -3560,6 +3560,38 @@ size of input and label are equal. The formula is as follows,</p>
</table>
</dd></dl>
</div>
<div class="section" id="multibox-loss">
<h3>multibox_loss<a class="headerlink" href="#multibox-loss" title="Permalink to this headline"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">multibox_loss</code></dt>
<dd><p>Compute the location loss and the confidence loss for ssd.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input_loc</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer</em>) &#8211; The input predict locations.</li>
<li><strong>input_conf</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer</em>) &#8211; The input priorbox confidence.</li>
<li><strong>priorbox</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input priorbox location and the variance.</li>
<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input label.</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; The number of the classification.</li>
<li><strong>overlap_threshold</strong> (<em>float</em>) &#8211; The threshold of the overlap.</li>
<li><strong>neg_pos_ratio</strong> (<em>float</em>) &#8211; The ratio of the negative bbox to the positive bbox.</li>
<li><strong>neg_overlap</strong> (<em>float</em>) &#8211; The negative bbox overlap threshold.</li>
<li><strong>background_id</strong> (<em>int</em>) &#8211; The background class index.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="check-layer">
......@@ -3678,6 +3710,42 @@ a_i * z_i &amp;\quad \mathrm{otherwise}\end{split}\]</div>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="detection-output-layer">
<h2>Detection output Layer<a class="headerlink" href="#detection-output-layer" title="Permalink to this headline"></a></h2>
<div class="section" id="detection-output">
<h3>detection_output<a class="headerlink" href="#detection-output" title="Permalink to this headline"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">detection_output</code></dt>
<dd><p>Apply the NMS to the output of network and compute the predict bounding
box location.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input_loc</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer.</em>) &#8211; The input predict locations.</li>
<li><strong>input_conf</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer.</em>) &#8211; The input priorbox confidence.</li>
<li><strong>priorbox</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input priorbox location and the variance.</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; The number of the classification.</li>
<li><strong>nms_threshold</strong> (<em>float</em>) &#8211; The Non-maximum suppression threshold.</li>
<li><strong>nms_top_k</strong> (<em>int</em>) &#8211; The bbox number kept of the NMS&#8217;s output</li>
<li><strong>keep_top_k</strong> (<em>int</em>) &#8211; The bbox number kept of the layer&#8217;s output</li>
<li><strong>confidence_threshold</strong> (<em>float</em>) &#8211; The classification confidence threshold</li>
<li><strong>background_id</strong> (<em>int</em>) &#8211; The background class index.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
</div>
......
develop/doc/searchindex.js
浏览文件 @ 05219ffb
因为 它太大了无法显示 source diff 。你可以改为 查看blob。
develop/doc_cn/_sources/api/v2/config/layer.rst.txt
浏览文件 @ 05219ffb
......@@ -445,6 +445,11 @@ smooth_l1_cost
.. autoclass:: paddle.v2.layer.smooth_l1_cost
:noindex:
multibox_loss
--------------
.. autoclass:: paddle.v2.layer.multibox_loss
:noindex:
Check Layer
============
......@@ -468,3 +473,11 @@ prelu
--------
.. autoclass:: paddle.v2.layer.prelu
:noindex:
Detection output Layer
======================
detection_output
----------------
.. autoclass:: paddle.v2.layer.detection_output
:noindex:
develop/doc_cn/api/v2/config/layer.html
浏览文件 @ 05219ffb
......@@ -3565,6 +3565,38 @@ size of input and label are equal. The formula is as follows,</p>
</table>
</dd></dl>
</div>
<div class="section" id="multibox-loss">
<h3>multibox_loss<a class="headerlink" href="#multibox-loss" title="永久链接至标题"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">multibox_loss</code></dt>
<dd><p>Compute the location loss and the confidence loss for ssd.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input_loc</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer</em>) &#8211; The input predict locations.</li>
<li><strong>input_conf</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer</em>) &#8211; The input priorbox confidence.</li>
<li><strong>priorbox</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input priorbox location and the variance.</li>
<li><strong>label</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input label.</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; The number of the classification.</li>
<li><strong>overlap_threshold</strong> (<em>float</em>) &#8211; The threshold of the overlap.</li>
<li><strong>neg_pos_ratio</strong> (<em>float</em>) &#8211; The ratio of the negative bbox to the positive bbox.</li>
<li><strong>neg_overlap</strong> (<em>float</em>) &#8211; The negative bbox overlap threshold.</li>
<li><strong>background_id</strong> (<em>int</em>) &#8211; The background class index.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="check-layer">
......@@ -3683,6 +3715,42 @@ a_i * z_i &amp;\quad \mathrm{otherwise}\end{split}\]</div>
</table>
</dd></dl>
</div>
</div>
<div class="section" id="detection-output-layer">
<h2>Detection output Layer<a class="headerlink" href="#detection-output-layer" title="永久链接至标题"></a></h2>
<div class="section" id="detection-output">
<h3>detection_output<a class="headerlink" href="#detection-output" title="永久链接至标题"></a></h3>
<dl class="class">
<dt>
<em class="property">class </em><code class="descclassname">paddle.v2.layer.</code><code class="descname">detection_output</code></dt>
<dd><p>Apply the NMS to the output of network and compute the predict bounding
box location.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">参数:</th><td class="field-body"><ul class="first simple">
<li><strong>name</strong> (<em>basestring</em>) &#8211; The Layer Name.</li>
<li><strong>input_loc</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer.</em>) &#8211; The input predict locations.</li>
<li><strong>input_conf</strong> (<em>paddle.v2.config_base.Layer | List of paddle.v2.config_base.Layer.</em>) &#8211; The input priorbox confidence.</li>
<li><strong>priorbox</strong> (<em>paddle.v2.config_base.Layer</em>) &#8211; The input priorbox location and the variance.</li>
<li><strong>num_classes</strong> (<em>int</em>) &#8211; The number of the classification.</li>
<li><strong>nms_threshold</strong> (<em>float</em>) &#8211; The Non-maximum suppression threshold.</li>
<li><strong>nms_top_k</strong> (<em>int</em>) &#8211; The bbox number kept of the NMS&#8217;s output</li>
<li><strong>keep_top_k</strong> (<em>int</em>) &#8211; The bbox number kept of the layer&#8217;s output</li>
<li><strong>confidence_threshold</strong> (<em>float</em>) &#8211; The classification confidence threshold</li>
<li><strong>background_id</strong> (<em>int</em>) &#8211; The background class index.</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">返回:</th><td class="field-body"><p class="first last">paddle.v2.config_base.Layer</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
</div>
</div>
......
develop/doc_cn/searchindex.js
浏览文件 @ 05219ffb
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