Deci-AI
/
super-gradients
connected to https://github.com/Deci-AI/super-gradients.git


  
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  <section id="super-gradients-training-datasets-detection-datasets-package">
<h1>super_gradients.training.datasets.detection_datasets package<a class="headerlink" href="#super-gradients-training-datasets-detection-datasets-package" title="Permalink to this headline"></a></h1>
<section id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</section>
<section id="module-super_gradients.training.datasets.detection_datasets.coco_detection">
<span id="super-gradients-training-datasets-detection-datasets-coco-detection-module"></span><h2>super_gradients.training.datasets.detection_datasets.coco_detection module<a class="headerlink" href="#module-super_gradients.training.datasets.detection_datasets.coco_detection" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.coco_detection.COCODetectionDataSet">
<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.datasets.detection_datasets.coco_detection.</span></span><span class="sig-name descname"><span class="pre">COCODetectionDataSet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/coco_detection.html#COCODetectionDataSet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.coco_detection.COCODetectionDataSet" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Generic</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">torch.utils.data.dataset.T_co</span></code>]</p>
<p>COCODetectionDataSet - Detection Data Set Class COCO Data Set</p>
</dd></dl>

</section>
<section id="module-super_gradients.training.datasets.detection_datasets.detection_dataset">
<span id="super-gradients-training-datasets-detection-datasets-detection-dataset-module"></span><h2>super_gradients.training.datasets.detection_datasets.detection_dataset module<a class="headerlink" href="#module-super_gradients.training.datasets.detection_datasets.detection_dataset" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet">
<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.datasets.detection_datasets.detection_dataset.</span></span><span class="sig-name descname"><span class="pre">DetectionDataSet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">root</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">list_file</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img_size</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">416</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">augment</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset_hyper_params</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">dict</span><span class="p"><span class="pre">]</span></span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cache_labels</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cache_images</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sample_loading_method</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">collate_fn</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_extension</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">'.txt'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels_offset</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_inclusion_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">all_classes_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Generic</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">torch.utils.data.dataset.T_co</span></code>]</p>
<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.augment_hsv">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">augment_hsv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hgain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sgain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">vgain</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.augment_hsv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.augment_hsv" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>img</strong> – <dl class="field-list simple">
<dt class="field-odd">param hgain</dt>
<dd class="field-odd"><p></p></dd>
<dt class="field-even">param sgain</dt>
<dd class="field-even"><p></p></dd>
<dt class="field-odd">param vgain</dt>
<dd class="field-odd"><p></p></dd>
</dl>
</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.box_candidates">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">box_candidates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">box1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">box2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wh_thr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ar_thr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">area_thr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.box_candidates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.box_candidates" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>compute candidate boxes</dt><dd><dl class="field-list simple">
<dt class="field-odd">param box1</dt>
<dd class="field-odd"><p>before augment</p>
</dd>
<dt class="field-even">param box2</dt>
<dd class="field-even"><p>after augment</p>
</dd>
<dt class="field-odd">param wh_thr</dt>
<dd class="field-odd"><p>wh_thr (pixels)</p>
</dd>
<dt class="field-even">param ar_thr</dt>
<dd class="field-even"><p>aspect_ratio_thr</p>
</dd>
<dt class="field-odd">param area_thr</dt>
<dd class="field-odd"><p>area_ratio</p>
</dd>
</dl>
</dd>
</dl>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p></p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.exif_size">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">exif_size</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.exif_size"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.exif_size" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>img</strong> – </p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.letterbox">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">letterbox</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(416,</span> <span class="pre">416)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">color</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(128,</span> <span class="pre">128,</span> <span class="pre">128)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">auto</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaleFill</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scaleup</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">interp</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">tuple</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.letterbox"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.letterbox" title="Permalink to this definition"></a></dt>
<dd><p>letterbox - Resizes image to a 32-pixel-multiple rectangle
:param img:
:param new_shape:
:param color:
:param auto:
:param scaleFill:
:param scaleup:
:param interp:
:return:</p>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.load_mosaic">
<span class="sig-name descname"><span class="pre">load_mosaic</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">index</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.load_mosaic"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.load_mosaic" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>load_mosaic - Load images in mosaic format to improve noise handling while training</dt><dd><dl class="field-list simple">
<dt class="field-odd">param index</dt>
<dd class="field-odd"><p></p></dd>
<dt class="field-even">return</dt>
<dd class="field-even"><p></p></dd>
</dl>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.random_perspective">
<span class="sig-name descname"><span class="pre">random_perspective</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">targets</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">()</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">border</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">perspective</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.random_perspective"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.random_perspective" title="Permalink to this definition"></a></dt>
<dd><p>random images and labels using a perspective transform</p>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_loader">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">sample_loader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sample_path</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.sample_loader"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_loader" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>sample_loader - Loads a coco dataset image from path</dt><dd><dl class="field-list simple">
<dt class="field-odd">param sample_path</dt>
<dd class="field-odd"><p></p></dd>
<dt class="field-even">return</dt>
<dd class="field-even"><p></p></dd>
</dl>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_post_process">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">sample_post_process</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.sample_post_process"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_post_process" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>sample_post_process - Normalizes and orders the image to be 3 x img_size x img_size</dt><dd><dl class="field-list simple">
<dt class="field-odd">param image</dt>
<dd class="field-odd"><p></p></dd>
<dt class="field-even">return</dt>
<dd class="field-even"><p></p></dd>
</dl>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_transform">
<span class="sig-name descname"><span class="pre">sample_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.sample_transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.sample_transform" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> – </p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.target_loader">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">target_loader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target_path</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_inclusion_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">all_classes_list</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.target_loader"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.target_loader" title="Permalink to this definition"></a></dt>
<dd><dl class="simple">
<dt>coco_target_loader</dt><dd><p>&#64;param target_path: str, path to target.
&#64;param all_classes_list: list(str) containing all the class names or None when subclassing is disabled.
&#64;param class_inclusion_list: list(str) containing the subclass names or None when subclassing is disabled.</p>
</dd>
</dl>
</dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.target_transform">
<em class="property"><span class="pre">static</span> </em><span class="sig-name descname"><span class="pre">target_transform</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ratio</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">w</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">h</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pad</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/detection_dataset.html#DetectionDataSet.target_transform"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.detection_dataset.DetectionDataSet.target_transform" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>target</strong> – </p></li>
<li><p><strong>ratio</strong> – </p></li>
<li><p><strong>w</strong> – </p></li>
<li><p><strong>h</strong> – </p></li>
<li><p><strong>pad</strong> – </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>

</dd></dl>

</section>
<section id="module-super_gradients.training.datasets.detection_datasets.pascal_voc_detection">
<span id="super-gradients-training-datasets-detection-datasets-pascal-voc-detection-module"></span><h2>super_gradients.training.datasets.detection_datasets.pascal_voc_detection module<a class="headerlink" href="#module-super_gradients.training.datasets.detection_datasets.pascal_voc_detection" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet">
<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.datasets.detection_datasets.pascal_voc_detection.</span></span><span class="sig-name descname"><span class="pre">PascalVOC2012DetectionDataSet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">samples_sub_directory</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">targets_sub_directory</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/pascal_voc_detection.html#PascalVOC2012DetectionDataSet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Generic</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">torch.utils.data.dataset.T_co</span></code>]</p>
<p>PascalVOC2012DtectionDataSet - Detection Data Set Class pascal_voc Data Set</p>
<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet.parse_xml_file">
<span class="sig-name descname"><span class="pre">parse_xml_file</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/pascal_voc_detection.html#PascalVOC2012DetectionDataSet.parse_xml_file"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet.parse_xml_file" title="Permalink to this definition"></a></dt>
<dd></dd></dl>

<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet.target_loader">
<span class="sig-name descname"><span class="pre">target_loader</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">target_path</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">numpy.array</span><a class="reference internal" href="_modules/super_gradients/training/datasets/detection_datasets/pascal_voc_detection.html#PascalVOC2012DetectionDataSet.target_loader"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.datasets.detection_datasets.pascal_voc_detection.PascalVOC2012DetectionDataSet.target_loader" title="Permalink to this definition"></a></dt>
<dd><p>target_loader -               load targets from xml file</p>
<blockquote>
<div><dl class="field-list simple">
<dt class="field-odd">param target_path</dt>
<dd class="field-odd"><p>xml file target path</p>
</dd>
<dt class="field-even">return</dt>
<dd class="field-even"><p>np.array         parsed labels</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>

</dd></dl>

</section>
<section id="module-super_gradients.training.datasets.detection_datasets">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-super_gradients.training.datasets.detection_datasets" title="Permalink to this headline"></a></h2>
</section>
</section>


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