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  89.   <section id="super-gradients-training-metrics-package">
    90. 

  90. <h1>super_gradients.training.metrics package<a class="headerlink" href="#super-gradients-training-metrics-package" title="Permalink to this headline"></a></h1>
    91. 

  91. <section id="submodules">
    92. 

  92. <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
    93. 

  93. </section>
    94. 

  94. <section id="module-super_gradients.training.metrics.classification_metrics">
    95. 

  95. <span id="super-gradients-training-metrics-classification-metrics-module"></span><h2>super_gradients.training.metrics.classification_metrics module<a class="headerlink" href="#module-super_gradients.training.metrics.classification_metrics" title="Permalink to this headline"></a></h2>
    96. 

  96. <dl class="py function">
    97. 

  97. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.accuracy">
    98. 

  98. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.classification_metrics.</span></span><span class="sig-name descname"><span class="pre">accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topk</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(1)</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.accuracy" title="Permalink to this definition"></a></dt>
    99. 

  99. <dd><p>Computes the precision&#64;k for the specified values of k
    100. 

  100. :param output: Tensor / Numpy / List</p>
    101. 

  101. <blockquote>
    102. 

  102. <div><p>The prediction</p>
    103. 

  103. </div></blockquote>
    104. 

  104. <dl class="field-list simple">
    105. 

  105. <dt class="field-odd">Parameters</dt>
    106. 

  106. <dd class="field-odd"><ul class="simple">
    107. 

  107. <li><p><strong>target</strong> – Tensor / Numpy / List
    108. 

  108. The corresponding lables</p></li>
    109. 

  109. <li><p><strong>topk</strong> – tuple
    110. 

  110. The type of accuracy to calculate, e.g. topk=(1,5) returns accuracy for top-1 and top-5</p></li>
    111. 

  111. </ul>
    112. 

  112. </dd>
    113. 

  113. </dl>
    114. 

  114. </dd></dl>
    115. 

  115. 

  116. <dl class="py class">
    117. 

  117. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy">
    118. 

  118. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.classification_metrics.</span></span><span class="sig-name descname"><span class="pre">Accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy" title="Permalink to this definition"></a></dt>
    119. 

  119. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.accuracy.Accuracy</span></code></p>
    120. 

  120. <dl class="py method">
    121. 

  121. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy.update">
    122. 

  122. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Accuracy.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy.update" title="Permalink to this definition"></a></dt>
    123. 

  123. <dd><p>Update state with predictions and targets. See
    124. 

  124. <span class="xref std std-ref">pages/classification:input types</span> for more information on input
    125. 

  125. types.</p>
    126. 

  126. <dl class="field-list simple">
    127. 

  127. <dt class="field-odd">Parameters</dt>
    128. 

  128. <dd class="field-odd"><ul class="simple">
    129. 

  129. <li><p><strong>preds</strong> – Predictions from model (logits, probabilities, or labels)</p></li>
    130. 

  130. <li><p><strong>target</strong> – Ground truth labels</p></li>
    131. 

  131. </ul>
    132. 

  132. </dd>
    133. 

  133. </dl>
    134. 

  134. </dd></dl>
    135. 

  135. 

  136. <dl class="py attribute">
    137. 

  137. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy.correct">
    138. 

  138. <span class="sig-name descname"><span class="pre">correct</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy.correct" title="Permalink to this definition"></a></dt>
    139. 

  139. <dd></dd></dl>
    140. 

  140. 

  141. <dl class="py attribute">
    142. 

  142. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy.total">
    143. 

  143. <span class="sig-name descname"><span class="pre">total</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy.total" title="Permalink to this definition"></a></dt>
    144. 

  144. <dd></dd></dl>
    145. 

  145. 

  146. <dl class="py attribute">
    147. 

  147. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy.mode">
    148. 

  148. <span class="sig-name descname"><span class="pre">mode</span></span><em class="property"><span class="pre">:</span> <span class="pre">DataType</span></em><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy.mode" title="Permalink to this definition"></a></dt>
    149. 

  149. <dd></dd></dl>
    150. 

  150. 

  151. <dl class="py attribute">
    152. 

  152. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Accuracy.training">
    153. 

  153. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Accuracy.training" title="Permalink to this definition"></a></dt>
    154. 

  154. <dd></dd></dl>
    155. 

  155. 

  156. </dd></dl>
    157. 

  157. 

  158. <dl class="py class">
    159. 

  159. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Top5">
    160. 

  160. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.classification_metrics.</span></span><span class="sig-name descname"><span class="pre">Top5</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Top5" title="Permalink to this definition"></a></dt>
    161. 

  161. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    162. 

  162. <dl class="py method">
    163. 

  163. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Top5.update">
    164. 

  164. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Top5.update" title="Permalink to this definition"></a></dt>
    165. 

  165. <dd><p>Override this method to update the state variables of your metric class.</p>
    166. 

  166. </dd></dl>
    167. 

  167. 

  168. <dl class="py method">
    169. 

  169. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.Top5.compute">
    170. 

  170. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.Top5.compute" title="Permalink to this definition"></a></dt>
    171. 

  171. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    172. 

  172. distributed backend.</p>
    173. 

  173. </dd></dl>
    174. 

  174. 

  175. </dd></dl>
    176. 

  176. 

  177. <dl class="py class">
    178. 

  178. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric">
    179. 

  179. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.classification_metrics.</span></span><span class="sig-name descname"><span class="pre">ToyTestClassificationMetric</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric" title="Permalink to this definition"></a></dt>
    180. 

  180. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    181. 

  181. <p>Dummy classification Mettric object returning 0 always (for testing).</p>
    182. 

  182. <dl class="py method">
    183. 

  183. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric.update">
    184. 

  184. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">None</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric.update" title="Permalink to this definition"></a></dt>
    185. 

  185. <dd><p>Override this method to update the state variables of your metric class.</p>
    186. 

  186. </dd></dl>
    187. 

  187. 

  188. <dl class="py method">
    189. 

  189. <dt class="sig sig-object py" id="super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric.compute">
    190. 

  190. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.classification_metrics.ToyTestClassificationMetric.compute" title="Permalink to this definition"></a></dt>
    191. 

  191. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    192. 

  192. distributed backend.</p>
    193. 

  193. </dd></dl>
    194. 

  194. 

  195. </dd></dl>
    196. 

  196. 

  197. </section>
    198. 

  198. <section id="module-super_gradients.training.metrics.detection_metrics">
    199. 

  199. <span id="super-gradients-training-metrics-detection-metrics-module"></span><h2>super_gradients.training.metrics.detection_metrics module<a class="headerlink" href="#module-super_gradients.training.metrics.detection_metrics" title="Permalink to this headline"></a></h2>
    200. 

  200. <dl class="py class">
    201. 

  201. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics">
    202. 

  202. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.detection_metrics.</span></span><span class="sig-name descname"><span class="pre">DetectionMetrics</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">num_cls:</span> <span class="pre">int</span></em>, <em class="sig-param"><span class="pre">post_prediction_callback:</span> <span class="pre">Optional[super_gradients.training.utils.detection_utils.DetectionPostPredictionCallback]</span> <span class="pre">=</span> <span class="pre">None</span></em>, <em class="sig-param"><span class="pre">normalize_targets:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></em>, <em class="sig-param"><span class="pre">iou_thres:</span> <span class="pre">super_gradients.training.utils.detection_utils.IouThreshold</span> <span class="pre">=</span> <span class="pre">&lt;IouThreshold.MAP_05_TO_095:</span> <span class="pre">(0.5</span></em>, <em class="sig-param"><span class="pre">0.95)&gt;</span></em>, <em class="sig-param"><span class="pre">recall_thres:</span> <span class="pre">Optional[torch.Tensor]</span> <span class="pre">=</span> <span class="pre">None</span></em>, <em class="sig-param"><span class="pre">score_thres:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">0.1</span></em>, <em class="sig-param"><span class="pre">top_k_predictions:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">100</span></em>, <em class="sig-param"><span class="pre">dist_sync_on_step:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></em>, <em class="sig-param"><span class="pre">accumulate_on_cpu:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics" title="Permalink to this definition"></a></dt>
    203. 

  203. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    204. 

  204. <p>Metric class for computing F1, Precision, Recall and Mean Average Precision.</p>
    205. 

  205. <dl class="py attribute">
    206. 

  206. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.num_cls">
    207. 

  207. <span class="sig-name descname"><span class="pre">num_cls</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.num_cls" title="Permalink to this definition"></a></dt>
    208. 

  208. <dd><p>Number of classes.</p>
    209. 

  209. </dd></dl>
    210. 

  210. 

  211. <dl class="py attribute">
    212. 

  212. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.post_prediction_callback">
    213. 

  213. <span class="sig-name descname"><span class="pre">post_prediction_callback</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.post_prediction_callback" title="Permalink to this definition"></a></dt>
    214. 

  214. <dd><p>DetectionPostPredictionCallback to be applied on net’s output prior
    215. 

  215. to the metric computation (NMS).</p>
    216. 

  216. </dd></dl>
    217. 

  217. 

  218. <dl class="py attribute">
    219. 

  219. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.normalize_targets">
    220. 

  220. <span class="sig-name descname"><span class="pre">normalize_targets</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.normalize_targets" title="Permalink to this definition"></a></dt>
    221. 

  221. <dd><p>Whether to normalize bbox coordinates by image size (default=False).</p>
    222. 

  222. </dd></dl>
    223. 

  223. 

  224. <dl class="py attribute">
    225. 

  225. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.iou_thresholds">
    226. 

  226. <span class="sig-name descname"><span class="pre">iou_thresholds</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.iou_thresholds" title="Permalink to this definition"></a></dt>
    227. 

  227. <dd><p>IoU threshold to compute the mAP (default=torch.linspace(0.5, 0.95, 10)).</p>
    228. 

  228. </dd></dl>
    229. 

  229. 

  230. <dl class="py attribute">
    231. 

  231. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.recall_thresholds">
    232. 

  232. <span class="sig-name descname"><span class="pre">recall_thresholds</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.recall_thresholds" title="Permalink to this definition"></a></dt>
    233. 

  233. <dd><p>Recall threshold to compute the mAP (default=torch.linspace(0, 1, 101)).</p>
    234. 

  234. </dd></dl>
    235. 

  235. 

  236. <dl class="py attribute">
    237. 

  237. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.score_threshold">
    238. 

  238. <span class="sig-name descname"><span class="pre">score_threshold</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.score_threshold" title="Permalink to this definition"></a></dt>
    239. 

  239. <dd><p>Score threshold to compute Recall, Precision and F1 (default=0.1)</p>
    240. 

  240. </dd></dl>
    241. 

  241. 

  242. <dl class="py attribute">
    243. 

  243. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.top_k_predictions">
    244. 

  244. <span class="sig-name descname"><span class="pre">top_k_predictions</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.top_k_predictions" title="Permalink to this definition"></a></dt>
    245. 

  245. <dd><p>Number of predictions per class used to compute metrics, ordered by confidence score
    246. 

  246. (default=100)</p>
    247. 

  247. </dd></dl>
    248. 

  248. 

  249. <dl class="py attribute">
    250. 

  250. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.dist_sync_on_step">
    251. 

  251. <span class="sig-name descname"><span class="pre">dist_sync_on_step</span></span><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.dist_sync_on_step" title="Permalink to this definition"></a></dt>
    252. 

  252. <dd><p>Synchronize metric state across processes at each <code class="docutils literal notranslate"><span class="pre">forward()</span></code>
    253. 

  253. before returning the value at the step. (default=False)</p>
    254. 

  254. <blockquote>
    255. 

  255. <div><dl class="simple">
    256. 

  256. <dt>accumulate_on_cpu:     Run on CPU regardless of device used in other parts.</dt><dd><p>This is to avoid “CUDA out of memory” that might happen on GPU (default False)</p>
    257. 

  257. </dd>
    258. 

  258. </dl>
    259. 

  259. </div></blockquote>
    260. 

  260. </dd></dl>
    261. 

  261. 

  262. <dl class="py method">
    263. 

  263. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.update">
    264. 

  264. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</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">inputs</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch._VariableFunctionsClass.tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">crowd_targets</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">torch.Tensor</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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.update" title="Permalink to this definition"></a></dt>
    265. 

  265. <dd><p>Apply NMS and match all the predictions and targets of a given batch, and update the metric state accordingly.</p>
    266. 

  266. <dl class="simple">
    267. 

  267. <dt>:param preds<span class="classifier">Raw output of the model, the format might change from one model to another, but has to fit</span></dt><dd><p>the input format of the post_prediction_callback</p>
    268. 

  268. </dd>
    269. 

  269. </dl>
    270. 

  270. <dl class="field-list simple">
    271. 

  271. <dt class="field-odd">Parameters</dt>
    272. 

  272. <dd class="field-odd"><ul class="simple">
    273. 

  273. <li><p><strong>target</strong> – Targets for all images of shape (total_num_targets, 6)
    274. 

  274. format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]</p></li>
    275. 

  275. <li><p><strong>device</strong> – Device to run on</p></li>
    276. 

  276. <li><p><strong>inputs</strong> – Input image tensor of shape (batch_size, n_img, height, width)</p></li>
    277. 

  277. <li><p><strong>crowd_targets</strong> – Crowd targets for all images of shape (total_num_targets, 6)
    278. 

  278. format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]</p></li>
    279. 

  279. </ul>
    280. 

  280. </dd>
    281. 

  281. </dl>
    282. 

  282. </dd></dl>
    283. 

  283. 

  284. <dl class="py method">
    285. 

  285. <dt class="sig sig-object py" id="super_gradients.training.metrics.detection_metrics.DetectionMetrics.compute">
    286. 

  286. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span> </span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span> </span><span class="pre">torch.Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.detection_metrics.DetectionMetrics.compute" title="Permalink to this definition"></a></dt>
    287. 

  287. <dd><p>Compute the metrics for all the accumulated results.
    288. 

  288. :return: Metrics of interest</p>
    289. 

  289. </dd></dl>
    290. 

  290. 

  291. </dd></dl>
    292. 

  292. 

  293. </section>
    294. 

  294. <section id="module-super_gradients.training.metrics.metric_utils">
    295. 

  295. <span id="super-gradients-training-metrics-metric-utils-module"></span><h2>super_gradients.training.metrics.metric_utils module<a class="headerlink" href="#module-super_gradients.training.metrics.metric_utils" title="Permalink to this headline"></a></h2>
    296. 

  296. <dl class="py function">
    297. 

  297. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.get_logging_values">
    298. 

  298. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">get_logging_values</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">loss_loggings</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><a class="reference internal" href="super_gradients.training.utils.html#super_gradients.training.utils.utils.AverageMeter" title="super_gradients.training.utils.utils.AverageMeter"><span class="pre">super_gradients.training.utils.utils.AverageMeter</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">metrics</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torchmetrics.collections.MetricCollection</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">criterion</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/metrics/metric_utils.html#get_logging_values"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.get_logging_values" title="Permalink to this definition"></a></dt>
    299. 

  299. <dd><p>&#64;param loss_loggings: AverageMeter running average for the loss items
    300. 

  300. &#64;param metrics: MetricCollection object for running user specified metrics
    301. 

  301. &#64;param criterion the object loss_loggings average meter is monitoring, when set to None- only the metrics values are
    302. 

  302. computed and returned.</p>
    303. 

  303. <p>&#64;return: tuple of the computed values</p>
    304. 

  304. </dd></dl>
    305. 

  305. 

  306. <dl class="py function">
    307. 

  307. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.get_metrics_titles">
    308. 

  308. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">get_metrics_titles</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">metrics_collection</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torchmetrics.collections.MetricCollection</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/metric_utils.html#get_metrics_titles"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.get_metrics_titles" title="Permalink to this definition"></a></dt>
    309. 

  309. <dd><p>&#64;param metrics_collection: MetricCollection object for running user specified metrics
    310. 

  310. &#64;return: list of all the names of the computed values list(str)</p>
    311. 

  311. </dd></dl>
    312. 

  312. 

  313. <dl class="py function">
    314. 

  314. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.get_metrics_results_tuple">
    315. 

  315. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">get_metrics_results_tuple</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">metrics_collection</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torchmetrics.collections.MetricCollection</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/metric_utils.html#get_metrics_results_tuple"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.get_metrics_results_tuple" title="Permalink to this definition"></a></dt>
    316. 

  316. <dd><p>&#64;param metrics_collection: metrics collection of the user specified metrics
    317. 

  317. &#64;type metrics_collection
    318. 

  318. &#64;return: tuple of metrics values</p>
    319. 

  319. </dd></dl>
    320. 

  320. 

  321. <dl class="py function">
    322. 

  322. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.flatten_metrics_dict">
    323. 

  323. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">flatten_metrics_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">metrics_dict</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/metric_utils.html#flatten_metrics_dict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.flatten_metrics_dict" title="Permalink to this definition"></a></dt>
    324. 

  324. <dd><p>:param metrics_dict - dictionary of metric values where values can also be dictionaries containing subvalues
    325. 

  325. (in the case of compound metrics)</p>
    326. 

  326. <p>&#64;return: flattened dict of metric values i.e {metric1_name: metric1_value…}</p>
    327. 

  327. </dd></dl>
    328. 

  328. 

  329. <dl class="py function">
    330. 

  330. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.get_metrics_dict">
    331. 

  331. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">get_metrics_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">metrics_tuple</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metrics_collection</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss_logging_item_names</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/metric_utils.html#get_metrics_dict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.get_metrics_dict" title="Permalink to this definition"></a></dt>
    332. 

  332. <dd><p>Returns a dictionary with the epoch results as values and their names as keys.
    333. 

  333. &#64;param metrics_tuple: the result tuple
    334. 

  334. &#64;param metrics_collection: MetricsCollection
    335. 

  335. &#64;param loss_logging_item_names: loss component’s names.
    336. 

  336. &#64;return: dict</p>
    337. 

  337. </dd></dl>
    338. 

  338. 

  339. <dl class="py function">
    340. 

  340. <dt class="sig sig-object py" id="super_gradients.training.metrics.metric_utils.get_train_loop_description_dict">
    341. 

  341. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.metric_utils.</span></span><span class="sig-name descname"><span class="pre">get_train_loop_description_dict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">metrics_tuple</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metrics_collection</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">loss_logging_item_names</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">log_items</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/metric_utils.html#get_train_loop_description_dict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.metric_utils.get_train_loop_description_dict" title="Permalink to this definition"></a></dt>
    342. 

  342. <dd><dl class="simple">
    343. 

  343. <dt>Returns a dictionary with the epoch’s logging items as values and their names as keys, with the purpose of</dt><dd><p>passing it as a description to tqdm’s progress bar.</p>
    344. 

  344. </dd>
    345. 

  345. </dl>
    346. 

  346. <p>&#64;param metrics_tuple: the result tuple
    347. 

  347. &#64;param metrics_collection: MetricsCollection
    348. 

  348. &#64;param loss_logging_item_names: loss component’s names.
    349. 

  349. &#64;param log_items additional logging items to be rendered.
    350. 

  350. &#64;return: dict</p>
    351. 

  351. </dd></dl>
    352. 

  352. 

  353. </section>
    354. 

  354. <section id="module-super_gradients.training.metrics.segmentation_metrics">
    355. 

  355. <span id="super-gradients-training-metrics-segmentation-metrics-module"></span><h2>super_gradients.training.metrics.segmentation_metrics module<a class="headerlink" href="#module-super_gradients.training.metrics.segmentation_metrics" title="Permalink to this headline"></a></h2>
    356. 

  356. <dl class="py function">
    357. 

  357. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.batch_pix_accuracy">
    358. 

  358. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">batch_pix_accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">predict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#batch_pix_accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.batch_pix_accuracy" title="Permalink to this definition"></a></dt>
    359. 

  359. <dd><p>Batch Pixel Accuracy
    360. 

  360. :param predict: input 4D tensor
    361. 

  361. :param target: label 3D tensor</p>
    362. 

  362. </dd></dl>
    363. 

  363. 

  364. <dl class="py function">
    365. 

  365. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.batch_intersection_union">
    366. 

  366. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">batch_intersection_union</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">predict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nclass</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#batch_intersection_union"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.batch_intersection_union" title="Permalink to this definition"></a></dt>
    367. 

  367. <dd><p>Batch Intersection of Union
    368. 

  368. :param predict: input 4D tensor
    369. 

  369. :param target: label 3D tensor
    370. 

  370. :param nclass: number of categories (int)</p>
    371. 

  371. </dd></dl>
    372. 

  372. 

  373. <dl class="py function">
    374. 

  374. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.pixel_accuracy">
    375. 

  375. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">pixel_accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">im_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">im_lab</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#pixel_accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.pixel_accuracy" title="Permalink to this definition"></a></dt>
    376. 

  376. <dd></dd></dl>
    377. 

  377. 

  378. <dl class="py function">
    379. 

  379. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.intersection_and_union">
    380. 

  380. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">intersection_and_union</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">im_pred</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">im_lab</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_class</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#intersection_and_union"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.intersection_and_union" title="Permalink to this definition"></a></dt>
    381. 

  381. <dd></dd></dl>
    382. 

  382. 

  383. <dl class="py class">
    384. 

  384. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn">
    385. 

  385. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">AbstractMetricsArgsPrepFn</span></span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#AbstractMetricsArgsPrepFn"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="Permalink to this definition"></a></dt>
    386. 

  386. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">abc.ABC</span></code></p>
    387. 

  387. <p>Abstract preprocess metrics arguments class.</p>
    388. 

  388. </dd></dl>
    389. 

  389. 

  390. <dl class="py class">
    391. 

  391. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.PreprocessSegmentationMetricsArgs">
    392. 

  392. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">PreprocessSegmentationMetricsArgs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">apply_arg_max</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">apply_sigmoid</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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PreprocessSegmentationMetricsArgs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.PreprocessSegmentationMetricsArgs" title="Permalink to this definition"></a></dt>
    393. 

  393. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></code></a></p>
    394. 

  394. <p>Default segmentation inputs preprocess function before updating segmentation metrics, handles multiple inputs and
    395. 

  395. apply normalizations.</p>
    396. 

  396. </dd></dl>
    397. 

  397. 

  398. <dl class="py class">
    399. 

  399. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.PixelAccuracy">
    400. 

  400. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">PixelAccuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ignore_label</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-</span> <span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.PixelAccuracy" title="Permalink to this definition"></a></dt>
    401. 

  401. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    402. 

  402. <dl class="py method">
    403. 

  403. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.PixelAccuracy.update">
    404. 

  404. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.PixelAccuracy.update" title="Permalink to this definition"></a></dt>
    405. 

  405. <dd><p>Override this method to update the state variables of your metric class.</p>
    406. 

  406. </dd></dl>
    407. 

  407. 

  408. <dl class="py method">
    409. 

  409. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.PixelAccuracy.compute">
    410. 

  410. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.PixelAccuracy.compute" title="Permalink to this definition"></a></dt>
    411. 

  411. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    412. 

  412. distributed backend.</p>
    413. 

  413. </dd></dl>
    414. 

  414. 

  415. </dd></dl>
    416. 

  416. 

  417. <dl class="py class">
    418. 

  418. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.IoU">
    419. 

  419. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">IoU</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_classes</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">reduction</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">'elementwise_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#IoU"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.IoU" title="Permalink to this definition"></a></dt>
    420. 

  420. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.jaccard.JaccardIndex</span></code></p>
    421. 

  421. <dl class="py method">
    422. 

  422. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.IoU.update">
    423. 

  423. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#IoU.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.IoU.update" title="Permalink to this definition"></a></dt>
    424. 

  424. <dd><p>Update state with predictions and targets.</p>
    425. 

  425. <dl class="field-list simple">
    426. 

  426. <dt class="field-odd">Parameters</dt>
    427. 

  427. <dd class="field-odd"><ul class="simple">
    428. 

  428. <li><p><strong>preds</strong> – Predictions from model</p></li>
    429. 

  429. <li><p><strong>target</strong> – Ground truth values</p></li>
    430. 

  430. </ul>
    431. 

  431. </dd>
    432. 

  432. </dl>
    433. 

  433. </dd></dl>
    434. 

  434. 

  435. <dl class="py attribute">
    436. 

  436. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.IoU.confmat">
    437. 

  437. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.IoU.confmat" title="Permalink to this definition"></a></dt>
    438. 

  438. <dd></dd></dl>
    439. 

  439. 

  440. <dl class="py attribute">
    441. 

  441. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.IoU.training">
    442. 

  442. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.IoU.training" title="Permalink to this definition"></a></dt>
    443. 

  443. <dd></dd></dl>
    444. 

  444. 

  445. </dd></dl>
    446. 

  446. 

  447. <dl class="py class">
    448. 

  448. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.Dice">
    449. 

  449. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">Dice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_classes</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">reduction</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">'elementwise_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.Dice" title="Permalink to this definition"></a></dt>
    450. 

  450. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.jaccard.JaccardIndex</span></code></p>
    451. 

  451. <dl class="py method">
    452. 

  452. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.Dice.update">
    453. 

  453. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.Dice.update" title="Permalink to this definition"></a></dt>
    454. 

  454. <dd><p>Update state with predictions and targets.</p>
    455. 

  455. <dl class="field-list simple">
    456. 

  456. <dt class="field-odd">Parameters</dt>
    457. 

  457. <dd class="field-odd"><ul class="simple">
    458. 

  458. <li><p><strong>preds</strong> – Predictions from model</p></li>
    459. 

  459. <li><p><strong>target</strong> – Ground truth values</p></li>
    460. 

  460. </ul>
    461. 

  461. </dd>
    462. 

  462. </dl>
    463. 

  463. </dd></dl>
    464. 

  464. 

  465. <dl class="py method">
    466. 

  466. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.Dice.compute">
    467. 

  467. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <span class="pre">torch.Tensor</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.Dice.compute" title="Permalink to this definition"></a></dt>
    468. 

  468. <dd><p>Computes Dice coefficient</p>
    469. 

  469. </dd></dl>
    470. 

  470. 

  471. <dl class="py attribute">
    472. 

  472. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.Dice.confmat">
    473. 

  473. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.Dice.confmat" title="Permalink to this definition"></a></dt>
    474. 

  474. <dd></dd></dl>
    475. 

  475. 

  476. <dl class="py attribute">
    477. 

  477. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.Dice.training">
    478. 

  478. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.Dice.training" title="Permalink to this definition"></a></dt>
    479. 

  479. <dd></dd></dl>
    480. 

  480. 

  481. </dd></dl>
    482. 

  482. 

  483. <dl class="py class">
    484. 

  484. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryIOU">
    485. 

  485. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">BinaryIOU</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryIOU"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryIOU" title="Permalink to this definition"></a></dt>
    486. 

  486. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.IoU" title="super_gradients.training.metrics.segmentation_metrics.IoU"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.IoU</span></code></a></p>
    487. 

  487. <dl class="py method">
    488. 

  488. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryIOU.compute">
    489. 

  489. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryIOU.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryIOU.compute" title="Permalink to this definition"></a></dt>
    490. 

  490. <dd><p>Computes intersection over union (IoU)</p>
    491. 

  491. </dd></dl>
    492. 

  492. 

  493. <dl class="py attribute">
    494. 

  494. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryIOU.confmat">
    495. 

  495. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryIOU.confmat" title="Permalink to this definition"></a></dt>
    496. 

  496. <dd></dd></dl>
    497. 

  497. 

  498. <dl class="py attribute">
    499. 

  499. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryIOU.training">
    500. 

  500. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryIOU.training" title="Permalink to this definition"></a></dt>
    501. 

  501. <dd></dd></dl>
    502. 

  502. 

  503. </dd></dl>
    504. 

  504. 

  505. <dl class="py class">
    506. 

  506. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryDice">
    507. 

  507. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.segmentation_metrics.</span></span><span class="sig-name descname"><span class="pre">BinaryDice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryDice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryDice" title="Permalink to this definition"></a></dt>
    508. 

  508. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.Dice" title="super_gradients.training.metrics.segmentation_metrics.Dice"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.Dice</span></code></a></p>
    509. 

  509. <dl class="py method">
    510. 

  510. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryDice.compute">
    511. 

  511. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryDice.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryDice.compute" title="Permalink to this definition"></a></dt>
    512. 

  512. <dd><p>Computes Dice coefficient</p>
    513. 

  513. </dd></dl>
    514. 

  514. 

  515. <dl class="py attribute">
    516. 

  516. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryDice.confmat">
    517. 

  517. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryDice.confmat" title="Permalink to this definition"></a></dt>
    518. 

  518. <dd></dd></dl>
    519. 

  519. 

  520. <dl class="py attribute">
    521. 

  521. <dt class="sig sig-object py" id="super_gradients.training.metrics.segmentation_metrics.BinaryDice.training">
    522. 

  522. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.segmentation_metrics.BinaryDice.training" title="Permalink to this definition"></a></dt>
    523. 

  523. <dd></dd></dl>
    524. 

  524. 

  525. </dd></dl>
    526. 

  526. 

  527. </section>
    528. 

  528. <section id="module-super_gradients.training.metrics">
    529. 

  529. <span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-super_gradients.training.metrics" title="Permalink to this headline"></a></h2>
    530. 

  530. <dl class="py function">
    531. 

  531. <dt class="sig sig-object py" id="super_gradients.training.metrics.accuracy">
    532. 

  532. <span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">output</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topk</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(1)</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.accuracy" title="Permalink to this definition"></a></dt>
    533. 

  533. <dd><p>Computes the precision&#64;k for the specified values of k
    534. 

  534. :param output: Tensor / Numpy / List</p>
    535. 

  535. <blockquote>
    536. 

  536. <div><p>The prediction</p>
    537. 

  537. </div></blockquote>
    538. 

  538. <dl class="field-list simple">
    539. 

  539. <dt class="field-odd">Parameters</dt>
    540. 

  540. <dd class="field-odd"><ul class="simple">
    541. 

  541. <li><p><strong>target</strong> – Tensor / Numpy / List
    542. 

  542. The corresponding lables</p></li>
    543. 

  543. <li><p><strong>topk</strong> – tuple
    544. 

  544. The type of accuracy to calculate, e.g. topk=(1,5) returns accuracy for top-1 and top-5</p></li>
    545. 

  545. </ul>
    546. 

  546. </dd>
    547. 

  547. </dl>
    548. 

  548. </dd></dl>
    549. 

  549. 

  550. <dl class="py class">
    551. 

  551. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy">
    552. 

  552. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">Accuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Accuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Accuracy" title="Permalink to this definition"></a></dt>
    553. 

  553. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.accuracy.Accuracy</span></code></p>
    554. 

  554. <dl class="py method">
    555. 

  555. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy.update">
    556. 

  556. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Accuracy.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Accuracy.update" title="Permalink to this definition"></a></dt>
    557. 

  557. <dd><p>Update state with predictions and targets. See
    558. 

  558. <span class="xref std std-ref">pages/classification:input types</span> for more information on input
    559. 

  559. types.</p>
    560. 

  560. <dl class="field-list simple">
    561. 

  561. <dt class="field-odd">Parameters</dt>
    562. 

  562. <dd class="field-odd"><ul class="simple">
    563. 

  563. <li><p><strong>preds</strong> – Predictions from model (logits, probabilities, or labels)</p></li>
    564. 

  564. <li><p><strong>target</strong> – Ground truth labels</p></li>
    565. 

  565. </ul>
    566. 

  566. </dd>
    567. 

  567. </dl>
    568. 

  568. </dd></dl>
    569. 

  569. 

  570. <dl class="py attribute">
    571. 

  571. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy.correct">
    572. 

  572. <span class="sig-name descname"><span class="pre">correct</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.Accuracy.correct" title="Permalink to this definition"></a></dt>
    573. 

  573. <dd></dd></dl>
    574. 

  574. 

  575. <dl class="py attribute">
    576. 

  576. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy.total">
    577. 

  577. <span class="sig-name descname"><span class="pre">total</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.Accuracy.total" title="Permalink to this definition"></a></dt>
    578. 

  578. <dd></dd></dl>
    579. 

  579. 

  580. <dl class="py attribute">
    581. 

  581. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy.mode">
    582. 

  582. <span class="sig-name descname"><span class="pre">mode</span></span><em class="property"><span class="pre">:</span> <span class="pre">DataType</span></em><a class="headerlink" href="#super_gradients.training.metrics.Accuracy.mode" title="Permalink to this definition"></a></dt>
    583. 

  583. <dd></dd></dl>
    584. 

  584. 

  585. <dl class="py attribute">
    586. 

  586. <dt class="sig sig-object py" id="super_gradients.training.metrics.Accuracy.training">
    587. 

  587. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.Accuracy.training" title="Permalink to this definition"></a></dt>
    588. 

  588. <dd></dd></dl>
    589. 

  589. 

  590. </dd></dl>
    591. 

  591. 

  592. <dl class="py class">
    593. 

  593. <dt class="sig sig-object py" id="super_gradients.training.metrics.Top5">
    594. 

  594. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">Top5</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Top5" title="Permalink to this definition"></a></dt>
    595. 

  595. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    596. 

  596. <dl class="py method">
    597. 

  597. <dt class="sig sig-object py" id="super_gradients.training.metrics.Top5.update">
    598. 

  598. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Top5.update" title="Permalink to this definition"></a></dt>
    599. 

  599. <dd><p>Override this method to update the state variables of your metric class.</p>
    600. 

  600. </dd></dl>
    601. 

  601. 

  602. <dl class="py method">
    603. 

  603. <dt class="sig sig-object py" id="super_gradients.training.metrics.Top5.compute">
    604. 

  604. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#Top5.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Top5.compute" title="Permalink to this definition"></a></dt>
    605. 

  605. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    606. 

  606. distributed backend.</p>
    607. 

  607. </dd></dl>
    608. 

  608. 

  609. </dd></dl>
    610. 

  610. 

  611. <dl class="py class">
    612. 

  612. <dt class="sig sig-object py" id="super_gradients.training.metrics.ToyTestClassificationMetric">
    613. 

  613. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">ToyTestClassificationMetric</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.ToyTestClassificationMetric" title="Permalink to this definition"></a></dt>
    614. 

  614. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    615. 

  615. <p>Dummy classification Mettric object returning 0 always (for testing).</p>
    616. 

  616. <dl class="py method">
    617. 

  617. <dt class="sig sig-object py" id="super_gradients.training.metrics.ToyTestClassificationMetric.update">
    618. 

  618. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span> &#x2192; <span class="pre">None</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.ToyTestClassificationMetric.update" title="Permalink to this definition"></a></dt>
    619. 

  619. <dd><p>Override this method to update the state variables of your metric class.</p>
    620. 

  620. </dd></dl>
    621. 

  621. 

  622. <dl class="py method">
    623. 

  623. <dt class="sig sig-object py" id="super_gradients.training.metrics.ToyTestClassificationMetric.compute">
    624. 

  624. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/classification_metrics.html#ToyTestClassificationMetric.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.ToyTestClassificationMetric.compute" title="Permalink to this definition"></a></dt>
    625. 

  625. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    626. 

  626. distributed backend.</p>
    627. 

  627. </dd></dl>
    628. 

  628. 

  629. </dd></dl>
    630. 

  630. 

  631. <dl class="py class">
    632. 

  632. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics">
    633. 

  633. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">DetectionMetrics</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">num_cls:</span> <span class="pre">int</span></em>, <em class="sig-param"><span class="pre">post_prediction_callback:</span> <span class="pre">Optional[super_gradients.training.utils.detection_utils.DetectionPostPredictionCallback]</span> <span class="pre">=</span> <span class="pre">None</span></em>, <em class="sig-param"><span class="pre">normalize_targets:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></em>, <em class="sig-param"><span class="pre">iou_thres:</span> <span class="pre">super_gradients.training.utils.detection_utils.IouThreshold</span> <span class="pre">=</span> <span class="pre">&lt;IouThreshold.MAP_05_TO_095:</span> <span class="pre">(0.5</span></em>, <em class="sig-param"><span class="pre">0.95)&gt;</span></em>, <em class="sig-param"><span class="pre">recall_thres:</span> <span class="pre">Optional[torch.Tensor]</span> <span class="pre">=</span> <span class="pre">None</span></em>, <em class="sig-param"><span class="pre">score_thres:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">0.1</span></em>, <em class="sig-param"><span class="pre">top_k_predictions:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">100</span></em>, <em class="sig-param"><span class="pre">dist_sync_on_step:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></em>, <em class="sig-param"><span class="pre">accumulate_on_cpu:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics" title="Permalink to this definition"></a></dt>
    634. 

  634. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    635. 

  635. <p>Metric class for computing F1, Precision, Recall and Mean Average Precision.</p>
    636. 

  636. <dl class="py attribute">
    637. 

  637. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.num_cls">
    638. 

  638. <span class="sig-name descname"><span class="pre">num_cls</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.num_cls" title="Permalink to this definition"></a></dt>
    639. 

  639. <dd><p>Number of classes.</p>
    640. 

  640. </dd></dl>
    641. 

  641. 

  642. <dl class="py attribute">
    643. 

  643. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.post_prediction_callback">
    644. 

  644. <span class="sig-name descname"><span class="pre">post_prediction_callback</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.post_prediction_callback" title="Permalink to this definition"></a></dt>
    645. 

  645. <dd><p>DetectionPostPredictionCallback to be applied on net’s output prior
    646. 

  646. to the metric computation (NMS).</p>
    647. 

  647. </dd></dl>
    648. 

  648. 

  649. <dl class="py attribute">
    650. 

  650. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.normalize_targets">
    651. 

  651. <span class="sig-name descname"><span class="pre">normalize_targets</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.normalize_targets" title="Permalink to this definition"></a></dt>
    652. 

  652. <dd><p>Whether to normalize bbox coordinates by image size (default=False).</p>
    653. 

  653. </dd></dl>
    654. 

  654. 

  655. <dl class="py attribute">
    656. 

  656. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.iou_thresholds">
    657. 

  657. <span class="sig-name descname"><span class="pre">iou_thresholds</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.iou_thresholds" title="Permalink to this definition"></a></dt>
    658. 

  658. <dd><p>IoU threshold to compute the mAP (default=torch.linspace(0.5, 0.95, 10)).</p>
    659. 

  659. </dd></dl>
    660. 

  660. 

  661. <dl class="py attribute">
    662. 

  662. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.recall_thresholds">
    663. 

  663. <span class="sig-name descname"><span class="pre">recall_thresholds</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.recall_thresholds" title="Permalink to this definition"></a></dt>
    664. 

  664. <dd><p>Recall threshold to compute the mAP (default=torch.linspace(0, 1, 101)).</p>
    665. 

  665. </dd></dl>
    666. 

  666. 

  667. <dl class="py attribute">
    668. 

  668. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.score_threshold">
    669. 

  669. <span class="sig-name descname"><span class="pre">score_threshold</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.score_threshold" title="Permalink to this definition"></a></dt>
    670. 

  670. <dd><p>Score threshold to compute Recall, Precision and F1 (default=0.1)</p>
    671. 

  671. </dd></dl>
    672. 

  672. 

  673. <dl class="py attribute">
    674. 

  674. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.top_k_predictions">
    675. 

  675. <span class="sig-name descname"><span class="pre">top_k_predictions</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.top_k_predictions" title="Permalink to this definition"></a></dt>
    676. 

  676. <dd><p>Number of predictions per class used to compute metrics, ordered by confidence score
    677. 

  677. (default=100)</p>
    678. 

  678. </dd></dl>
    679. 

  679. 

  680. <dl class="py attribute">
    681. 

  681. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.dist_sync_on_step">
    682. 

  682. <span class="sig-name descname"><span class="pre">dist_sync_on_step</span></span><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.dist_sync_on_step" title="Permalink to this definition"></a></dt>
    683. 

  683. <dd><p>Synchronize metric state across processes at each <code class="docutils literal notranslate"><span class="pre">forward()</span></code>
    684. 

  684. before returning the value at the step. (default=False)</p>
    685. 

  685. <blockquote>
    686. 

  686. <div><dl class="simple">
    687. 

  687. <dt>accumulate_on_cpu:     Run on CPU regardless of device used in other parts.</dt><dd><p>This is to avoid “CUDA out of memory” that might happen on GPU (default False)</p>
    688. 

  688. </dd>
    689. 

  689. </dl>
    690. 

  690. </div></blockquote>
    691. 

  691. </dd></dl>
    692. 

  692. 

  693. <dl class="py method">
    694. 

  694. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.update">
    695. 

  695. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</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">inputs</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch._VariableFunctionsClass.tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">crowd_targets</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">torch.Tensor</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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.update" title="Permalink to this definition"></a></dt>
    696. 

  696. <dd><p>Apply NMS and match all the predictions and targets of a given batch, and update the metric state accordingly.</p>
    697. 

  697. <dl class="simple">
    698. 

  698. <dt>:param preds<span class="classifier">Raw output of the model, the format might change from one model to another, but has to fit</span></dt><dd><p>the input format of the post_prediction_callback</p>
    699. 

  699. </dd>
    700. 

  700. </dl>
    701. 

  701. <dl class="field-list simple">
    702. 

  702. <dt class="field-odd">Parameters</dt>
    703. 

  703. <dd class="field-odd"><ul class="simple">
    704. 

  704. <li><p><strong>target</strong> – Targets for all images of shape (total_num_targets, 6)
    705. 

  705. format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]</p></li>
    706. 

  706. <li><p><strong>device</strong> – Device to run on</p></li>
    707. 

  707. <li><p><strong>inputs</strong> – Input image tensor of shape (batch_size, n_img, height, width)</p></li>
    708. 

  708. <li><p><strong>crowd_targets</strong> – Crowd targets for all images of shape (total_num_targets, 6)
    709. 

  709. format:  (index, x, y, w, h, label) where x,y,w,h are in range [0,1]</p></li>
    710. 

  710. </ul>
    711. 

  711. </dd>
    712. 

  712. </dl>
    713. 

  713. </dd></dl>
    714. 

  714. 

  715. <dl class="py method">
    716. 

  716. <dt class="sig sig-object py" id="super_gradients.training.metrics.DetectionMetrics.compute">
    717. 

  717. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span> </span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span> </span><span class="pre">torch.Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><a class="reference internal" href="_modules/super_gradients/training/metrics/detection_metrics.html#DetectionMetrics.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.DetectionMetrics.compute" title="Permalink to this definition"></a></dt>
    718. 

  718. <dd><p>Compute the metrics for all the accumulated results.
    719. 

  719. :return: Metrics of interest</p>
    720. 

  720. </dd></dl>
    721. 

  721. 

  722. </dd></dl>
    723. 

  723. 

  724. <dl class="py class">
    725. 

  725. <dt class="sig sig-object py" id="super_gradients.training.metrics.PreprocessSegmentationMetricsArgs">
    726. 

  726. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">PreprocessSegmentationMetricsArgs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">apply_arg_max</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">apply_sigmoid</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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PreprocessSegmentationMetricsArgs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.PreprocessSegmentationMetricsArgs" title="Permalink to this definition"></a></dt>
    727. 

  727. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></code></a></p>
    728. 

  728. <p>Default segmentation inputs preprocess function before updating segmentation metrics, handles multiple inputs and
    729. 

  729. apply normalizations.</p>
    730. 

  730. </dd></dl>
    731. 

  731. 

  732. <dl class="py class">
    733. 

  733. <dt class="sig sig-object py" id="super_gradients.training.metrics.PixelAccuracy">
    734. 

  734. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">PixelAccuracy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ignore_label</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-</span> <span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.PixelAccuracy" title="Permalink to this definition"></a></dt>
    735. 

  735. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.metric.Metric</span></code></p>
    736. 

  736. <dl class="py method">
    737. 

  737. <dt class="sig sig-object py" id="super_gradients.training.metrics.PixelAccuracy.update">
    738. 

  738. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.PixelAccuracy.update" title="Permalink to this definition"></a></dt>
    739. 

  739. <dd><p>Override this method to update the state variables of your metric class.</p>
    740. 

  740. </dd></dl>
    741. 

  741. 

  742. <dl class="py method">
    743. 

  743. <dt class="sig sig-object py" id="super_gradients.training.metrics.PixelAccuracy.compute">
    744. 

  744. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#PixelAccuracy.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.PixelAccuracy.compute" title="Permalink to this definition"></a></dt>
    745. 

  745. <dd><p>Override this method to compute the final metric value from state variables synchronized across the
    746. 

  746. distributed backend.</p>
    747. 

  747. </dd></dl>
    748. 

  748. 

  749. </dd></dl>
    750. 

  750. 

  751. <dl class="py class">
    752. 

  752. <dt class="sig sig-object py" id="super_gradients.training.metrics.IoU">
    753. 

  753. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">IoU</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_classes</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">reduction</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">'elementwise_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#IoU"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.IoU" title="Permalink to this definition"></a></dt>
    754. 

  754. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.jaccard.JaccardIndex</span></code></p>
    755. 

  755. <dl class="py method">
    756. 

  756. <dt class="sig sig-object py" id="super_gradients.training.metrics.IoU.update">
    757. 

  757. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#IoU.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.IoU.update" title="Permalink to this definition"></a></dt>
    758. 

  758. <dd><p>Update state with predictions and targets.</p>
    759. 

  759. <dl class="field-list simple">
    760. 

  760. <dt class="field-odd">Parameters</dt>
    761. 

  761. <dd class="field-odd"><ul class="simple">
    762. 

  762. <li><p><strong>preds</strong> – Predictions from model</p></li>
    763. 

  763. <li><p><strong>target</strong> – Ground truth values</p></li>
    764. 

  764. </ul>
    765. 

  765. </dd>
    766. 

  766. </dl>
    767. 

  767. </dd></dl>
    768. 

  768. 

  769. <dl class="py attribute">
    770. 

  770. <dt class="sig sig-object py" id="super_gradients.training.metrics.IoU.confmat">
    771. 

  771. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.IoU.confmat" title="Permalink to this definition"></a></dt>
    772. 

  772. <dd></dd></dl>
    773. 

  773. 

  774. <dl class="py attribute">
    775. 

  775. <dt class="sig sig-object py" id="super_gradients.training.metrics.IoU.training">
    776. 

  776. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.IoU.training" title="Permalink to this definition"></a></dt>
    777. 

  777. <dd></dd></dl>
    778. 

  778. 

  779. </dd></dl>
    780. 

  780. 

  781. <dl class="py class">
    782. 

  782. <dt class="sig sig-object py" id="super_gradients.training.metrics.Dice">
    783. 

  783. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">Dice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">num_classes</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">reduction</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">'elementwise_mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Dice" title="Permalink to this definition"></a></dt>
    784. 

  784. <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torchmetrics.classification.jaccard.JaccardIndex</span></code></p>
    785. 

  785. <dl class="py method">
    786. 

  786. <dt class="sig sig-object py" id="super_gradients.training.metrics.Dice.update">
    787. 

  787. <span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">preds</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">torch.Tensor</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Dice.update" title="Permalink to this definition"></a></dt>
    788. 

  788. <dd><p>Update state with predictions and targets.</p>
    789. 

  789. <dl class="field-list simple">
    790. 

  790. <dt class="field-odd">Parameters</dt>
    791. 

  791. <dd class="field-odd"><ul class="simple">
    792. 

  792. <li><p><strong>preds</strong> – Predictions from model</p></li>
    793. 

  793. <li><p><strong>target</strong> – Ground truth values</p></li>
    794. 

  794. </ul>
    795. 

  795. </dd>
    796. 

  796. </dl>
    797. 

  797. </dd></dl>
    798. 

  798. 

  799. <dl class="py method">
    800. 

  800. <dt class="sig sig-object py" id="super_gradients.training.metrics.Dice.compute">
    801. 

  801. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> &#x2192; <span class="pre">torch.Tensor</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#Dice.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.Dice.compute" title="Permalink to this definition"></a></dt>
    802. 

  802. <dd><p>Computes Dice coefficient</p>
    803. 

  803. </dd></dl>
    804. 

  804. 

  805. <dl class="py attribute">
    806. 

  806. <dt class="sig sig-object py" id="super_gradients.training.metrics.Dice.confmat">
    807. 

  807. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.Dice.confmat" title="Permalink to this definition"></a></dt>
    808. 

  808. <dd></dd></dl>
    809. 

  809. 

  810. <dl class="py attribute">
    811. 

  811. <dt class="sig sig-object py" id="super_gradients.training.metrics.Dice.training">
    812. 

  812. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.Dice.training" title="Permalink to this definition"></a></dt>
    813. 

  813. <dd></dd></dl>
    814. 

  814. 

  815. </dd></dl>
    816. 

  816. 

  817. <dl class="py class">
    818. 

  818. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryIOU">
    819. 

  819. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">BinaryIOU</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryIOU"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.BinaryIOU" title="Permalink to this definition"></a></dt>
    820. 

  820. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.IoU" title="super_gradients.training.metrics.segmentation_metrics.IoU"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.IoU</span></code></a></p>
    821. 

  821. <dl class="py method">
    822. 

  822. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryIOU.compute">
    823. 

  823. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryIOU.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.BinaryIOU.compute" title="Permalink to this definition"></a></dt>
    824. 

  824. <dd><p>Computes intersection over union (IoU)</p>
    825. 

  825. </dd></dl>
    826. 

  826. 

  827. <dl class="py attribute">
    828. 

  828. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryIOU.confmat">
    829. 

  829. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.BinaryIOU.confmat" title="Permalink to this definition"></a></dt>
    830. 

  830. <dd></dd></dl>
    831. 

  831. 

  832. <dl class="py attribute">
    833. 

  833. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryIOU.training">
    834. 

  834. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.BinaryIOU.training" title="Permalink to this definition"></a></dt>
    835. 

  835. <dd></dd></dl>
    836. 

  836. 

  837. </dd></dl>
    838. 

  838. 

  839. <dl class="py class">
    840. 

  840. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryDice">
    841. 

  841. <em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.metrics.</span></span><span class="sig-name descname"><span class="pre">BinaryDice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dist_sync_on_step</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">ignore_index</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">int</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">threshold</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">float</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">metrics_args_prep_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><a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn" title="super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn"><span class="pre">super_gradients.training.metrics.segmentation_metrics.AbstractMetricsArgsPrepFn</span></a><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><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryDice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.BinaryDice" title="Permalink to this definition"></a></dt>
    842. 

  842. <dd><p>Bases: <a class="reference internal" href="#super_gradients.training.metrics.segmentation_metrics.Dice" title="super_gradients.training.metrics.segmentation_metrics.Dice"><code class="xref py py-class docutils literal notranslate"><span class="pre">super_gradients.training.metrics.segmentation_metrics.Dice</span></code></a></p>
    843. 

  843. <dl class="py method">
    844. 

  844. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryDice.compute">
    845. 

  845. <span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/metrics/segmentation_metrics.html#BinaryDice.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.metrics.BinaryDice.compute" title="Permalink to this definition"></a></dt>
    846. 

  846. <dd><p>Computes Dice coefficient</p>
    847. 

  847. </dd></dl>
    848. 

  848. 

  849. <dl class="py attribute">
    850. 

  850. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryDice.confmat">
    851. 

  851. <span class="sig-name descname"><span class="pre">confmat</span></span><em class="property"><span class="pre">:</span> <span class="pre">torch.Tensor</span></em><a class="headerlink" href="#super_gradients.training.metrics.BinaryDice.confmat" title="Permalink to this definition"></a></dt>
    852. 

  852. <dd></dd></dl>
    853. 

  853. 

  854. <dl class="py attribute">
    855. 

  855. <dt class="sig sig-object py" id="super_gradients.training.metrics.BinaryDice.training">
    856. 

  856. <span class="sig-name descname"><span class="pre">training</span></span><em class="property"><span class="pre">:</span> <span class="pre">bool</span></em><a class="headerlink" href="#super_gradients.training.metrics.BinaryDice.training" title="Permalink to this definition"></a></dt>
    857. 

  857. <dd></dd></dl>
    858. 

  858. 

  859. </dd></dl>
    860. 

  860. 

  861. </section>
    862. 

  862. </section>
    863. 

  863. 

  864. 

  865.            </div>
    866. 

  866.           </div>
    867. 

  867.           <footer>
    868. 

  868. 

  869.   <hr/>
    870. 

  870. 

  871.   <div role="contentinfo">
    872. 

  872.     <p>&#169; Copyright 2021, SuperGradients team.</p>
    873. 

  873.   </div>
    874. 

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  875.   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
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    881. 

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    882. 

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    883. 

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