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<div class="subTitle">org.opencv.dnn</div>
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<h2 title="Class DetectionModel" class="title">Class DetectionModel</h2>
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<li>org.opencv.dnn.DetectionModel</li>
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<pre>public class <span class="typeNameLabel">DetectionModel</span>
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extends <a href="../../../org/opencv/dnn/Model.html" title="class in org.opencv.dnn">Model</a></pre>
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<div class="block">This class represents high-level API for object detection networks.
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DetectionModel allows to set params for preprocessing input image.
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DetectionModel creates net from file with trained weights and config,
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sets preprocessing input, runs forward pass and return result detections.
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For DetectionModel SSD, Faster R-CNN, YOLO topologies are supported.</div>
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<tr class="altColor">
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#DetectionModel-org.opencv.dnn.Net-">DetectionModel</a></span>(<a href="../../../org/opencv/dnn/Net.html" title="class in org.opencv.dnn">Net</a> network)</code>
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<div class="block">Create model from deep learning network.</div>
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</td>
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</tr>
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<tr class="rowColor">
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#DetectionModel-java.lang.String-">DetectionModel</a></span>(java.lang.String model)</code>
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<div class="block">Create detection model from network represented in one of the supported formats.</div>
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</td>
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<tr class="altColor">
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<td class="colOne"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#DetectionModel-java.lang.String-java.lang.String-">DetectionModel</a></span>(java.lang.String model,
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java.lang.String config)</code>
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<div class="block">Create detection model from network represented in one of the supported formats.</div>
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<h3>Method Summary</h3>
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<table class="memberSummary" border="0" cellpadding="3" cellspacing="0" summary="Method Summary table, listing methods, and an explanation">
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<caption><span id="t0" class="activeTableTab"><span>All Methods</span><span class="tabEnd"> </span></span><span id="t1" class="tableTab"><span><a href="javascript:show(1);">Static Methods</a></span><span class="tabEnd"> </span></span><span id="t2" class="tableTab"><span><a href="javascript:show(2);">Instance Methods</a></span><span class="tabEnd"> </span></span><span id="t4" class="tableTab"><span><a href="javascript:show(8);">Concrete Methods</a></span><span class="tabEnd"> </span></span></caption>
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<td class="colFirst"><code>static <a href="../../../org/opencv/dnn/DetectionModel.html" title="class in org.opencv.dnn">DetectionModel</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#Z:Z__fromPtr__-long-">__fromPtr__</a></span>(long addr)</code> </td>
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<tr id="i1" class="rowColor">
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<td class="colFirst"><code>void</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#detect-org.opencv.core.Mat-org.opencv.core.MatOfInt-org.opencv.core.MatOfFloat-org.opencv.core.MatOfRect-">detect</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes)</code>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
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<td class="colFirst"><code>void</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#detect-org.opencv.core.Mat-org.opencv.core.MatOfInt-org.opencv.core.MatOfFloat-org.opencv.core.MatOfRect-float-">detect</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes,
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float confThreshold)</code>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
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<td class="colFirst"><code>void</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#detect-org.opencv.core.Mat-org.opencv.core.MatOfInt-org.opencv.core.MatOfFloat-org.opencv.core.MatOfRect-float-float-">detect</a></span>(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes,
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float confThreshold,
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float nmsThreshold)</code>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
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<td class="colFirst"><code>boolean</code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#getNmsAcrossClasses--">getNmsAcrossClasses</a></span>()</code>
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<div class="block">Getter for nmsAcrossClasses.</div>
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<td class="colFirst"><code><a href="../../../org/opencv/dnn/DetectionModel.html" title="class in org.opencv.dnn">DetectionModel</a></code></td>
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<td class="colLast"><code><span class="memberNameLink"><a href="../../../org/opencv/dnn/DetectionModel.html#setNmsAcrossClasses-boolean-">setNmsAcrossClasses</a></span>(boolean value)</code>
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<div class="block">nmsAcrossClasses defaults to false,
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such that when non max suppression is used during the detect() function, it will do so per-class.</div>
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<h3>Methods inherited from class org.opencv.dnn.<a href="../../../org/opencv/dnn/Model.html" title="class in org.opencv.dnn">Model</a></h3>
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<code><a href="../../../org/opencv/dnn/Model.html#getNativeObjAddr--">getNativeObjAddr</a>, <a href="../../../org/opencv/dnn/Model.html#predict-org.opencv.core.Mat-java.util.List-">predict</a>, <a href="../../../org/opencv/dnn/Model.html#setInputCrop-boolean-">setInputCrop</a>, <a href="../../../org/opencv/dnn/Model.html#setInputMean-org.opencv.core.Scalar-">setInputMean</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams--">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams-double-">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams-double-org.opencv.core.Size-">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams-double-org.opencv.core.Size-org.opencv.core.Scalar-">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams-double-org.opencv.core.Size-org.opencv.core.Scalar-boolean-">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputParams-double-org.opencv.core.Size-org.opencv.core.Scalar-boolean-boolean-">setInputParams</a>, <a href="../../../org/opencv/dnn/Model.html#setInputScale-double-">setInputScale</a>, <a href="../../../org/opencv/dnn/Model.html#setInputSize-int-int-">setInputSize</a>, <a href="../../../org/opencv/dnn/Model.html#setInputSize-org.opencv.core.Size-">setInputSize</a>, <a href="../../../org/opencv/dnn/Model.html#setInputSwapRB-boolean-">setInputSwapRB</a>, <a href="../../../org/opencv/dnn/Model.html#setPreferableBackend-int-">setPreferableBackend</a>, <a href="../../../org/opencv/dnn/Model.html#setPreferableTarget-int-">setPreferableTarget</a></code></li>
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<h3>Methods inherited from class java.lang.Object</h3>
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<code>equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait</code></li>
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<h3>Constructor Detail</h3>
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<a name="DetectionModel-org.opencv.dnn.Net-">
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<pre>public DetectionModel(<a href="../../../org/opencv/dnn/Net.html" title="class in org.opencv.dnn">Net</a> network)</pre>
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<pre>public DetectionModel(java.lang.String model)</pre>
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<div class="block">Create detection model from network represented in one of the supported formats.
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<dd><code>model</code> - Binary file contains trained weights.</dd>
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<pre>public DetectionModel(java.lang.String model,
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java.lang.String config)</pre>
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<dd><code>model</code> - Binary file contains trained weights.</dd>
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<dd><code>config</code> - Text file contains network configuration.</dd>
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<pre>public static <a href="../../../org/opencv/dnn/DetectionModel.html" title="class in org.opencv.dnn">DetectionModel</a> __fromPtr__(long addr)</pre>
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<h4>detect</h4>
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<pre>public void detect(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes)</pre>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>classIds</code> - Class indexes in result detection.</dd>
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<dd><code>confidences</code> - A set of corresponding confidences.</dd>
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<dd><code>boxes</code> - A set of bounding boxes.</dd>
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<dd><code>frame</code> - automatically generated</dd>
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<h4>detect</h4>
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<pre>public void detect(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes,
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float confThreshold)</pre>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>classIds</code> - Class indexes in result detection.</dd>
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<dd><code>confidences</code> - A set of corresponding confidences.</dd>
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<dd><code>boxes</code> - A set of bounding boxes.</dd>
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<dd><code>confThreshold</code> - A threshold used to filter boxes by confidences.</dd>
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<dd><code>frame</code> - automatically generated</dd>
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<h4>detect</h4>
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<pre>public void detect(<a href="../../../org/opencv/core/Mat.html" title="class in org.opencv.core">Mat</a> frame,
|
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<a href="../../../org/opencv/core/MatOfInt.html" title="class in org.opencv.core">MatOfInt</a> classIds,
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<a href="../../../org/opencv/core/MatOfFloat.html" title="class in org.opencv.core">MatOfFloat</a> confidences,
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<a href="../../../org/opencv/core/MatOfRect.html" title="class in org.opencv.core">MatOfRect</a> boxes,
|
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float confThreshold,
|
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float nmsThreshold)</pre>
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<div class="block">Given the <code>input</code> frame, create input blob, run net and return result detections.</div>
|
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<dl>
|
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<dt><span class="paramLabel">Parameters:</span></dt>
|
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<dd><code>classIds</code> - Class indexes in result detection.</dd>
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<dd><code>confidences</code> - A set of corresponding confidences.</dd>
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<dd><code>boxes</code> - A set of bounding boxes.</dd>
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<dd><code>confThreshold</code> - A threshold used to filter boxes by confidences.</dd>
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<dd><code>nmsThreshold</code> - A threshold used in non maximum suppression.</dd>
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<dd><code>frame</code> - automatically generated</dd>
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<h4>getNmsAcrossClasses</h4>
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<pre>public boolean getNmsAcrossClasses()</pre>
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<div class="block">Getter for nmsAcrossClasses. This variable defaults to false,
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such that when non max suppression is used during the detect() function, it will do so only per-class</div>
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<dl>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>automatically generated</dd>
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<h4>setNmsAcrossClasses</h4>
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<pre>public <a href="../../../org/opencv/dnn/DetectionModel.html" title="class in org.opencv.dnn">DetectionModel</a> setNmsAcrossClasses(boolean value)</pre>
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<div class="block">nmsAcrossClasses defaults to false,
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such that when non max suppression is used during the detect() function, it will do so per-class.
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This function allows you to toggle this behaviour.</div>
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<dl>
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<dt><span class="paramLabel">Parameters:</span></dt>
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<dd><code>value</code> - The new value for nmsAcrossClasses</dd>
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<dt><span class="returnLabel">Returns:</span></dt>
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<dd>automatically generated</dd>
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