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<!DOCTYPE html>
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<title>Tracker — Multi-object trackers in Python 1.0.0 documentation</title>
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<a href="../index.html" class="icon icon-home"> Multi-object trackers in Python
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<ul class="current">
<li class="toctree-l1"><a class="reference internal" href="readmefile.html">Multi-object trackers in Python</a></li>
<li class="toctree-l1"><a class="reference internal" href="readmefile.html#example-tf-mobilenetssd-centroidtracker">Example: <cite>TF-MobileNetSSD + CentroidTracker</cite></a></li>
<li class="toctree-l1"><a class="reference internal" href="readmefile.html#example-yolov3-centroidtracker">Example: <cite>YOLOv3 + CentroidTracker</cite></a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">Tracker</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.tracker.Tracker"><code class="docutils literal notranslate"><span class="pre">Tracker</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.tracker.Tracker.preprocess_input"><code class="docutils literal notranslate"><span class="pre">Tracker.preprocess_input()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.tracker.Tracker.update"><code class="docutils literal notranslate"><span class="pre">Tracker.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#sort">SORT</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.sort_tracker.assign_tracks2detection_iou"><code class="docutils literal notranslate"><span class="pre">assign_tracks2detection_iou()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.sort_tracker.SORT"><code class="docutils literal notranslate"><span class="pre">SORT</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.sort_tracker.SORT.update"><code class="docutils literal notranslate"><span class="pre">SORT.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#iou-tracker">IOU Tracker</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.iou_tracker.IOUTracker"><code class="docutils literal notranslate"><span class="pre">IOUTracker</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.iou_tracker.IOUTracker.update"><code class="docutils literal notranslate"><span class="pre">IOUTracker.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#kalman-filter-based-centroid-tracker">Kalman Filter based Centroid Tracker</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.centroid_kf_tracker.assign_tracks2detection_centroid_distances"><code class="docutils literal notranslate"><span class="pre">assign_tracks2detection_centroid_distances()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.centroid_kf_tracker.CentroidKF_Tracker"><code class="docutils literal notranslate"><span class="pre">CentroidKF_Tracker</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.centroid_kf_tracker.CentroidKF_Tracker.update"><code class="docutils literal notranslate"><span class="pre">CentroidKF_Tracker.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#tracks">Tracks</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.track.Track"><code class="docutils literal notranslate"><span class="pre">Track</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.Track.centroid"><code class="docutils literal notranslate"><span class="pre">Track.centroid</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.Track.get_mot_challenge_format"><code class="docutils literal notranslate"><span class="pre">Track.get_mot_challenge_format()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.Track.get_vis_drone_format"><code class="docutils literal notranslate"><span class="pre">Track.get_vis_drone_format()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.Track.predict"><code class="docutils literal notranslate"><span class="pre">Track.predict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.Track.update"><code class="docutils literal notranslate"><span class="pre">Track.update()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.track.KFTrackSORT"><code class="docutils literal notranslate"><span class="pre">KFTrackSORT</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrackSORT.predict"><code class="docutils literal notranslate"><span class="pre">KFTrackSORT.predict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrackSORT.update"><code class="docutils literal notranslate"><span class="pre">KFTrackSORT.update()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.track.KFTrack4DSORT"><code class="docutils literal notranslate"><span class="pre">KFTrack4DSORT</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrack4DSORT.predict"><code class="docutils literal notranslate"><span class="pre">KFTrack4DSORT.predict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrack4DSORT.update"><code class="docutils literal notranslate"><span class="pre">KFTrack4DSORT.update()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.track.KFTrackCentroid"><code class="docutils literal notranslate"><span class="pre">KFTrackCentroid</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrackCentroid.predict"><code class="docutils literal notranslate"><span class="pre">KFTrackCentroid.predict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.track.KFTrackCentroid.update"><code class="docutils literal notranslate"><span class="pre">KFTrackCentroid.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#kalman-filters">Kalman Filters</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KalmanFilter"><code class="docutils literal notranslate"><span class="pre">KalmanFilter</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.kalman_tracker.KalmanFilter.predict"><code class="docutils literal notranslate"><span class="pre">KalmanFilter.predict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.kalman_tracker.KalmanFilter.update"><code class="docutils literal notranslate"><span class="pre">KalmanFilter.update()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KFTrackerConstantAcceleration"><code class="docutils literal notranslate"><span class="pre">KFTrackerConstantAcceleration</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KFTracker1D"><code class="docutils literal notranslate"><span class="pre">KFTracker1D</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KFTracker2D"><code class="docutils literal notranslate"><span class="pre">KFTracker2D</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KFTracker4D"><code class="docutils literal notranslate"><span class="pre">KFTracker4D</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.kalman_tracker.KFTrackerSORT"><code class="docutils literal notranslate"><span class="pre">KFTrackerSORT</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#object-detection">Object Detection</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.detectors.detector.Detector"><code class="docutils literal notranslate"><span class="pre">Detector</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.detector.Detector.detect"><code class="docutils literal notranslate"><span class="pre">Detector.detect()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.detector.Detector.draw_bboxes"><code class="docutils literal notranslate"><span class="pre">Detector.draw_bboxes()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.detector.Detector.forward"><code class="docutils literal notranslate"><span class="pre">Detector.forward()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.detectors.caffe.Caffe_SSDMobileNet"><code class="docutils literal notranslate"><span class="pre">Caffe_SSDMobileNet</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.caffe.Caffe_SSDMobileNet.forward"><code class="docutils literal notranslate"><span class="pre">Caffe_SSDMobileNet.forward()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.detectors.tf.TF_SSDMobileNetV2"><code class="docutils literal notranslate"><span class="pre">TF_SSDMobileNetV2</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.tf.TF_SSDMobileNetV2.forward"><code class="docutils literal notranslate"><span class="pre">TF_SSDMobileNetV2.forward()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.detectors.yolo.YOLOv3"><code class="docutils literal notranslate"><span class="pre">YOLOv3</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.yolo.YOLOv3.detect"><code class="docutils literal notranslate"><span class="pre">YOLOv3.detect()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="#motrackers.detectors.yolo.YOLOv3.forward"><code class="docutils literal notranslate"><span class="pre">YOLOv3.forward()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#utilities">Utilities</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.get_centroid"><code class="docutils literal notranslate"><span class="pre">get_centroid()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.iou"><code class="docutils literal notranslate"><span class="pre">iou()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.iou_xywh"><code class="docutils literal notranslate"><span class="pre">iou_xywh()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.xyxy2xywh"><code class="docutils literal notranslate"><span class="pre">xyxy2xywh()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.xywh2xyxy"><code class="docutils literal notranslate"><span class="pre">xywh2xyxy()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.midwh2xywh"><code class="docutils literal notranslate"><span class="pre">midwh2xywh()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.intersection_complement_indices"><code class="docutils literal notranslate"><span class="pre">intersection_complement_indices()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.nms"><code class="docutils literal notranslate"><span class="pre">nms()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.draw_tracks"><code class="docutils literal notranslate"><span class="pre">draw_tracks()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.load_labelsjson"><code class="docutils literal notranslate"><span class="pre">load_labelsjson()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.misc.dict2jsonfile"><code class="docutils literal notranslate"><span class="pre">dict2jsonfile()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.create_filechooser"><code class="docutils literal notranslate"><span class="pre">create_filechooser()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_caffemodel_prototxt"><code class="docutils literal notranslate"><span class="pre">select_caffemodel_prototxt()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_caffemodel_weights"><code class="docutils literal notranslate"><span class="pre">select_caffemodel_weights()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_caffemodel"><code class="docutils literal notranslate"><span class="pre">select_caffemodel()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_videofile"><code class="docutils literal notranslate"><span class="pre">select_videofile()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_yolo_weights"><code class="docutils literal notranslate"><span class="pre">select_yolo_weights()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_coco_labels"><code class="docutils literal notranslate"><span class="pre">select_coco_labels()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_yolo_config"><code class="docutils literal notranslate"><span class="pre">select_yolo_config()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_yolo_model"><code class="docutils literal notranslate"><span class="pre">select_yolo_model()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_pbtxt"><code class="docutils literal notranslate"><span class="pre">select_pbtxt()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_tfmobilenet_weights"><code class="docutils literal notranslate"><span class="pre">select_tfmobilenet_weights()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#motrackers.utils.filechooser_utils.select_tfmobilenet"><code class="docutils literal notranslate"><span class="pre">select_tfmobilenet()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="#download-pretrained-neural-network-weights">Download pretrained neural-network weights.</a><ul>
<li class="toctree-l3"><a class="reference internal" href="#yolov3">YOLOv3</a></li>
<li class="toctree-l3"><a class="reference internal" href="#tensorflow-mobilenetssdv2">TensorFlow - MobileNetSSDv2</a></li>
<li class="toctree-l3"><a class="reference internal" href="#caffemodel-mobilenetssd">Caffemodel - MobileNetSSD</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="#references-and-credits">References and Credits</a></li>
<li class="toctree-l1"><a class="reference internal" href="#contributor-covenant-code-of-conduct">Contributor Covenant Code of Conduct</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#our-pledge">Our Pledge</a></li>
<li class="toctree-l2"><a class="reference internal" href="#our-standards">Our Standards</a></li>
<li class="toctree-l2"><a class="reference internal" href="#our-responsibilities">Our Responsibilities</a></li>
<li class="toctree-l2"><a class="reference internal" href="#scope">Scope</a></li>
<li class="toctree-l2"><a class="reference internal" href="#enforcement">Enforcement</a></li>
<li class="toctree-l2"><a class="reference internal" href="#attribution">Attribution</a></li>
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<a href="../index.html">Multi-object trackers in Python</a>
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<section id="tracker">
<h1>Tracker<a class="headerlink" href="#tracker" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.tracker.Tracker">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.tracker.</span></span><span class="sig-name descname"><span class="pre">Tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/tracker.html#Tracker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.tracker.Tracker" title="Permalink to this definition"></a></dt>
<dd><p>Greedy Tracker with tracking based on <code class="docutils literal notranslate"><span class="pre">centroid</span></code> location of the bounding box of the object.
This tracker is also referred as <code class="docutils literal notranslate"><span class="pre">CentroidTracker</span></code> in this repository.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>max_lost</strong> (<em>int</em>) – Maximum number of consecutive frames object was not detected.</p></li>
<li><p><strong>tracker_output_format</strong> (<em>str</em>) – Output format of the tracker.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.tracker.Tracker.preprocess_input">
<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">preprocess_input</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_scores</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/tracker.html#Tracker.preprocess_input"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.tracker.Tracker.preprocess_input" title="Permalink to this definition"></a></dt>
<dd><p>Preprocess the input data.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bboxes</strong> (<em>list</em><em> or </em><em>numpy.ndarray</em>) – Array of bounding boxes with each bbox as a tuple containing <cite>(xmin, ymin, width, height)</cite>.</p></li>
<li><p><strong>class_ids</strong> (<em>list</em><em> or </em><em>numpy.ndarray</em>) – Array of Class ID or label ID.</p></li>
<li><p><strong>detection_scores</strong> (<em>list</em><em> or </em><em>numpy.ndarray</em>) – Array of detection scores (a.k.a. detection probabilities).</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>Data for detections as list of tuples containing <cite>(bbox, class_id, detection_score)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>detections (list[Tuple])</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.tracker.Tracker.update">
<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">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_scores</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/tracker.html#Tracker.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.tracker.Tracker.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the tracker based on the new bounding boxes.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bboxes</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of bounding boxes detected in the current frame. Each element of the list represent
coordinates of bounding box as tuple <cite>(top-left-x, top-left-y, width, height)</cite>.</p></li>
<li><p><strong>detection_scores</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of detection scores (probability) of each detected object.</p></li>
<li><p><strong>class_ids</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of class_ids (int) corresponding to labels of the detected object. Default is <cite>None</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>List of tracks being currently tracked by the tracker. Each track is represented by the tuple with elements <cite>(frame_id, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>list</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="sort">
<h1>SORT<a class="headerlink" href="#sort" title="Permalink to this heading"></a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="motrackers.sort_tracker.assign_tracks2detection_iou">
<span class="sig-prename descclassname"><span class="pre">motrackers.sort_tracker.</span></span><span class="sig-name descname"><span class="pre">assign_tracks2detection_iou</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bbox_tracks</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox_detections</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/sort_tracker.html#assign_tracks2detection_iou"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.sort_tracker.assign_tracks2detection_iou" title="Permalink to this definition"></a></dt>
<dd><p>Assigns detected bounding boxes to tracked bounding boxes using IoU as a distance metric.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bbox_tracks</strong> (<em>numpy.ndarray</em>) – Bounding boxes of shape <cite>(N, 4)</cite> where <cite>N</cite> is number of objects already being tracked.</p></li>
<li><p><strong>bbox_detections</strong> (<em>numpy.ndarray</em>) – Bounding boxes of shape <cite>(M, 4)</cite> where <cite>M</cite> is number of objects that are newly detected.</p></li>
<li><p><strong>iou_threshold</strong> (<em>float</em>) – IOU threashold.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><dl class="simple">
<dt>Tuple contains the following elements in the given order:</dt><dd><ul class="simple">
<li><p>matches (numpy.ndarray): Array of shape <cite>(n, 2)</cite> where <cite>n</cite> is number of pairs formed after matching tracks to detections. This is an array of tuples with each element as matched pair of indices`(track_index, detection_index)`.</p></li>
<li><p>unmatched_detections (numpy.ndarray): Array of shape <cite>(m,)</cite> where <cite>m</cite> is number of unmatched detections.</p></li>
<li><p>unmatched_tracks (numpy.ndarray): Array of shape <cite>(k,)</cite> where <cite>k</cite> is the number of unmatched tracks.</p></li>
</ul>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.sort_tracker.SORT">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.sort_tracker.</span></span><span class="sig-name descname"><span class="pre">SORT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</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/motrackers/sort_tracker.html#SORT"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.sort_tracker.SORT" title="Permalink to this definition"></a></dt>
<dd><p>SORT - Multi object tracker.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>max_lost</strong> (<em>int</em>) – Max. number of times a object is lost while tracking.</p></li>
<li><p><strong>tracker_output_format</strong> (<em>str</em>) – Output format of the tracker.</p></li>
<li><p><strong>iou_threshold</strong> (<em>float</em>) – Intersection over union minimum value.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em><em> or </em><em>numpy.ndarray</em>) – Process noise covariance matrix of shape (3, 3)
or covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em><em> or </em><em>numpy.ndarray</em>) – Measurement noise covariance matrix of shape (1,)
or covariance magnitude as scalar value.</p></li>
<li><p><strong>time_step</strong> (<em>int</em><em> or </em><em>float</em>) – Time step for Kalman Filter.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.sort_tracker.SORT.update">
<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">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_scores</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/sort_tracker.html#SORT.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.sort_tracker.SORT.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the tracker based on the new bounding boxes.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bboxes</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of bounding boxes detected in the current frame. Each element of the list represent
coordinates of bounding box as tuple <cite>(top-left-x, top-left-y, width, height)</cite>.</p></li>
<li><p><strong>detection_scores</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of detection scores (probability) of each detected object.</p></li>
<li><p><strong>class_ids</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of class_ids (int) corresponding to labels of the detected object. Default is <cite>None</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>List of tracks being currently tracked by the tracker. Each track is represented by the tuple with elements <cite>(frame_id, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>list</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="iou-tracker">
<h1>IOU Tracker<a class="headerlink" href="#iou-tracker" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.iou_tracker.IOUTracker">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.iou_tracker.</span></span><span class="sig-name descname"><span class="pre">IOUTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_threshold</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">min_detection_confidence</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_detection_confidence</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/iou_tracker.html#IOUTracker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.iou_tracker.IOUTracker" title="Permalink to this definition"></a></dt>
<dd><p>Intersection over Union Tracker.</p>
<p class="rubric">References</p>
<ul class="simple">
<li><p>Implementation of this algorithm is heavily based on <a class="reference external" href="https://github.com/bochinski/iou-tracker">https://github.com/bochinski/iou-tracker</a></p></li>
</ul>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>max_lost</strong> (<em>int</em>) – Maximum number of consecutive frames object was not detected.</p></li>
<li><p><strong>tracker_output_format</strong> (<em>str</em>) – Output format of the tracker.</p></li>
<li><p><strong>min_detection_confidence</strong> (<em>float</em>) – Threshold for minimum detection confidence.</p></li>
<li><p><strong>max_detection_confidence</strong> (<em>float</em>) – Threshold for max. detection confidence.</p></li>
<li><p><strong>iou_threshold</strong> (<em>float</em>) – Intersection over union minimum value.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.iou_tracker.IOUTracker.update">
<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">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_scores</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/iou_tracker.html#IOUTracker.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.iou_tracker.IOUTracker.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the tracker based on the new bounding boxes.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bboxes</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of bounding boxes detected in the current frame. Each element of the list represent
coordinates of bounding box as tuple <cite>(top-left-x, top-left-y, width, height)</cite>.</p></li>
<li><p><strong>detection_scores</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of detection scores (probability) of each detected object.</p></li>
<li><p><strong>class_ids</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of class_ids (int) corresponding to labels of the detected object. Default is <cite>None</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>List of tracks being currently tracked by the tracker. Each track is represented by the tuple with elements <cite>(frame_id, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>list</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="kalman-filter-based-centroid-tracker">
<h1>Kalman Filter based Centroid Tracker<a class="headerlink" href="#kalman-filter-based-centroid-tracker" title="Permalink to this heading"></a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="motrackers.centroid_kf_tracker.assign_tracks2detection_centroid_distances">
<span class="sig-prename descclassname"><span class="pre">motrackers.centroid_kf_tracker.</span></span><span class="sig-name descname"><span class="pre">assign_tracks2detection_centroid_distances</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bbox_tracks</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox_detections</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">distance_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10.0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/centroid_kf_tracker.html#assign_tracks2detection_centroid_distances"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.centroid_kf_tracker.assign_tracks2detection_centroid_distances" title="Permalink to this definition"></a></dt>
<dd><p>Assigns detected bounding boxes to tracked bounding boxes using IoU as a distance metric.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bbox_tracks</strong> (<em>numpy.ndarray</em>) – Tracked bounding boxes with shape <cite>(n, 4)</cite>
and each row as <cite>(xmin, ymin, width, height)</cite>.</p></li>
<li><p><strong>bbox_detections</strong> (<em>numpy.ndarray</em>) – detection bounding boxes with shape <cite>(m, 4)</cite> and
each row as <cite>(xmin, ymin, width, height)</cite>.</p></li>
<li><p><strong>distance_threshold</strong> (<em>float</em>) – Minimum distance between the tracked object
and new detection to consider for assignment.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><dl class="simple">
<dt>Tuple containing the following elements:</dt><dd><ul class="simple">
<li><p>matches (numpy.ndarray): Array of shape <cite>(n, 2)</cite> where <cite>n</cite> is number of pairs formed after matching tracks to detections. This is an array of tuples with each element as matched pair of indices`(track_index, detection_index)`.</p></li>
<li><p>unmatched_detections (numpy.ndarray): Array of shape <cite>(m,)</cite> where <cite>m</cite> is number of unmatched detections.</p></li>
<li><p>unmatched_tracks (numpy.ndarray): Array of shape <cite>(k,)</cite> where <cite>k</cite> is the number of unmatched tracks.</p></li>
</ul>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.centroid_kf_tracker.CentroidKF_Tracker">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.centroid_kf_tracker.</span></span><span class="sig-name descname"><span class="pre">CentroidKF_Tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroid_distance_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">30.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</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/motrackers/centroid_kf_tracker.html#CentroidKF_Tracker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.centroid_kf_tracker.CentroidKF_Tracker" title="Permalink to this definition"></a></dt>
<dd><p>Kalman filter based tracking of multiple detected objects.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>max_lost</strong> (<em>int</em>) – Maximum number of consecutive frames object was not detected.</p></li>
<li><p><strong>tracker_output_format</strong> (<em>str</em>) – Output format of the tracker.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em><em> or </em><em>numpy.ndarray</em>) – Process noise covariance matrix of shape (3, 3) or
covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em><em> or </em><em>numpy.ndarray</em>) – Measurement noise covariance matrix of shape (1,)
or covariance magnitude as scalar value.</p></li>
<li><p><strong>time_step</strong> (<em>int</em><em> or </em><em>float</em>) – Time step for Kalman Filter.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.centroid_kf_tracker.CentroidKF_Tracker.update">
<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">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_scores</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/centroid_kf_tracker.html#CentroidKF_Tracker.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.centroid_kf_tracker.CentroidKF_Tracker.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the tracker based on the new bounding boxes.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bboxes</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of bounding boxes detected in the current frame. Each element of the list represent
coordinates of bounding box as tuple <cite>(top-left-x, top-left-y, width, height)</cite>.</p></li>
<li><p><strong>detection_scores</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of detection scores (probability) of each detected object.</p></li>
<li><p><strong>class_ids</strong> (<em>numpy.ndarray</em><em> or </em><em>list</em>) – List of class_ids (int) corresponding to labels of the detected object. Default is <cite>None</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>List of tracks being currently tracked by the tracker. Each track is represented by the tuple with elements <cite>(frame_id, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>list</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="tracks">
<h1>Tracks<a class="headerlink" href="#tracks" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.track.Track">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.track.</span></span><span class="sig-name descname"><span class="pre">Track</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#Track"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.Track" title="Permalink to this definition"></a></dt>
<dd><p>Track containing attributes to track various objects.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>track_id</strong> (<em>int</em>) – Track Id</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>str</em><em> or </em><em>int</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>data_output_format</strong> (<em>str</em>) – Output format for data in tracker.
Options include <code class="docutils literal notranslate"><span class="pre">['mot_challenge',</span> <span class="pre">'visdrone_challenge']</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">mot_challenge</span></code>.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
<dl class="py property">
<dt class="sig sig-object py" id="motrackers.track.Track.centroid">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">centroid</span></span><a class="headerlink" href="#motrackers.track.Track.centroid" title="Permalink to this definition"></a></dt>
<dd><p>Return the centroid of the bounding box.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Centroid (x, y) of bounding box.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.Track.get_mot_challenge_format">
<span class="sig-name descname"><span class="pre">get_mot_challenge_format</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#Track.get_mot_challenge_format"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.Track.get_mot_challenge_format" title="Permalink to this definition"></a></dt>
<dd><p>Get the tracker data in MOT challenge format as a tuple of elements containing
<cite>(frame, id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite></p>
<p class="rubric">References</p>
<ul class="simple">
<li><p>Website : <a class="reference external" href="https://motchallenge.net/">https://motchallenge.net/</a></p></li>
</ul>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Tuple of 10 elements representing <cite>(frame, id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z)</cite>.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.Track.get_vis_drone_format">
<span class="sig-name descname"><span class="pre">get_vis_drone_format</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#Track.get_vis_drone_format"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.Track.get_vis_drone_format" title="Permalink to this definition"></a></dt>
<dd><p>Track data output in VISDRONE Challenge format with tuple as
<cite>(frame_index, target_id, bbox_left, bbox_top, bbox_width, bbox_height, score, object_category,
truncation, occlusion)</cite>.</p>
<p class="rubric">References</p>
<ul class="simple">
<li><p>Website : <a class="reference external" href="http://aiskyeye.com/">http://aiskyeye.com/</a></p></li>
<li><p>Paper : <a class="reference external" href="https://arxiv.org/abs/2001.06303">https://arxiv.org/abs/2001.06303</a></p></li>
<li><p>GitHub : <a class="reference external" href="https://github.com/VisDrone/VisDrone2018-MOT-toolkit">https://github.com/VisDrone/VisDrone2018-MOT-toolkit</a></p></li>
<li><p>GitHub : <a class="reference external" href="https://github.com/VisDrone/">https://github.com/VisDrone/</a></p></li>
</ul>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Tuple containing the elements as <cite>(frame_index, target_id, bbox_left, bbox_top, bbox_width, bbox_height,
score, object_category, truncation, occlusion)</cite>.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.Track.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#Track.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.Track.predict" title="Permalink to this definition"></a></dt>
<dd><p>Implement to prediction the next estimate of track.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.Track.update">
<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">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#Track.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.Track.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>int</em><em> or </em><em>str</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.track.KFTrackSORT">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.track.</span></span><span class="sig-name descname"><span class="pre">KFTrackSORT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackSORT"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackSORT" title="Permalink to this definition"></a></dt>
<dd><p>Track based on Kalman filter tracker used for SORT MOT-Algorithm.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>track_id</strong> (<em>int</em>) – Track Id</p></li>
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>str</em><em> or </em><em>int</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>data_output_format</strong> (<em>str</em>) – Output format for data in tracker.
Options <code class="docutils literal notranslate"><span class="pre">['mot_challenge',</span> <span class="pre">'visdrone_challenge']</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">mot_challenge</span></code>.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em>) – Process noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em>) – Measurement noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrackSORT.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackSORT.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackSORT.predict" title="Permalink to this definition"></a></dt>
<dd><p>Predicts the next estimate of the bounding box of the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrackSORT.update">
<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">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackSORT.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackSORT.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>int</em><em> or </em><em>str</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.track.KFTrack4DSORT">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.track.</span></span><span class="sig-name descname"><span class="pre">KFTrack4DSORT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kf_time_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrack4DSORT"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrack4DSORT" title="Permalink to this definition"></a></dt>
<dd><p>Track based on Kalman filter tracker used for SORT MOT-Algorithm.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>track_id</strong> (<em>int</em>) – Track Id</p></li>
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>str</em><em> or </em><em>int</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>data_output_format</strong> (<em>str</em>) – Output format for data in tracker.
Options <code class="docutils literal notranslate"><span class="pre">['mot_challenge',</span> <span class="pre">'visdrone_challenge']</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">mot_challenge</span></code>.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em>) – Process noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em>) – Measurement noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrack4DSORT.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrack4DSORT.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrack4DSORT.predict" title="Permalink to this definition"></a></dt>
<dd><p>Implement to prediction the next estimate of track.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrack4DSORT.update">
<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">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrack4DSORT.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrack4DSORT.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>int</em><em> or </em><em>str</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.track.KFTrackCentroid">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.track.</span></span><span class="sig-name descname"><span class="pre">KFTrackCentroid</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data_output_format</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mot_challenge'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackCentroid"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackCentroid" title="Permalink to this definition"></a></dt>
<dd><p>Track based on Kalman filter used for Centroid Tracking of bounding box in MOT.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>track_id</strong> (<em>int</em>) – Track Id</p></li>
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>str</em><em> or </em><em>int</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>data_output_format</strong> (<em>str</em>) – Output format for data in tracker.
Options <code class="docutils literal notranslate"><span class="pre">['mot_challenge',</span> <span class="pre">'visdrone_challenge']</span></code>. Default is <code class="docutils literal notranslate"><span class="pre">mot_challenge</span></code>.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em>) – Process noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em>) – Measurement noise covariance scale or covariance magnitude as scalar value.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrackCentroid.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackCentroid.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackCentroid.predict" title="Permalink to this definition"></a></dt>
<dd><p>Predicts the next estimate of the bounding box of the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p>
</dd>
<dt class="field-even">Return type</dt>
<dd class="field-even"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.track.KFTrackCentroid.update">
<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">frame_id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">detection_confidence</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_id</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">lost</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/track.html#KFTrackCentroid.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.track.KFTrackCentroid.update" title="Permalink to this definition"></a></dt>
<dd><p>Update the track.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>frame_id</strong> (<em>int</em>) – Camera frame id.</p></li>
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box pixel coordinates as (xmin, ymin, width, height) of the track.</p></li>
<li><p><strong>detection_confidence</strong> (<em>float</em>) – Detection confidence of the object (probability).</p></li>
<li><p><strong>class_id</strong> (<em>int</em><em> or </em><em>str</em>) – Class label id.</p></li>
<li><p><strong>lost</strong> (<em>int</em>) – Number of times the object or track was not tracked by tracker in consecutive frames.</p></li>
<li><p><strong>iou_score</strong> (<em>float</em>) – Intersection over union score.</p></li>
<li><p><strong>kwargs</strong> (<em>dict</em>) – Additional key word arguments.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="kalman-filters">
<h1>Kalman Filters<a class="headerlink" href="#kalman-filters" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KalmanFilter">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KalmanFilter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transition_matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">control_matrix</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">process_noise_covariance</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">measurement_noise_covariance</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">prediction_covariance</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">initial_state</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/motrackers/kalman_tracker.html#KalmanFilter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KalmanFilter" title="Permalink to this definition"></a></dt>
<dd><p>Kalman Filter Implementation.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>transition_matrix</strong> (<em>numpy.ndarray</em>) – Transition matrix of shape <code class="docutils literal notranslate"><span class="pre">(n,</span> <span class="pre">n)</span></code>.</p></li>
<li><p><strong>measurement_matrix</strong> (<em>numpy.ndarray</em>) – Measurement matrix of shape <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n)</span></code>.</p></li>
<li><p><strong>control_matrix</strong> (<em>numpy.ndarray</em>) – Control matrix of shape <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n)</span></code>.</p></li>
<li><p><strong>process_noise_covariance</strong> (<em>numpy.ndarray</em>) – Covariance matrix of shape <code class="docutils literal notranslate"><span class="pre">(n,</span> <span class="pre">n)</span></code>.</p></li>
<li><p><strong>measurement_noise_covariance</strong> (<em>numpy.ndarray</em>) – Covariance matrix of shape <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">m)</span></code>.</p></li>
<li><p><strong>prediction_covariance</strong> (<em>numpy.ndarray</em>) – Predicted (a priori) estimate covariance of shape <code class="docutils literal notranslate"><span class="pre">(n,</span> <span class="pre">n)</span></code>.</p></li>
<li><p><strong>initial_state</strong> (<em>numpy.ndarray</em>) – Initial state of shape <code class="docutils literal notranslate"><span class="pre">(n,)</span></code>.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KalmanFilter.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">u</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KalmanFilter.predict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KalmanFilter.predict" title="Permalink to this definition"></a></dt>
<dd><p>Prediction step of Kalman Filter.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>u</strong> (<em>float</em><em> or </em><em>int</em><em> or </em><em>numpy.ndarray</em>) – Control input. Default is <cite>0</cite>.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>State vector of shape <cite>(n,)</cite>.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KalmanFilter.update">
<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">z</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KalmanFilter.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KalmanFilter.update" title="Permalink to this definition"></a></dt>
<dd><p>Measurement update of Kalman Filter.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>z</strong> (<em>numpy.ndarray</em>) – Measurement vector of the system with shape <code class="docutils literal notranslate"><span class="pre">(m,)</span></code>.</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KFTrackerConstantAcceleration">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KFTrackerConstantAcceleration</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_measurement</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KFTrackerConstantAcceleration"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KFTrackerConstantAcceleration" title="Permalink to this definition"></a></dt>
<dd><p>Kalman Filter with constant acceleration kinematic model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>initial_measurement</strong> (<em>numpy.ndarray</em>) – Initial state of the tracker.</p></li>
<li><p><strong>time_step</strong> (<em>float</em>) – Time step.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em>) – Process noise covariance scale.
or covariance magnitude as scalar value.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em>) – Measurement noise covariance scale.
or covariance magnitude as scalar value.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KFTracker1D">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KFTracker1D</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_measurement</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">array([0.0])</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KFTracker1D"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KFTracker1D" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KFTracker2D">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KFTracker2D</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_measurement</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">array([0.0,</span> <span class="pre">0.0])</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KFTracker2D"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KFTracker2D" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KFTracker4D">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KFTracker4D</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">initial_measurement</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">array([0.0,</span> <span class="pre">0.0,</span> <span class="pre">0.0,</span> <span class="pre">0.0])</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/kalman_tracker.html#KFTracker4D"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KFTracker4D" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.kalman_tracker.KFTrackerSORT">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.kalman_tracker.</span></span><span class="sig-name descname"><span class="pre">KFTrackerSORT</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bbox</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">process_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">measurement_noise_scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">time_step</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/motrackers/kalman_tracker.html#KFTrackerSORT"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.kalman_tracker.KFTrackerSORT" title="Permalink to this definition"></a></dt>
<dd><p>Kalman filter for <code class="docutils literal notranslate"><span class="pre">SORT</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bbox</strong> (<em>numpy.ndarray</em>) – Bounding box coordinates as <code class="docutils literal notranslate"><span class="pre">(xmid,</span> <span class="pre">ymid,</span> <span class="pre">area,</span> <span class="pre">aspect_ratio)</span></code>.</p></li>
<li><p><strong>time_step</strong> (<em>float</em><em> or </em><em>int</em>) – Time step.</p></li>
<li><p><strong>process_noise_scale</strong> (<em>float</em>) – Scale (a.k.a covariance) of the process noise.</p></li>
<li><p><strong>measurement_noise_scale</strong> (<em>float</em>) – Scale (a.k.a. covariance) of the measurement noise.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</section>
<section id="object-detection">
<h1>Object Detection<a class="headerlink" href="#object-detection" title="Permalink to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.detectors.detector.Detector">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.detectors.detector.</span></span><span class="sig-name descname"><span class="pre">Detector</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">object_names</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confidence_threshold</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nms_threshold</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">draw_bboxes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/detector.html#Detector"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.detector.Detector" title="Permalink to this definition"></a></dt>
<dd><p>Abstract class for detector.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>object_names</strong> (<em>dict</em>) – Dictionary containing (key, value) as (class_id, class_name) for object detector.</p></li>
<li><p><strong>confidence_threshold</strong> (<em>float</em>) – Confidence threshold for object detection.</p></li>
<li><p><strong>nms_threshold</strong> (<em>float</em>) – Threshold for non-maximal suppression.</p></li>
<li><p><strong>draw_bboxes</strong> (<em>bool</em>) – If true, draw bounding boxes on the image is possible.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.detectors.detector.Detector.detect">
<span class="sig-name descname"><span class="pre">detect</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/detector.html#Detector.detect"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.detector.Detector.detect" title="Permalink to this definition"></a></dt>
<dd><p>Detect objects in the input image.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> (<em>numpy.ndarray</em>) – Input image.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p><dl class="simple">
<dt>Tuple containing the following elements:</dt><dd><ul class="simple">
<li><p>bboxes (numpy.ndarray): Bounding boxes with shape (n, 4) containing detected objects with each row as <cite>(xmin, ymin, width, height)</cite>.</p></li>
<li><p>confidences (numpy.ndarray): Confidence or detection probabilities if the detected objects with shape (n,).</p></li>
<li><p>class_ids (numpy.ndarray): Class_ids or label_ids of detected objects with shape (n, 4)</p></li>
</ul>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.detectors.detector.Detector.draw_bboxes">
<span class="sig-name descname"><span class="pre">draw_bboxes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bboxes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confidences</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">class_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/detector.html#Detector.draw_bboxes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.detector.Detector.draw_bboxes" title="Permalink to this definition"></a></dt>
<dd><p>Draw the bounding boxes about detected objects in the image.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>image</strong> (<em>numpy.ndarray</em>) – Image or video frame.</p></li>
<li><p><strong>bboxes</strong> (<em>numpy.ndarray</em>) – Bounding boxes pixel coordinates as (xmin, ymin, width, height)</p></li>
<li><p><strong>confidences</strong> (<em>numpy.ndarray</em>) – Detection confidence or detection probability.</p></li>
<li><p><strong>class_ids</strong> (<em>numpy.ndarray</em>) – Array containing class ids (aka label ids) of each detected object.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>image with the bounding boxes drawn on it.</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.detectors.detector.Detector.forward">
<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/detector.html#Detector.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.detector.Detector.forward" title="Permalink to this definition"></a></dt>
<dd><p>Forward pass for the detector with input image.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> (<em>numpy.ndarray</em>) – Input image.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>detections</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.detectors.caffe.Caffe_SSDMobileNet">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.detectors.caffe.</span></span><span class="sig-name descname"><span class="pre">Caffe_SSDMobileNet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">configfile_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confidence_threshold</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">nms_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">draw_bboxes</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">use_gpu</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/motrackers/detectors/caffe.html#Caffe_SSDMobileNet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.caffe.Caffe_SSDMobileNet" title="Permalink to this definition"></a></dt>
<dd><p>Caffe SSD MobileNet model for Object Detection.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>weights_path</strong> (<em>str</em>) – path to network weights file.</p></li>
<li><p><strong>configfile_path</strong> (<em>str</em>) – path to network configuration file.</p></li>
<li><p><strong>labels_path</strong> (<em>str</em>) – path to data labels json file.</p></li>
<li><p><strong>confidence_threshold</strong> (<em>float</em>) – confidence threshold to select the detected object.</p></li>
<li><p><strong>nms_threshold</strong> (<em>float</em>) – Non-maximum suppression threshold.</p></li>
<li><p><strong>draw_bboxes</strong> (<em>bool</em>) – If True, assign colors for drawing bounding boxes on the image.</p></li>
<li><p><strong>use_gpu</strong> (<em>bool</em>) – If True, try to load the model on GPU.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.detectors.caffe.Caffe_SSDMobileNet.forward">
<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/caffe.html#Caffe_SSDMobileNet.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.caffe.Caffe_SSDMobileNet.forward" title="Permalink to this definition"></a></dt>
<dd><p>Forward pass for the detector with input image.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> (<em>numpy.ndarray</em>) – Input image.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>detections</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.detectors.tf.TF_SSDMobileNetV2">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.detectors.tf.</span></span><span class="sig-name descname"><span class="pre">TF_SSDMobileNetV2</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">configfile_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confidence_threshold</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">nms_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">draw_bboxes</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">use_gpu</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/motrackers/detectors/tf.html#TF_SSDMobileNetV2"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.tf.TF_SSDMobileNetV2" title="Permalink to this definition"></a></dt>
<dd><p>Tensorflow SSD MobileNetv2 model for Object Detection.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>weights_path</strong> (<em>str</em>) – path to network weights file.</p></li>
<li><p><strong>configfile_path</strong> (<em>str</em>) – path to network configuration file.</p></li>
<li><p><strong>labels_path</strong> (<em>str</em>) – path to data labels json file.</p></li>
<li><p><strong>confidence_threshold</strong> (<em>float</em>) – confidence threshold to select the detected object.</p></li>
<li><p><strong>nms_threshold</strong> (<em>float</em>) – Non-maximum suppression threshold.</p></li>
<li><p><strong>draw_bboxes</strong> (<em>bool</em>) – If True, assign colors for drawing bounding boxes on the image.</p></li>
<li><p><strong>use_gpu</strong> (<em>bool</em>) – If True, try to load the model on GPU.</p></li>
</ul>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="motrackers.detectors.tf.TF_SSDMobileNetV2.forward">
<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/motrackers/detectors/tf.html#TF_SSDMobileNetV2.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.tf.TF_SSDMobileNetV2.forward" title="Permalink to this definition"></a></dt>
<dd><p>Forward pass for the detector with input image.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>image</strong> (<em>numpy.ndarray</em>) – Input image.</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>detections</p>
</dd>
<dt class="field-odd">Return type</dt>
<dd class="field-odd"><p>numpy.ndarray</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="motrackers.detectors.yolo.YOLOv3">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">motrackers.detectors.yolo.</span></span><span class="sig-name descname"><span class="pre">YOLOv3</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">weights_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">configfile_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confidence_threshold</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">nms_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">draw_bboxes</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">use_gpu</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/motrackers/detectors/yolo.html#YOLOv3"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#motrackers.detectors.yolo.YOLOv3" title="Permalink to this definition"></a></dt>
<dd><p>YOLOv3 Object Detector Module.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>weights_path</strong> (<em>str</em>) – path to network weights file.</p></li>
<li><p><strong>configfile_path</strong> (<em>str</em>) – path to network configuration file.</p></li>
<li><p><strong>labels_path</strong> (<em>str</em>) – path to data labels json file.</p></li>
<li><p><strong>confidence_threshold</strong> (<em>float</em>) – confidence threshold to select the detected object.</p></li>
<li><p><strong>nms_threshold</strong> (<em>float</em>) – Non-maximum suppression threshold.</p></li>
<li><p><strong>draw_bboxes</strong> (<em>bool</em>) – If True, assign colors for drawing bounding boxes on the image.</p></li>
<li><p><strong>use_gpu</strong> (<em>bool</em>) – If True, try to load the model on GPU.</p></li>
</ul>
</dd>