Python: Real-time Multiple Object Tracking (MOT) with Yolov3, Tensorflow and Deep SORT [FULL COURSE]

YouTube Excerpt: TABLE OF CONTENT Introduction 00:01:38 Part 1 - How to setup a local GPU environment 00:02:45 - Full list of Python Packages 00:05:38 Part 2 - How to convert YOLO to Tensorflow 00:07:27 Part 3 - How to detect, recognize and track multiple objects 00:10:54 Part 4 - Programming exercise - Multiple Object Tracking 00:21:02 - Multiple Object Tracking with historical trajectory 01:07:03 - Multiple Object Tracking - Counter (Gate) 01:15:55 - Multiple Object Tracking - Counter (Zone) 01:25:17 USEFUL LINKS Full explanation of custom object training in Python https://www.youtube.com/watch?v=DLngCtsG3bk Github https://github.com/emasterclassacademy/Single-Multiple-Custom-Object-Detection-and-Tracking Yolov3 weights https://pjreddie.com/media/files/yolov3.weights Yolov3-tiny weights https://pjreddie.com/media/files/yolov3-tiny.weights --------------------------------------------------------------------------------------------------------------------------- Support FREE content: https://www.buymeacoffee.com/eMasterClass REFERENCE https://github.com/yehengchen/Object-Detection-and-Tracking/tree/master/OneStage/yolo https://github.com/AlexeyAB/darknet https://github.com/theAIGuysCode/yolov3_deepsort#command-line-args-reference https://github.com/anguoyang/keras-yolo3-1 https://www.intechopen.com/books/intelligent-system-and-computing/vehicle-tracking-using-video-surveillance http://www.isy.liu.se/edu/projekt/bildbehandling/2018/detection/Technical_report.pdf

TABLE OF CONTENT Introduction 00:01:38 Part 1 - How to setup a local GPU environment 00:02:45 - Full list of Python Packages...

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