Learn how to build and run your very own Object Tracker in Google Colab! This tutorial walks you through the process of building an object tracking application using DeepSORT and YOLOv4 Object Detection in the Cloud on Google Colab’s FREE GPU! Get it up and running with only a few clicks of a button. This tutorial covers it all.

YOLOv4 is a state of the art algorithm that uses deep convolutional neural networks to perform object detections. We can take the output of YOLOv4 feed these object detections into Deep SORT (Simple Online and Realtime Tracking with a Deep Association Metric) in order to create a highly accurate object tracker.

In this video I cover:

  1. Setting up the Colab Notebook and Enabling GPU
  2. Cloning the code and installing dependencies.
  3. Converting YOLOv4 pre-trained model into TensorFlow model.
  4. Running Object Tracker on video.
  5. Filtering allowed classes to track.
  6. Adding info flag to see detailed information on tracked objects.

THE GOOGLE COLAB NOTEBOOK: https://bit.ly/3cJ6m1z

GET THE CODE HERE:https://github.com/theAIGuysCode/yolov4-deepsort

SUBSCRIBE : https://www.youtube.com/channel/UCrydcKaojc44XnuXrfhlV8Q

#yolo #object #yolov4 #tensorflow

YOLOv4 in the CLOUD: Build Object Tracking Using DeepSORT in Google Colab (FREE GPU)
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