Object Tracking Using YOLOv4, Deep SORT, and TensorFlow
Learn how to Build an Object Tracker using YOLOv4, Deep SORT, and Tensorflow! Run the real-time object tracker on both webcam and video. This video will show you how to get the necessary code, setup required dependencies and run the tracker. It can be run using YOLOv4, YOLOv4-tiny or YOLOv3 object detection models.
#objecttracking #yolov4 #deepsort
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. Run Deep SORT with YOLOv4-tiny model and obtain even higher speed and FPS, perfect for mobile apps or edge devices such as Raspberry Pi or Jetson Nano.
GET THE CODE HERE: https://github.com/theAIGuysCode/yolo...
In this video I cover:
1. Cloning the code and installing dependencies.
2. Converting YOLOv4 pre-trained model into TensorFlow model.
3. Running Object Tracker on video.
4. Filtering allowed classes to track.
5. Running Object Tracker with YOLOv4-tiny for high FPS.
6. Adding info flag to see detailed information on tracks.
------------------------------Resources------------------------------
Learn to Convert to TFLite and TensorRT: • YOLOv4 Object Detection with TensorFl...
Configure to Run with Custom YOLOv4 Detector: • How to Build a Custom YOLOv4 Object D...
Train Custom YOLOv4 Detector in Cloud: • YOLOv4 in the CLOUD: Build and Train ...
The Official YOLOv4 paper: https://arxiv.org/abs/2004.10934
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The AI Guy
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