YOLOv4 custom object detection with TensorFlow 2
To be a state-of-the-art model, YOLOv4 needs to be at the leading-edge of deep learning. YOLOv4 authors have worked on techniques to improve the accuracy of the model while training and in post-processing.
These techniques are called bag-of-freebies and bag-of-specials. In my previous tutorial, we mostly covered the YOLOv4 backbone, the neck and part of bag-of-specials (BoS) for the detector. So, in this part, we will continue bag-of-specials (BoS) and we'll cover bag-of-freebies (BoF).
Text version tutorial: https://pylessons.com/YOLOv4-TF2-trai...
Full video playlist: • Yolo v3 Introduction to object detect...
GitHub code: https://github.com/pythonlessons/Tens...
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