►FREE YOLO GIFT – http://augmentedstartups.info/yolofreegiftsp
►YOLOv3 Course – http://augmentedstartups.info/YoloV3_Course
►Github Repo – http://augmentedstartups.info/github-yolo-access
In this lecture we are going to get into the most fun part of this entire series which is to train our neural network. We will be using Supervisely to deploy our dataset and model to our deep learning cluster that we created in the previous lecture, to train our YoloV3 model.
What’s really nice about Supervisely is that you can try out other types of network like SSD and Faster-RCNN without having to re-label or alter your dataset in any way! If you are not aware, certain CNN architectures require that your annotations be in a certain format, either, .xml, .txt or. json.
Okay so let’s start with the training of our YoloV3 detector
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