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In this video tutorial, Ivan discusses data collection and labelling for training a custom YOLOv5 model. The key points covered include determining if object detection is right for the problem, collecting training images, using labelling tools, and storing the dataset in the cloud with Weights Biases. This is part 2 of the YOLOv5 series, with previous parts covering YOLOv5 integration and real-time object detection. Feel free to ask any questions in the comments.
