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In this video tutorial, Ivan discusses data collection and labeling for training a custom YOLOv5 model. The process includes determining if object detection is suitable for the problem, collecting training images, using labeling tools, and utilizing Weights Biases for dataset storage in the cloud. This is Part 2 of the series; Part 0 covers YOLOv5 and Weights Biases integration, and Part 1 focuses on real-time object detection on Windows and Google Colab. If you have any questions, feel free to ask in the comments section. Determine if object detection is the right approach for your problem to begin.