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In this video tutorial, Ivan covers data collection and labelling for training a custom YOLOv5 model. The process includes assessing if object detection is suitable for the problem, collecting training images, using labelling tools, and storing the dataset on Weights & Biases. This is Part 2 of the YOLOv5 series, with previous parts discussing integration with Weights & Biases and real-time object detection. Feel free to ask questions in the comments section. Making the right decision about object detection is crucial to the entire process.
