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Computer vision models rely on the quality of the data provided, with good labels being essential for good performance. This tutorial walks through annotating images for object detection models, improving data quality to create higher-performing models. The speaker outlines seven techniques for creating high-quality data, using a chess piece detection model as an example. The process involves labeling images with bounding boxes to help the model learn and predict the location of chess pieces on a board. Step one is deciding on the goal of the model.
