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Computer vision models rely on the quality of the data provided, with good labels being essential for creating high-performing models. The tutorial demonstrates how to annotate images for object detection models, improving model accuracy by ensuring high-quality data. The process involves labeling images with bounding boxes to train the model to recognize and predict chess pieces on a chess board. Seven techniques are presented to help achieve the highest quality data for improved model performance.
