Bounding box annotation is a fundamental technique that involves placing rectangular boxes around objects in images to help AI learn object detection. This simple but precise process supports applications like self-driving cars and robotics by providing accurate data for computer vision models.
Question:
What challenges do you think annotators might face when drawing bounding boxes around objects, and why is accuracy so important in this task?