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Image annotation refers to adding a label or marker to each object in an image to provide more information about the content of the image. By labeling each object in an image, the image can be transformed into a data set that a machine can understand, allowing for deeper analysis and research using computer vision techniques. Image annotation  can help machine learning models better understand images and thus more accurately identify objects in images. How to label images? Image annotation methods specifically include semantic segmentation, rectangular frame annotation, polygon annotation, key point annotation, point cloud annotation, 3D cube annotation, 2D/3D fusion annotation, target tracking, attribute discrimination, etc. 1. Semantic Segmentation Semantic segmentation refers to dividing complex and irregular images into regions based on the attributes of objects, and marking the corresponding attributes to help train image recognition models. It is often used in a...