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In object detection, they usually resize by keeping the ratio the same as the original image, which usually names "letterbox" resize.

My question is:

  1. Why do we need to do that? As I see with some images too long in vertical or horizontal, we will lose a lot of features in those images.

  2. If it is better than normal resize, why people don't apply it in the classification task?

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