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When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations.

If random rotations are added, how is the new bounding box calculated?

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    $\begingroup$ I don't have much practical experience with them, but, I guess, if you rotate the images, you just need to rotate the boxes (i.e. labels) too. Check this (which may not be a reliable implementation: I don't know!). $\endgroup$
    – nbro
    Nov 15 '20 at 22:43
  • $\begingroup$ The problem is the predicted boxes are not rotated - so would you just create a new box from the rotated images bounding box corners? This works but might make the predicted box a little larger,. $\endgroup$ Nov 15 '20 at 22:47

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