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This architecture will provide you with eight points in the output, you can join the points accordingly to get the bounding box. In some cases neural network will provide with multiple bounding boxes, in that case you have to perform non maximun suppression.
While training you dont need to provide the bounding box shape. You have to provide with regression targets for each instance of vehicle, like eight corners with centered zero.
Can anyone tell me how the bounding boxes are predcition with the model? and which function does that?
Thank you.
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