Hello, I am developing a pipeline consisting in a detection model as pgie and classification model as sgie. As I understand it, it should work as follows (please correct me if I am wrong):
The detection model makes a bbox prediction, the object is cropped where the bbox is, and the cropout is fed as input to the classification model.
I have two questions:
- My classification model takes images of size 256x144. I want to keep aspect ratio for the cropped bboxes, so I need padding. I read on a post that padding is only at the bottom and the right. Is this correct? Or can the padding be on any border of the image?
- I am training the classification model with TLT. There is an option to choose the image size and resize_interpolation_method. I don’t see a flag to pad. Do I need to add padding to the images manually before training? (i.e. make my input images 256x144 with padding so that no resizing happens in training)
Thanks for your help