Comments (4)
boxes_t[:, 0::2] = boxes_t[:, 0::2] * (self.img_dim / width) / self.img_dim, so the self.img_dim is reduced.
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@biubug6
A little of-topic.. Can you described the meaning behind "min_sizes" and "steps" in config please? What would be the reason for modifying them?
from pytorch_retinaface.
"min_sizes" is anchor size on different scales, "steps" is downsampling rate of feature map. I don't modify them?
from pytorch_retinaface.
@hegc Sorry. maybe I'm missing something but both boxes and landmarks are normalized with width and height of the image before resizing, why?
Since height and width change after resizing shouldn't they be normalized with width and height after resizing?
from pytorch_retinaface.
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from pytorch_retinaface.