Non Normalized coordinates

[vaishnavm217]

Hi, I am working on face detection using your ssd model. One thing I noticed that my model was giving zero loss, i.e all the ious were zero. After long inspection https://github.com/kuangliu/torchcv/blob/6291f3e1e4bbf6467fd6b1e79001d34a59481bb6/examples/ssd/train.py#L63 this line passes the boxes coordinates as it is. It should be normalized to get correct iou

[tfygg]

Yeah, i also noticed that you tested the VOC dataset by the image size of 300*300.

[ljtruong]

@vaishnavm217 to fix this do we just do something like this? to normalise the bounding boxes.

        w,h = image.size
        boxes /= torch.Tensor([w,h,w,h]).expand_as(boxes)

[vaishnavm217]

That's more appropriate. But assuming a square image as input, you can just divide it by any one of the dimension.

On Sun, 15 Jul 2018, 10:22 Leon, [email protected] wrote:

@vaishnavm217 https://github.com/vaishnavm217 to fix this do we just do something like this? to normalise the bounding boxes.

    w,h = image.size
    boxes /= torch.Tensor([w,h,w,h]).expand_as(boxes)

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[ljtruong]

@vaishnavm217 thank you for the confirmation. much appreciated. I'm testing out the train now and it's working well.

Just looking ahead. When I run it through prediction or evaluation, where would the best place to denormalise the labels?.