Is there a problem in the coordinates normalization before computing IoU ? about yolo_v1_pytorch HOT 2 OPEN

I totally agree with @E-delweiss observation.
I am not sure to understand why we have to divide by S=7 again.
I did compute the iou with these rescaling methods and I had good results, but I still do not understand why we rescale in that way specifically.

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@E-delweiss @valentin-fngr
After reading the code, I think the implementation is already correct.
Since in voc.py, the xy_normalized is normalized by dividing it by cell_size, with cell_size = 1/S. 1 here is the normalized width or height of the image size.

xy_normalized = (xy - x0y0) / cell_size # x & y of the box on the cell, normalized from 0.0 to 1.0.
xy_normalized = (xy - x0y0) * S

So, in order to de-normalize the center_x and center_y to normalized image scale, we need to multiply back with cell_size, which is 1/S.

xy = xy_normalized * cell_size 
xy = xy_normalized / S

Cmiiw.

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