SipMask-benchmark/fcos_core/modeling/rpn/sipmask/loss.py
def center_size(boxes):
    """ Convert prior_boxes to (cx, cy, w, h)
    representation for comparison to center-size form ground truth data.
    Args:
        boxes: (tensor) point_form boxes
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
    """
    return torch.cat(( (boxes[:, 2:] + boxes[:, :2])/2,     # cx, cy
                        boxes[:, 2:] - boxes[:, :2]  ), 1)
 Convert prior_boxes to (cx, cy, w, h)
    representation for comparison to center-size form ground truth data.
    Args:
        boxes: (tensor) point_form boxes
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
    
Convert prior_boxes to (cx, cy, w, h)
representation for comparison to center-size form ground truth data.
Convert prior_boxes to ( cx cy w h ) representation for comparison to center - size form ground truth data .
def center_size(boxes):
    return torch.cat(( (boxes[:, 2:] + boxes[:, :2])/2,     
                        boxes[:, 2:] - boxes[:, :2]  ), 1)
def center_size ( boxes ) : return torch . cat ( ( ( boxes [ : , 2 : ] + boxes [ : , : 2 ] ) / 2 , boxes [ : , 2 : ] - boxes [ : , : 2 ] ) , 1 )
Convert prior_boxes to (cx, cy, w, h)
representation for comparison to center-size form ground truth data.
Convert prior_boxes to ( cx cy w h ) representation for comparison to center - size form ground truth data .
""" Convert prior_boxes to (cx, cy, w, h)
    representation for comparison to center-size form ground truth data.
    Args:
        boxes: (tensor) point_form boxes
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
    """ # cx, cy
boxes
(tensor) point_form boxes
( tensor ) point_form boxes