(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.
    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 . Args : boxes : ( tensor ) point_form boxes Return : boxes : ( tensor ) Converted xmin ymin xmax ymax form of boxes .
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)
def center_size ( boxes ) : return torch . cat ( ( boxes [ : , 2 : ] + boxes [ : , : 2 ] ) / 2 , # cx, cy boxes [ : , 2 : ] - boxes [ : , : 2 ] , 1 )