(boxes)
return torch.cat((boxes[:, :2] - boxes[:, 2:] / 2,  # xmin, ymin
                      boxes[:, :2] + boxes[:, 2:] / 2), 1)
Convert prior_boxes to (xmin, ymin, xmax, ymax)
    representation for comparison to point form ground truth data.
    Args:
        boxes: (tensor) center-size default boxes from priorbox layers.
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
Convert prior_boxes to (xmin, ymin, xmax, ymax)
    representation for comparison to point form ground truth data.
    Args:
        boxes: (tensor) center-size default boxes from priorbox layers.
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
Convert prior_boxes to ( xmin ymin xmax ymax ) representation for comparison to point form ground truth data . Args : boxes : ( tensor ) center - size default boxes from priorbox layers . Return : boxes : ( tensor ) Converted xmin ymin xmax ymax form of boxes .
def point_form(boxes):
    """ Convert prior_boxes to (xmin, ymin, xmax, ymax)
    representation for comparison to point form ground truth data.
    Args:
        boxes: (tensor) center-size default boxes from priorbox layers.
    Return:
        boxes: (tensor) Converted xmin, ymin, xmax, ymax form of boxes.
    """
    return torch.cat((boxes[:, :2] - boxes[:, 2:] / 2,  # xmin, ymin
                      boxes[:, :2] + boxes[:, 2:] / 2), 1)
def point_form ( boxes ) : return torch . cat ( ( boxes [ : , : 2 ] - boxes [ : , 2 : ] / 2 , # xmin, ymin boxes [ : , : 2 ] + boxes [ : , 2 : ] / 2 ) , 1 )