def _scale_meshes()

in meshrcnn/utils/metrics.py [0:0]

• 18 lines of code
• 9 McCabe index (conditional complexity)

def _scale_meshes(pred_meshes, gt_meshes, scale):
    if isinstance(scale, float):
        # Assume scale is a single scalar to use for both preds and GT
        pred_scale = gt_scale = scale
    elif isinstance(scale, tuple):
        # Rescale preds and GT with different scalars
        pred_scale, gt_scale = scale
    elif scale.startswith("gt-"):
        # Rescale both preds and GT so that the largest edge length of each GT
        # mesh is target
        target = float(scale[3:])
        bbox = gt_meshes.get_bounding_boxes()  # (N, 3, 2)
        long_edge = (bbox[:, :, 1] - bbox[:, :, 0]).max(dim=1)[0]  # (N,)
        scale = target / long_edge
        if scale.numel() == 1:
            scale = scale.expand(len(pred_meshes))
        pred_scale, gt_scale = scale, scale
    else:
        raise ValueError("Invalid scale: %r" % scale)
    pred_meshes = pred_meshes.scale_verts(pred_scale)
    gt_meshes = gt_meshes.scale_verts(gt_scale)
    return pred_meshes, gt_meshes