pose_human36M_32_to_pose_human36M_32

menpo.landmark.pose_human36M_32_to_pose_human36M_32(x, return_mapping=False)[source]

Apply the human3.6M 32-point semantic labels.

The semantic labels applied are as follows:

  • pelvis
  • right_leg
  • left_leg
  • spine
  • head
  • left_arm
  • left_hand
  • right_arm
  • right_hand
  • torso

References

[1]http://vision.imar.ro/human3.6m/
Parameters:
  • x (LandmarkGroup or PointCloud or ndarray) – The input landmark group, pointcloud or array to label. If a pointcloud is passed, then only the connectivity information is propagated to the pointcloud (a subclass of PointCloud may be returned).
  • return_mapping (bool, optional) – Only applicable if a PointCloud or ndarray is passed. Returns the mapping dictionary which maps labels to indices into the resulting PointCloud (which is then used to for building a LandmarkGroup. This parameter is only provided for internal use so that other labellers can piggyback off one another.
Returns:

  • x_labelled (LandmarkGroup or PointCloud) – If a LandmarkGroup was passed, a LandmarkGroup is returned. This landmark group will contain specific labels and these labels may refer to sub-pointclouds with specific connectivity information.

    If a PointCloud was passed, a PointCloud is returned. Only the connectivity information is propagated to the pointcloud (a subclass of PointCloud may be returned).

  • mapping_dict (ordereddict {str -> int ndarray}, optional) – Only returned if return_mapping==True. Used for building LandmarkGroup.
Raises:

: :map:`LabellingError` – If the given landmark group/pointcloud contains less than the expected number of points.