pose_human36M_32_to_pose_human36M_32

menpo.landmark.pose_human36M_32_to_pose_human36M_32(x, return_mapping=False)

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 (LabelledPointUndirectedGraph or PointCloud or ndarray) – The input labelled point graph, pointcloud, subclass of those 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 LabelledPointUndirectedGraph. This parameter is only provided for internal use so that other labellers can piggyback off one another.

Returns:

• x_labelled (LabelledPointUndirectedGraph or PointCloud) – If a LabelledPointUndirectedGraph was passed, a LabelledPointUndirectedGraph is returned. This labelled pointgraph 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 LabelledPointUndirectedGraph.

Raises:

: :map:`LabellingError` – If the given labelled point graph/pointcloud contains less than the expected number of points.