Method forward

detrsmpl/models/body_models/mano.py:207–256

Forward function. Args: *args: extra arguments for MANO return_verts: whether to return vertices return_full_pose: whether to return full pose parameters **kwargs: extra arguments for MANO Returns: output: contains output

(self,
                *args,
                return_verts: bool = True,
                return_full_pose: bool = False,
                **kwargs)

        self.num_joints = get_keypoint_num(convention=self.keypoint_dst)

    def forward(self,
                *args,
                return_verts: bool = True,
                return_full_pose: bool = False,
                **kwargs) -> dict:
        """Forward function.

        Args:
            *args: extra arguments for MANO
            return_verts: whether to return vertices
            return_full_pose: whether to return full pose parameters
            **kwargs: extra arguments for MANO

        Returns:
            output: contains output parameters and attributes
        """
        if 'right_hand_pose' in kwargs:
            kwargs['hand_pose'] = kwargs['right_hand_pose']
        mano_output = super(MANOLayer, self).forward(*args, **kwargs)
        joints = mano_output.joints

        joints = self.get_keypoints_from_mesh(mano_output.vertices, joints)

        joints, joint_mask = convert_kps(joints,
                                         src=self.keypoint_src,
                                         dst=self.keypoint_dst,
                                         approximate=self.keypoint_approximate)
        if isinstance(joint_mask, np.ndarray):
            joint_mask = torch.tensor(joint_mask,
                                      dtype=torch.uint8,
                                      device=joints.device)

        batch_size = joints.shape[0]
        joint_mask = joint_mask.reshape(1, -1).expand(batch_size, -1)

        output = dict(
            global_orient=mano_output.global_orient,
            hand_pose=mano_output.hand_pose,
            joints=joints,
            joint_mask=joint_mask,
            keypoints=torch.cat([joints, joint_mask[:, :, None]], dim=-1),
            betas=mano_output.betas,
        )

        if return_verts:
            output['vertices'] = mano_output.vertices
        if return_full_pose:
            output['full_pose'] = mano_output.full_pose

        return output

    def get_keypoints_from_mesh(self, mesh_vertices, keypoints_regressed):
        """Assembles the full 21 keypoint set from the 16 Mano Keypoints and 5