Convert pose parameters to rotation matrix Args: param_dict: smplx parameters param_type: should be one of body/head/hand Returns: param_dict: smplx parameters
(self, param_dict, param_type)
| 320 | return param_dict |
| 321 | |
| 322 | def convert_pose(self, param_dict, param_type): |
| 323 | ''' Convert pose parameters to rotation matrix |
| 324 | Args: |
| 325 | param_dict: smplx parameters |
| 326 | param_type: should be one of body/head/hand |
| 327 | Returns: |
| 328 | param_dict: smplx parameters |
| 329 | ''' |
| 330 | assert param_type in ['body', 'head', 'hand'] |
| 331 | |
| 332 | # convert pose representations: the output from network are continous repre or axis angle, |
| 333 | # while the input pose for smplx need to be rotation matrix |
| 334 | for key in param_dict: |
| 335 | if "pose" in key and 'jaw' not in key: |
| 336 | param_dict[key] = converter.batch_cont2matrix(param_dict[key]) |
| 337 | if param_type == 'body' or param_type == 'head': |
| 338 | param_dict['jaw_pose'] = converter.batch_euler2matrix(param_dict['jaw_pose'])[ |
| 339 | :, None, :, :] |
| 340 | |
| 341 | # complement params if it's not in given param dict |
| 342 | if param_type == 'head': |
| 343 | batch_size = param_dict['shape'].shape[0] |
| 344 | param_dict['abs_head_pose'] = param_dict['head_pose'].clone() |
| 345 | param_dict['global_pose'] = param_dict['head_pose'] |
| 346 | param_dict['partbody_pose'] = self.smplx.body_pose.unsqueeze(0).expand( |
| 347 | batch_size, -1, -1, -1)[:, :self.param_list_dict['body_list']['partbody_pose']] |
| 348 | param_dict['neck_pose'] = self.smplx.neck_pose.unsqueeze( |
| 349 | 0).expand(batch_size, -1, -1, -1) |
| 350 | param_dict['left_wrist_pose'] = self.smplx.neck_pose.unsqueeze( |
| 351 | 0).expand(batch_size, -1, -1, -1) |
| 352 | param_dict['left_hand_pose'] = self.smplx.left_hand_pose.unsqueeze( |
| 353 | 0).expand(batch_size, -1, -1, -1) |
| 354 | param_dict['right_wrist_pose'] = self.smplx.neck_pose.unsqueeze( |
| 355 | 0).expand(batch_size, -1, -1, -1) |
| 356 | param_dict['right_hand_pose'] = self.smplx.right_hand_pose.unsqueeze( |
| 357 | 0).expand(batch_size, -1, -1, -1) |
| 358 | elif param_type == 'hand': |
| 359 | batch_size = param_dict['right_hand_pose'].shape[0] |
| 360 | param_dict['abs_right_wrist_pose'] = param_dict['right_wrist_pose'].clone() |
| 361 | dtype = param_dict['right_hand_pose'].dtype |
| 362 | device = param_dict['right_hand_pose'].device |
| 363 | x_180_pose = torch.eye( |
| 364 | 3, dtype=dtype, device=device).unsqueeze(0).repeat(1, 1, 1) |
| 365 | x_180_pose[0, 2, 2] = -1. |
| 366 | x_180_pose[0, 1, 1] = -1. |
| 367 | param_dict['global_pose'] = x_180_pose.unsqueeze( |
| 368 | 0).expand(batch_size, -1, -1, -1) |
| 369 | param_dict['shape'] = self.smplx.shape_params.expand( |
| 370 | batch_size, -1) |
| 371 | param_dict['exp'] = self.smplx.expression_params.expand( |
| 372 | batch_size, -1) |
| 373 | param_dict['head_pose'] = self.smplx.head_pose.unsqueeze( |
| 374 | 0).expand(batch_size, -1, -1, -1) |
| 375 | param_dict['neck_pose'] = self.smplx.neck_pose.unsqueeze( |
| 376 | 0).expand(batch_size, -1, -1, -1) |
| 377 | param_dict['jaw_pose'] = self.smplx.jaw_pose.unsqueeze( |
| 378 | 0).expand(batch_size, -1, -1, -1) |
| 379 | param_dict['partbody_pose'] = self.smplx.body_pose.unsqueeze(0).expand( |