| import torch | |
| from manopth.manolayer import ManoLayer | |
| from manopth import demo | |
| batch_size = 10 | |
| # Select number of principal components for pose space | |
| ncomps = 6 | |
| # Initialize MANO layer | |
| mano_layer = ManoLayer( | |
| mano_root='mano/models', use_pca=True, ncomps=ncomps, flat_hand_mean=False) | |
| # Generate random shape parameters | |
| random_shape = torch.rand(batch_size, 10) | |
| # Generate random pose parameters, including 3 values for global axis-angle rotation | |
| random_pose = torch.rand(batch_size, ncomps + 3) | |
| # Forward pass through MANO layer | |
| hand_verts, hand_joints = mano_layer(random_pose, random_shape) | |
| demo.display_hand({ | |
| 'verts': hand_verts, | |
| 'joints': hand_joints | |
| }, | |
| mano_faces=mano_layer.th_faces) | |