Initial snapshot: hand motion pipeline (Dyn-HaMR + dex-retargeting + SPIDER)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-09-15 14:13:49 +08:00
commit 7e4ef6f98b
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+# Copyright (c) OpenMMLab. All rights reserved.
+import os.path as osp
+import tempfile
+
+import numpy as np
+import torch
+
+from mmpose.models.utils import SMPL
+from tests.utils.mesh_utils import generate_smpl_weight_file
+
+
+def test_smpl():
+    """Test smpl model."""
+
+    # build smpl model
+    smpl = None
+    with tempfile.TemporaryDirectory() as tmpdir:
+        # generate weight file for SMPL model.
+        generate_smpl_weight_file(tmpdir)
+
+        smpl_cfg = dict(
+            smpl_path=tmpdir,
+            joints_regressor=osp.join(tmpdir, 'test_joint_regressor.npy'))
+        smpl = SMPL(**smpl_cfg)
+
+    assert smpl is not None, 'Fail to build SMPL model'
+
+    # test get face function
+    faces = smpl.get_faces()
+    assert isinstance(faces, np.ndarray)
+
+    betas = torch.zeros(3, 10)
+    body_pose = torch.zeros(3, 23 * 3)
+    global_orient = torch.zeros(3, 3)
+    transl = torch.zeros(3, 3)
+    gender = torch.LongTensor([-1, 0, 1])
+
+    # test forward with body_pose and global_orient in axis-angle format
+    smpl_out = smpl(
+        betas=betas, body_pose=body_pose, global_orient=global_orient)
+    assert isinstance(smpl_out, dict)
+    assert smpl_out['vertices'].shape == torch.Size([3, 6890, 3])
+    assert smpl_out['joints'].shape == torch.Size([3, 24, 3])
+
+    # test forward with body_pose and global_orient in rotation matrix format
+    body_pose = torch.eye(3).repeat([3, 23, 1, 1])
+    global_orient = torch.eye(3).repeat([3, 1, 1, 1])
+    _ = smpl(betas=betas, body_pose=body_pose, global_orient=global_orient)
+
+    # test forward with translation
+    _ = smpl(
+        betas=betas,
+        body_pose=body_pose,
+        global_orient=global_orient,
+        transl=transl)
+
+    # test forward with gender
+    _ = smpl(
+        betas=betas,
+        body_pose=body_pose,
+        global_orient=global_orient,
+        transl=transl,
+        gender=gender)
+
+    # test forward when all samples in the same gender
+    gender = torch.LongTensor([0, 0, 0])
+    _ = smpl(
+        betas=betas,
+        body_pose=body_pose,
+        global_orient=global_orient,
+        transl=transl,
+        gender=gender)
+
+    # test forward when batch size = 0
+    _ = smpl(
+        betas=torch.zeros(0, 10),
+        body_pose=torch.zeros(0, 23 * 3),
+        global_orient=torch.zeros(0, 3))