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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+"""Export Dyn-HaMR MANO joints, preserving the exact reconstruction FK convention."""
+import os
+os.environ.setdefault('OMP_NUM_THREADS', '4')
+import sys
+from pathlib import Path
+import numpy as np
+import torch
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT / 'third_party/Dyn-HaMR/dyn-hamr'))
+from body_model.mano_wrapper import MANO
+
+def main():
+    torch.set_num_threads(4)
+    source = ROOT / 'output/results_2047635068/world_results.npz'
+    out = ROOT / 'output/dex_2047635068'
+    out.mkdir(exist_ok=True)
+    data = np.load(source)
+    candidates = np.flatnonzero(np.all(data['is_right'] > .5, axis=1))
+    assert len(candidates) == 1, 'Expected exactly one consistent right-hand track'
+    track = int(candidates[0])
+    pose = data['pose_body'][track].reshape(-1, 45)
+    model = MANO(model_path=str(ROOT / 'third_party/Dyn-HaMR/_DATA/data/mano'),
+                 batch_size=128, pose2rot=True)
+    joints = []
+    wrists = []
+    with torch.no_grad():
+        for start in range(0, len(pose), 128):
+            p = torch.from_numpy(pose[start:start+128]).float()
+            n = len(p)
+            result = model(hand_pose=p, global_orient=torch.zeros(n, 3),
+                           transl=torch.zeros(n, 3),
+                           betas=torch.from_numpy(data['betas'][track]).float().expand(n, -1))
+            j = result.joints.numpy()
+            joints.append(j - j[:, :1])
+            world = model(hand_pose=p,
+                          global_orient=torch.from_numpy(data['root_orient'][track,start:start+n]).float(),
+                          transl=torch.from_numpy(data['trans'][track,start:start+n]).float(),
+                          betas=torch.from_numpy(data['betas'][track]).float().expand(n,-1))
+            wrists.append(world.joints[:,0].numpy())
+    joints = np.concatenate(joints)
+    assert joints.shape == (len(pose), 21, 3) and np.isfinite(joints).all()
+    np.savez_compressed(out / 'human_joints.npz', joints=joints, fps=30,
+                        source_track=track, source=str(source.resolve()),
+                        wrist_world=np.concatenate(wrists),
+                        root_orient=data['root_orient'][track], trans=data['trans'][track])
+    print(f'Exported {joints.shape}, right track {track}, to {out}', flush=True)
+
+if __name__ == '__main__':
+    main()