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
7002 changed files with 1452249 additions and 0 deletions
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+import torch
+import lietorch
+import numpy as np
+
+from lietorch import SE3
+from factor_graph import FactorGraph
+
+
+class DroidBackend:
+    def __init__(self, net, video, args):
+        self.video = video
+        self.update_op = net.update
+
+        # global optimization window
+        self.t0 = 0
+        self.t1 = 0
+
+        self.upsample = args.upsample
+        self.beta = args.beta
+        self.backend_thresh = args.backend_thresh
+        self.backend_radius = args.backend_radius
+        self.backend_nms = args.backend_nms
+        
+    @torch.no_grad()
+    def __call__(self, steps=12):
+        """ main update """
+
+        t = self.video.counter.value
+        if not self.video.stereo and not torch.any(self.video.disps_sens):
+             self.video.normalize()
+
+        graph = FactorGraph(self.video, self.update_op, corr_impl="alt", max_factors=16*t, upsample=self.upsample)
+
+        graph.add_proximity_factors(rad=self.backend_radius, 
+                                    nms=self.backend_nms, 
+                                    thresh=self.backend_thresh, 
+                                    beta=self.beta)
+
+        graph.update_lowmem(steps=steps)
+        graph.clear_edges()
+        self.video.dirty[:t] = True