Ship the WeChat hot-update catalogs and the camp, TideWhale T2, UI atlas, and animation-lab work.

Co-authored-by: Cursor <cursoragent@cursor.com>

Tools/tokenrig_lmgirl_trial_remote.py

@@ -0,0 +1,36 @@
+"""Job-scoped instrumentation of installed TokenRig; no shared code modified.
+
+Run inside the existing DGXA container. One prediction produces raw + voxel
+postprocessed outputs, avoiding stochastic differences between the two trials.
+"""
+import hashlib
+import os
+from pathlib import Path
+import runpy
+import sys
+
+job=Path(__file__).resolve().parent
+source=Path('/workspace/SkinTokens/demo.py').read_text()
+needle='        if use_postprocess:\n'
+assert source.count(needle)==1
+instrument='''        import numpy as np
+        import os
+        pair_folder = os.environ["TOKENRIG_PAIR_FOLDER"]
+        np.savez_compressed(pair_folder + "/raw_prediction.npz", vertices=asset.vertices, faces=asset.faces, joints=asset.joints, parents=asset.parents, skin=asset.skin)
+        post_bpy_payload("transfer", dict(source_asset=asset, target_path=asset.path, export_path=pair_folder + "/rigged_raw.glb", group_per_vertex=4))
+        print("PAIR_RAW_EXPORTED", flush=True)
+'''
+source=source.replace(needle,instrument+needle)
+needle2='            asset.normalize_skin()\n'
+assert source.count(needle2)==1
+source=source.replace(needle2,needle2+'''            np.savez_compressed(pair_folder + "/post_prediction.npz", vertices=asset.vertices, faces=asset.faces, joints=asset.joints, parents=asset.parents, skin=asset.skin)
+            print("PAIR_POSTPROCESSED", flush=True)
+''')
+source='import random\nimport numpy as np\nimport torch\nrandom.seed(20261023)\nnp.random.seed(20261023)\ntorch.manual_seed(20261023)\n'+source
+script=job/'instrumented_demo.py'
+script.write_text(source)
+(job/'installed_demo.sha256').write_text(hashlib.sha256(Path('/workspace/SkinTokens/demo.py').read_bytes()).hexdigest())
+os.environ['TOKENRIG_PAIR_FOLDER']=str(job)
+sys.argv=[str(script),'--input',str(job/'source.glb'),'--output',str(job/'rigged_post.glb'),
+          '--use_skeleton','--use_transfer','--use_postprocess','--skeleton_template','original','--rig_cls','vroid']
+runpy.run_path(str(script),run_name='__main__')