Update archives, README and checksums for recon-hoi release

README.md

@@ -41,7 +41,7 @@ Prompt template used for generation: `<VIDEO> In a real-world continuous footage
 
 ## Download
 
-The repository contains ~4,900 small files, so a per-file download hits the Hub's API rate limit. Download the single archive instead (317 MB, sha256 `eb1fbcd2ef2714218292f9faf98e6cf57ac7f792da0becf89b3ca89d65850f5d`):
+The repository contains ~7,900 small files, so a per-file download hits the Hub's API rate limit. Download the single archive instead (495 MB, sha256 `b030baccb16beb633a647366f1c1a06ae4a8b106923fa7d50d4123b68b1e6a52`):
 
 ```bash
 hf download Amazon-FAR/far-prism-data far-prism-data.tar.gz --repo-type dataset --local-dir .
@@ -51,6 +51,8 @@ cd far-prism-data && sha256sum --check SHA256SUMS --quiet && echo OK
 
 The extracted directory has exactly the layout below. The individual files are kept in the repository for browsing.
 
+The visual meshes inside the repository are decimated to 50k faces (bounding boxes change by < 1 mm, vertex colors kept) so that the object URDFs load everywhere without a 10 GB download. The original full-resolution reconstructions (129 meshes, ~0.5–1.2 M faces each) are in `recon-hoi-visual-meshes-original.tar.gz` (2.39 GB, sha256 `5b624d6a36786747de33c21f959b77db3c5283c6b5decb2d1271e1fb6cccefb7`); extract it over `data/recon-hoi/` to replace the decimated files.
+
 ## What is included
 
 **129 clips** (box 35, bin 32, barrel 34, ball 28) from the 137 generated clips, keeping the ones whose teacher rollout succeeded. Per-clip index: `clips.csv`.
@@ -62,7 +64,13 @@ data/train-student/
   data/robot_assets/         G1 URDF and depth-rendering meshes
   data/checkpoints/          teacher_40000.pt (privileged teacher), box_23000.pt (student initialiser)
   vis/                       129 x <clip_id>.mp4  reference replays (1280x720, 50 fps)
-data/raw_video/  data/recon-hoi/  data/train-teacher/     under review, placeholder README only
+data/recon-hoi/<clip_id>/
+  <clip_id>_real2sim_six_axis_iou_strict_v19.obj    object visual mesh, decimated to 50k faces with vertex colors (originals: see below)
+  <clip_id>_real2sim_six_axis_iou_strict_v19.urdf   object URDF (visual mesh + convex collision parts)
+  meshes_collision_convex/part_*.obj                 COACD convex collision meshes (unchanged)
+  retarget_qpos.npz                                  contact-anchored retarget result, qpos (217, 43) at 30 fps
+data/recon-hoi/index.json                            per-clip object size, human height, SMPL scale, mesh face counts
+data/raw_video/  data/train-teacher/                 under review, placeholder README only
 ```
 
 Clip ids follow `prism_cf_<category>_m<seed>_v<variant>`.

far-prism-data.tar.gz

@@ -1,3 +1,3 @@
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-oid sha256:eb1fbcd2ef2714218292f9faf98e6cf57ac7f792da0becf89b3ca89d65850f5d
-size 316914726
+oid sha256:b030baccb16beb633a647366f1c1a06ae4a8b106923fa7d50d4123b68b1e6a52
+size 495210307

recon-hoi-visual-meshes-original.tar.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5b624d6a36786747de33c21f959b77db3c5283c6b5decb2d1271e1fb6cccefb7
+size 2390028411