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EgoPressure/shared-v1.1/doc/SDK_LICENSE.txt

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+MICROSOFT SOFTWARE LICENSE TERMS
+MICROSOFT AZURE KINECT SENSOR SOFTWARE DEVELOPMENT KIT
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EgoPressure/shared-v1.1/doc/SDK_REDIST.txt

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+sdk\linux_gnu\amd64\release\lib\libdepthengine.so
+sdk\linux_gnu\amd64\release\lib\libdepthengine.so.2.0
+sdk\linux_gnu\amd64\release\lib\libk4a.so.1.4.1
+sdk\linux_gnu\amd64\release\lib\libk4arecord.so.1.4.1
+sdk\linux_gnu\arm64\release\lib\libdepthengine.so
+sdk\linux_gnu\arm64\release\lib\libdepthengine.so.2.0
+sdk\linux_gnu\arm64\release\lib\libk4a.so.1.4.1
+sdk\linux_gnu\arm64\release\lib\libk4arecord.so.1.4.1
+sdk\netstandard2.0\release\Microsoft.Azure.Kinect.Sensor.dll
+sdk\windows-desktop\amd64\release\bin\depthengine_2_0.dll
+sdk\windows-desktop\amd64\release\bin\k4a.dll
+sdk\windows-desktop\amd64\release\bin\k4arecord.dll
+sdk\windows-desktop\x86\release\bin\depthengine_2_0.dll
+sdk\windows-desktop\x86\release\bin\k4a.dll
+sdk\windows-desktop\x86\release\bin\k4arecord.dll
+tools\AzureKinectFirmwareTool.exe
+tools\k4arecorder.exe
+tools\k4aviewer.exe
+tools\firmware\AzureKinectDK_Fw_1.6.110079014.bin

EgoPressure/shared-v1.1/doc/SDK_provenance.json

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+{
+  "url": "https://api.nuget.org/v3-flatcontainer/microsoft.azure.kinect.sensor/1.4.1/microsoft.azure.kinect.sensor.1.4.1.nupkg",
+  "version": "1.4.1",
+  "package_sha256": "6c512a20c4a82b80e02b0f6d4a6cda51e88d4893cd47ab85c7bca37cd364c976"
+}

EgoPressure/shared-v1.1/doc/SOURCE.json

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+{
+  "dataset": "EgoPressure",
+  "source_repo": "eth-siplab/EgoPressure",
+  "source_revision": "cea37de99be44078f0e4b9796fd6f614d9110dc2",
+  "source_url": "https://huggingface.co/datasets/eth-siplab/EgoPressure",
+  "attribution": "Yiming Zhao, Taein Kwon, Paul Streli, Marc Pollefeys, Christian Holz. EgoPressure, CVPR 2025.",
+  "license": "CC-BY-NC-SA-4.0; MANO-derived annotations additionally subject to the MANO license",
+  "selection": {
+    "participants": "all 21",
+    "sequences": 1344,
+    "camera": "d (egocentric)",
+    "modalities": [
+      "RGB",
+      "depth",
+      "MANO and ego pose annotations",
+      "all original configs"
+    ]
+  }
+}

EgoPressure/shared-v1.1/doc/SOURCE_README.md

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+---
+license: cc-by-nc-sa-4.0
+pretty_name: EgoPressure
+tags:
+  - hand-pose
+  - pressure-estimation
+  - egocentric-vision
+  - hand-object-interaction
+  - MANO
+size_categories:
+  - 1M<n<10M
+---
+
+<h1 align="center">EgoPressure: A Dataset for Hand Pressure and Pose Estimation in Egocentric Vision</h1>
+
+<div align="center">
+
+**CVPR 2025 (Highlight)**
+
+[Yiming Zhao<sup>1*</sup>](https://yiming-zhao.github.io), [Taein Kwon<sup>1*</sup>](https://taeinkwon.com/), [Paul Streli<sup>1*</sup>](https://www.paulstreli.com), [Marc Pollefeys<sup>1,2</sup>](https://people.inf.ethz.ch/marc.pollefeys/), [Christian Holz<sup>1</sup>](https://www.christianholz.net/)<br/>
+
+<sup>1</sup> ETH Zürich
+<sup>2</sup> Microsoft<br/>
+<sup>*</sup> Equal contribution<br/>
+
+</div>
+
+A dataset for **hand pressure and pose estimation in egocentric vision**.
+Participants perform touch gestures on a
+pressure-sensing touchpad (Sensel Morph) while being recorded by a
+head-mounted egocentric camera and seven static Azure Kinects — providing
+synchronized RGB-D from 8 views, fine-grained touch pressure for every
+contact, and MANO hand mesh annotations.
+
+- 📄 Paper: https://arxiv.org/abs/2409.02224
+- 🛠️ Toolkit (download / load / visualize): https://github.com/eth-siplab/EgoPressure
+- 🎬 Preview videos: https://drive.google.com/drive/folders/1JUIUvIR2jAV-ghYGtVLgBEN1JdCzkvnE
+
+<p align="center">
+<img src="assets/teaser.gif" width="800">
+</p>
+
+## Composition
+
+| | |
+|---|---|
+| Participants | 21 (pseudonymized `p_001` … `p_021`) |
+| Sequences | **1,344** — 32 gestures × 2 hands per participant |
+| Gestures | palm/finger/index presses (high, low, no-contact), pinches, pinch-zoom, grasps, pull/push, drawing, typing + a calibration routine |
+| Views | 8 synchronized RGB-D cameras (1 egocentric 1920×1080 + 7 static 2560×1440) at 30 Hz |
+| Frames | ≈630K per camera stream (≈5M camera-frames overall) |
+| Modalities | RGB, depth, hand masks, raw touch-pressure grid, UV pressure maps, MANO hand meshes (pose, shape, per-vertex refinement), per-frame egocentric camera pose |
+| Total size | **1.96 TB** — selectively downloadable per participant / sequence / camera / modality |
+
+## Quick start (toolkit)
+
+The official toolkit handles selective download, loading every modality,
+geometry, and visualization:
+
+```bash
+pip install "egopressure[all] @ git+https://github.com/eth-siplab/EgoPressure"
+
+egopressure list
+egopressure download --participants p_001 --cameras d --modalities rgb,depth,pressure,pose
+egopressure video p_001 p_001_press_palm_low_x5_right --out seq.mp4
+```
+
+```python
+from egopressure import EgoPressure
+
+ep = EgoPressure.from_hub(participants=["p_001"], cameras=["d"],
+                          modalities=["rgb", "depth", "pressure", "pose"])
+seq = ep.sequence("p_001", "p_001_press_palm_low_x5_right")
+frame = seq.load_frame(60, depth=True)      # rgb, depth, force, annotation
+frame.show(camera="d", overlays=["mesh", "skeleton", "pressure"])
+```
+
+The toolkit's [data reference](https://github.com/eth-siplab/EgoPressure/blob/master/docs/DATA.md)
+documents every field, unit, and convention.
+
+## Download without the toolkit
+
+Everything is sharded by participant / sequence / camera / modality, so plain
+`huggingface_hub` works too:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download("eth-siplab/EgoPressure", repo_type="dataset",
+                  local_dir="egopressure_data",
+                  allow_patterns=["configs/p_001/*",
+                                  "data/p_001/*/cam-d.color.parquet",
+                                  "data/p_001/*/pressure.parquet",
+                                  "data/p_001/*/annotation.parquet"])
+```
+
+### Layout
+
+```
+configs/<participant>/<sequence>.json         # camera calibration + metadata
+configs/<participant>/<sequence>_k4a/         # per-camera factory calibrations
+data/<participant>/<sequence>/
+    cam-d.color.parquet   cam-1.color.parquet ... cam-7.color.parquet
+    cam-d.depth.parquet   cam-1.depth.parquet ... cam-7.depth.parquet
+    cam-d.mask.parquet    cam-1.mask.parquet  ... cam-7.mask.parquet
+    pressure.parquet                                 # Sensel grid + UV pressure
+    annotation.parquet                               # MANO pose/mesh + ego pose
+```
+
+Each Parquet shard holds one row per frame (`frame` column).
+
+### Modalities
+
+| Shard | Content |
+|---|---|
+| `cam-*.color` | RGB frames as original JPEG bytes (ego `d`: 1920×1080; static `1..7`: 2560×1440; undistorted) |
+| `cam-*.depth` | 512×512 uint16 depth in millimetres (PNG bytes), all 8 cameras; depth-sensor frame, covering the camera's color view (+32 px guard band) — `0` = no measurement |
+| `cam-*.mask` | hand segmentation masks (PNG bytes) |
+| `pressure` | raw Sensel Morph grid (105×185 float32, flattened) + normalised 224×224 UV pressure map with `[min, max]` range |
+| `annotation` | MANO `vertices (778×3)`, `joint_position (21×3)`, `betas (10)`, `full_pose (48)`, `transl`, `normals`, `displacement`, per-static-camera `visible_vertices (7×778)`, per-frame egocentric camera pose (`ego_R` 3×3, `ego_T` 3) |
+
+### Geometry essentials
+
+- World origin on the touchpad surface (the calibrated 240 × 137.5 mm pad
+  rectangle, x–y plane at z = 0); MANO vertices and the ego pose are in **metres**, static-camera
+  `ModelViewMatrix` extrinsics in **millimetres**.
+- Images are undistorted → plain pinhole projection with the config intrinsics.
+- Depth maps are in each camera's **depth-sensor frame** (not registered to
+  color) and cover the region co-visible with that camera's color image;
+  `configs/<p>/<seq>_k4a/` holds the factory calibrations — the toolkit's
+  `register_depth_to_color()` produces pixel-aligned RGB-D.
+- Raw sensor counts convert to Newtons via `counts / 1736` (cell pitch 1.25 mm).
+
+## License & citation
+
+Released under **CC BY-NC-SA 4.0** (non-commercial, academic). MANO-derived
+annotations are additionally subject to the
+[MANO license](https://mano.is.tue.mpg.de/license.html).
+
+```bibtex
+@InProceedings{Zhao_2025_CVPR,
+  author    = {Zhao, Yiming and Kwon, Taein and Streli, Paul and Pollefeys, Marc and Holz, Christian},
+  title     = {EgoPressure: A Dataset for Hand Pressure and Pose Estimation in Egocentric Vision},
+  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  month     = {June},
+  year      = {2025},
+  pages     = {27727--27738}
+}
+```

EgoPressure/shared-v1.1/doc/USAGE.md

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+# EgoPressure shared-v1.1
+
+Each data/<sequence>/cam-d-rgb directory contains original RGB, registered depth, pixel validity, camera tensors, frame IDs and standard MANO. Depth is camera Z in metres. Dataset attribution and licensing are in SOURCE.json and SOURCE_README.md. See RAW_TO_SHARED.json for geometry and LOCAL_VALIDATION.json for validation coverage.
+
+To read, import Reader from script/egopressure_pilot_v3_reader.py, construct Reader(view_path), iterate reader.frames(), and call reader.tensor("mano") or reader.tensor("mano","valid").
+
+To reproduce on Windows x64, install Python packages numpy, scipy, torch with weights_only support, PyAV, opencv-python and pyarrow. Set EGOPRESSURE_K4A_SDK to the extracted Microsoft.Azure.Kinect.Sensor 1.4.1 NuGet package (see SDK_provenance.json). Set EGOPRESSURE_RAW_DATA to the downloaded EgoPressure/raw/data directory, EGOPRESSURE_MANO_PATH to your licensed MANO model directory, and EGOPRESSURE_TOOLKIT_MANO to egopressure/mano.py from the eth-siplab/EgoPressure toolkit at commit 517b4ffe39e38641e0eadff6680d956d53263d68. Supply left and right MANO models in the source convention. Run python script/convert_sequence.py SEQUENCE --out NEW_DIRECTORY. Each invocation accepts a fresh output directory. The published media use lossless FFV1 and original JPEG payloads.

EgoPressure/shared-v1.1/doc/V1_0_SEMANTICS.md

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+# 手物数据仓库统一约定 v1.0
+
+格式版本：`hand-warehouse/1.0`。存储约定：`lossless-video-2026-09-18`。
+
+范围限于手物交互重建。按本任务纳入的源模态转换，不要求每个数据集填满所有组件。缺失模态、尚未下载、语义未核实分别报告，不能互相替代。
+
+本文定义各字段的含义与使用规则，机器可读注册表见 [schema.json](schema.json)。两者互相补充；如有冲突，应先核实并统一定义。
+
+## 1. 目录
+
+```text
+hand-datasets/
+  <dataset_name>/
+    raw/
+      doc/                         # 官方说明、来源与校验记录
+      script/                      # 官方下载脚本、必要包装脚本
+      data/                        # 保留原始包，不原地解压或改写
+    <dataset_version>/
+      doc/                         # 发布说明、schema、来源清单
+      script/                      # 转换、校验脚本及运行配置
+      data/
+        <sequence_id>/
+          <camera_id>/
+            metainfo.json
+            observation/
+              rgb.mkv
+              rgb_valid.pt
+              depth.mkv           # float32 深度的可逆视频编码
+              depth_valid.mkv     # 逐像素 bool 的无损视频编码
+            camera/
+              frames.jsonl
+              intrinsic.pt
+              intrinsic_valid.pt
+              extrinsic.pt
+              extrinsic_valid.pt
+            annotation/
+              mano/
+                motion.pt
+                motion_valid.pt
+                visibility.pt
+              keypoints/
+                uv.pt
+                uv_valid.pt
+                xyz.pt
+                xyz_valid.pt
+                visibility.pt    # 源数据有时提供
+              object/
+                <object_id>/
+                  assets/          # 该物体的网格、材质、纹理及部件资产
+                    <mesh_id>.obj
+                  pose.pt
+                  pose_valid.pt
+                  visibility.pt
+                  metainfo.json    # 物体身份、类别、mesh、尺寸与部件引用
+                  articulation.json
+                  keypoints/
+                  vertex_part_ids.pt
+                  joint_state.pt
+                  joint_state_valid.pt
+                  parts/<part_id>/pose.pt
+                  parts/<part_id>/pose_valid.pt
+              segment/
+                mask.mkv
+                mask_valid.pt
+                instances.jsonl
+              contact/
+                relations.jsonl
+                <subject_id>__<object_id>/  # 对应实体间的距离/接触区域
+```
+
+目录展示可能存在的组件，不要求填满。具体文件、字段和缺省规则分别见后续对应小节。原始包的解压发生在临时工作区，raw 内原始包保持不变。
+
+## 2. 相机视图的 metainfo.json
+
+### 2.1 顶层字段与发布信息
+
+每个相机视图必须有 `metainfo.json`。以下字段除另行说明外均为必填：
+
+| 字段 | 填写内容 |
+|---|---|
+| schema_version | 结构版本，本版为 `hand-warehouse/1.0` |
+| dataset_id | 数据集的逻辑标识 |
+| release_id | 本次数据发布版本，对应目录中的 dataset_version |
+| sequence_id | 所属序列或独立图片样本的标识 |
+| camera_id | 当前相机视图标识 |
+| sample_type | `image` 或 `video`，规则见 2.2 |
+| num_frames | 当前视图帧数 T，所有随帧组件按同一时间轴组织 |
+| hand_slots | 固定为 `["left", "right"]`；解剖学左右的使用规则见 5.1 |
+| sampling | 采样类型、源 FPS、帧索引引用及选择策略，见 2.2 |
+| camera | 当前相机模型与图像尺寸，见 2.3 |
+| components | 实际提供的组件及其文件、schema、有效性和来源，见 2.5 |
+| split | `train/val/test/unknown`，划分协议见 2.4 |
+| view_type | 可选，`ego/exo/unknown` |
+
+`dataset_version` 是数据发布版本；`schema_version` 是结构版本，两者独立。原始包校验摘要、官方来源和转换配置应记录在发布清单中。解压发生在临时工作区，原始包保持不变。
+
+### 2.2 图片、视频与 sampling
+
+`sample_type=image`：允许单图 T=1、`sampling.type=single`，也允许将独立图片批量装入一个视频容器，T>1 时 `sampling.type=independent`、`source_fps=null`。分片大小按数据集选择；FreiHAND 默认每片最多 4096 张，训练与评估分开，尾片不补帧。该数量不是其他数据集的强制要求；同批分辨率、相机模型类型及划分协议一致。每行 frames 必须有稳定且唯一的 `sample_id`、原始文件定位；内参、手形状等仍逐帧保留，不能因打包而共享错误的标定或身份。`sequence_id` 在这里仅是批次标识，不代表真实序列；不得按相邻帧推断跟踪、同步或接触延续。源 camera_id、image_variant、split 等随样本变化时放在 frames 的对应字段中。真实采集时间未知则 timestamp_ns=null。合成背景变体不视为真实多相机。
+
+`sample_type=video`：`sampling.type=dense/sparse`；`source_fps` 是真实采集 FPS，未知为 null。非连续取样必须保留源帧号和已知源时间，不可用采样后索引除以 FPS 冒充源时间。可另记采样策略与步长。
+
+shared 可以仅存所选 RGB 帧对应的数据。OakInk2 图像/动捕不同采样率时用 annotation_matches 明确映射；不要求将未采样动捕点硬塞进 T。多视角身份和源同步关系要保留；选择了哪些帧/相机及原因写在 sampling 中。
+
+`sampling.frames_ref` 指向 `camera/frames.jsonl`。帧号、逐帧时间、同步与标注匹配记录的结构见 4.1；MKV 封装时间的约定见 3.1。
+
+### 2.3 camera 模型声明
+
+`camera` 至少包含 `model`、`schema_id`、`image_size:[W,H]`。模型未知使用 `unknown` 和 `null`，不猜成针孔。实际内参、畸变及外参数组放在 `camera/`，各模型的固定结构见第 4 节。
+
+### 2.4 split 与划分协议
+
+保留上游划分，不将同一采集序列的相邻帧随意拆到不同集合。
+
+有官方划分时必填 split_scheme 和 split_source_locator，split_scheme 区分如 Dex-YCB s0/s1、ARCTIC P1/P2 等选定协议；不知道时 split=unknown 并给理由，不凭空分配。每发布可选择一种协议；存在逐帧差异时 frames 中的 split 覆盖视图默认值，并登记其来源。
+
+### 2.5 components 组件登记
+
+组件表的键是本发布内唯一名称，例如 `rgb`、`depth`、`mano`、`keypoints_uv`。每个已提供组件声明以下信息；模态特有参数在第 3–5 节对应小节中定义。
+
+| 字段 | 约定 |
+|---|---|
+| available | 本发布是否提供该组件；缺省也表示未提供 |
+| schema_id | 已登记的具体存储与语义类型，不得临时创造未登记名称 |
+| data_ref | 数据文件路径，相对当前相机视图根目录，使用 POSIX 路径 |
+| axes | 数组各维度的含义 |
+| valid_ref / valid_axes | 有效性文件及其维度；语义由所属组件规定 |
+| storage / valid_storage | 视频数据／视频有效性的存储配置；包含已登记 profile、实际 codec、pixel_format、encoded_size，见 3.1；非视频组件按原数组规则 |
+| provenance | source / format_conversion / derived，以及转换或生成方法 |
+| source_locator | 原文件、压缩包成员和记录／帧的定位信息 |
+
+不存在的组件允许缺省或写作 `{ "available": false, "reason": "..." }`，不用引用不存在的文件。静态网格可声明标量有效性；具体见 5.4。观测的 valid 见第 3 节，标注的 valid 与 visibility 区分见 5.1。
+
+`provenance.kind` 使用 source/format_conversion/derived，`method` 说明转换或生成方法；发布清单补充脚本版本、参数、输入摘要。`source_locator` 定位到原始文件/压缩包成员和记录、帧号；允许引用有完整溯源清单的前一发布，但链条最终应能回到 raw。不得仅写一个无法定位记录的数据集名字。
+
+`.pt` 仅保存 CPU Tensor，不保存 Python 自定义对象；浮点默认 float32，有效性为 bool，浮点无效位置填 NaN。所有随帧数组保留首维 T，单帧也不 squeeze；静态资产按其 schema 单独声明。单位、坐标及固定形状见各组件小节。
+
+机器注册表 `schema.json` 中，`components` 固定解码后的数据类型、形状、单位和语义；`storage_profiles` 固定视频内的编码／还原方式。不得临时创造未登记的 schema_id 或 storage.profile。同一语义允许选择其登记的不同无损存储 profile。
+
+## 3. observation 观测数据
+
+### 3.1 rgb.mkv 与 rgb_valid.pt
+
+RGB、深度和栅格 mask 在 shared 中统一使用 MKV 视频容器，不展开为逐帧图片或图像 tar。MANO、关键点、位姿等数值标注仍用数组；分割的重叠多边形仍用 JSONL，不为了视频化而有损栅格化。单图可为一帧视频，独立图批量封装规则见 2.2。
+
+**无损指共享层不增加信息损失。** 源 JPEG／H.264 等本身可能已是有损编码，原样保留并不恢复已丢失信息；不得重新以有损 JPEG、H.264、H.265、AV1 参数编码。源视频／图片的色彩、位深、分辨率和几何关系不得被静默改变。RGB schema `rgb/uint8/v1` 的统一读取结果是 `[T,H,W,3] uint8`、RGB 通道，有效性仍为 `rgb_valid.pt [T] bool`。超出该 schema 的高位深或 HDR 源必须报告并扩展定义，不能降到 8 位冒充无损。
+
+#### 3.1.1 允许的 RGB 存储 profile
+
+| storage.profile | 编码方式 | 适用规则 |
+|---|---|---|
+| mkv/mjpeg_copy/v1 | 源 JPEG 压缩帧直接封装成 MJPEG/MKV | 不解码重编码；保持每张 JPEG 码流字节；普通 8 位 JPEG 且 MKV/解码器支持时使用 |
+| mkv/source_copy/v1 | 已有视频的 RGB 对应码流直接封装为 MKV | 仅源编码能被 MKV 和选定解码器支持时使用，不伪造帧；需维持正确的呈现顺序与依赖帧 |
+| mkv/h264_rgb_lossless/v1 | libx264rgb 的真正无损模式 | 必须 RGB 路径、CRF=0，并通过全帧 RGB 字节比较；不能替换成默认 libx264 YUV420 路径 |
+| mkv/ffv1_rgb/v1 | FFV1 的 RGB 可逆编码路径 | 作为通用候选；解码回 RGB 后必须逐字节相同，不做色度降采样 |
+
+优先尝试源码流直接封装；不能封装或需要选择稀疏帧时，比较 FFV1 与无损 RGB H.264。对完整待发布片段，只在通过无损验收的候选中选择文件较小者，不假设某个编码器总最小；编码时间和随机读取代价记入构建记录。中间候选不作为 shared 多份常驻。H.264 跨帧压缩允许较长 GOP，必须记录 GOP／关键帧间隔，随机取帧需从前一关键帧正确解码，不能把 seek 返回的近似帧当目标帧。
+
+普通源视频可以保留它已有的有损码流，但不允许新增有损重编码。源是 VRS 等记录容器时，先查明图像流实际编码：已有兼容 JPEG／视频包可直接提取封装，否则解码后使用真正无损编码；不把整个 VRS 改后缀当 MKV。PNG 不要求直接塞进 MKV，可选上表两种无损重编码方式。
+
+#### 3.1.2 视频配置与校验
+
+每个视频组件在 metainfo 中登记 `storage`，至少包含：
+
+| 字段 | 内容 |
+|---|---|
+| profile | 上述登记的存储 profile；语义仍由组件 schema_id 指定 |
+| codec | 文件中实际 codec，例如 mjpeg、h264、ffv1；source_copy 必须写实际 codec |
+| pixel_format | 实际编码像素格式；不得仅凭编码器参数猜测 |
+| encoded_size | 视频物理像素尺寸 `[width,height]`；深度可能不同于逻辑尺寸，见 3.2 |
+| decoder | 解码器名称、版本，以及颜色矩阵／范围／旋转处理等实际像素解释配置；未知的源色彩声明 unknown，不擅自称为 sRGB |
+| encoder_parameters | 重编码时的编码器、版本、无损模式和 GOP 等参数；直接封装时记录 stream_copy |
+| source_lossy | 源是否已有损：true / false / unknown；不是共享层再有损编码的许可 |
+
+无损重新编码的 RGB 必须使用同一固定解码配置，比较**全部帧**的统一 RGB 字节、数量及顺序。MJPEG-copy 不重新编码，生产校验采用 `jpeg-packets-all-rgb-sample16/v1`：从 MKV 逐包取回，对全部源 JPEG 的 SHA256、数量、顺序和图像尺寸进行精确核对；每视图另用同一固定解码配置比较最多 16 帧的源与目标 RGB 字节（含首尾与四分位位置，其余由固定种子抽取）。记录策略、实际索引、种子与结果；不足 16 帧时全查。试点与最终完整序列随机抽查，对选中视图的全部帧复核解码 RGB。历史已做全帧像素检查的证明继续保留。
+
+逐包一致与像素抽查的范围必须分别声明，不能将抽查写成全量像素检查。不能用 PSNR 高、视觉相似、编码器参数称为 lossless 等替代精确检查。同时保留源编码的色彩标记和必要元数据；原图有 EXIF/色彩/方向等元数据时保留 raw 和必要来源信息；不能静默自动旋转图像而不更新像素对应与标定。以上加速策略仅适用于原 JPEG 码流直接封装，不适用于深度、标签或重新编码的 RGB。
+
+所有共享视频的呈现帧顺序与统一 frame_index 一一对应，每个栅格组件恰好 T 帧。MKV 的 `storage_fps` 只服务封装，声明 `timebase_role=index_only`；source_copy 可以保留源 PTS 以避免改坏码流，但真实时间与标注对齐仍以 frames 为准。未知真实时间保留 null。缺失某帧组件时保留索引位置并使用该组件的无效占位／valid 标识，不删帧；不能以重复相邻图像冒充已知观测。
+
+### 3.2 depth.mkv 与 depth_valid.mkv
+
+深度语义仍是 `depth/z_float32/v1`：统一读取结果 `[T,H,W] float32`，米制相机 Z 分量，`depth_type=z`。有效深度有限且大于 0，无效位置为 NaN。`depth_origin=measured/rendered/unknown` 必填，来源不明时 unknown。默认与 RGB 共用像素网格及相机参考系，不处理未注册 RGB-D。射线距离必须依据源定义转换成 z，不能只改声明。
+
+#### 3.2.1 float32 的可逆视频编码
+
+采用 `mkv/depth_float32_bits/v1`：**不是把深度量化成 uint16**，而是将规范化后每个 IEEE-754 float32 的完整 32 位拆成两个 uint16，使用 FFV1 gray16le 保存。视频物理尺寸为 `[2W,H]`：每行前 W 列存原 float32 位串的低 16 位，后 W 列存高 16 位。读取时先合并为 uint32 位串，再按 float32 重新解释，不能数值 cast 成 float32。
+
+```text
+u = reinterpret_uint32(depth_float32)
+encoded[:, :, :W] = uint16(u & 65535)
+encoded[:, :, W:] = uint16(u >> 16)
+u_restored = uint32(low) | (uint32(high) << 16)
+depth_float32 = reinterpret_float32(u_restored)
+```
+
+统一采用 little-endian 原始字节接口。`camera.image_size` 始终是逻辑 RGB 尺寸 `[W,H]`，不能改成编���视频的 2W；`storage.encoded_size=[2W,H]`。包括 NaN 在内的 float32 位串必须全帧完全恢复，不允许改成 float16、整数毫米、归一化灰度或 RGB 伪彩色。这里的无损验收基准是完成既定米制／坐标转换后的标准 float32 数组，不声称消除 float64→float32 等原约定转换本身的舍入。
+
+#### 3.2.2 逐像素有效性
+
+`depth_valid.mkv` 使用 `mkv/bool_ffv1/v1`，FFV1 gray8（FFmpeg pixel_format=`gray`），物理尺寸 `[W,H]`。像素只能为 0 或 1，统一解码为 `[T,H,W] bool`，逐像素含义不变。这样不再把庞大的 bool 数组保存为未压缩 `.pt`；标注的帧级／手级 valid 仍保留原有小数组。
+
+登记示例（W、H 以下取 640、480；decoder/encoder_parameters 的实际版本由转换器填写）：
+
+```json
+{
+  "available": true,
+  "schema_id": "depth/z_float32/v1",
+  "data_ref": "observation/depth.mkv",
+  "axes": ["T", "height", "width"],
+  "valid_ref": "observation/depth_valid.mkv",
+  "valid_axes": ["T", "height", "width"],
+  "unit": "m",
+  "depth_type": "z",
+  "depth_origin": "measured",
+  "invalid_value": "NaN",
+  "storage": {
+    "profile": "mkv/depth_float32_bits/v1",
+    "codec": "ffv1",
+    "pixel_format": "gray16le",
+    "encoded_size": [1280, 480],
+    "source_lossy": false,
+    "decoder": {"name": "ffmpeg", "version": "填写实际版本"},
+    "encoder_parameters": {"name": "ffv1", "level": 3, "version": "填写实际版本"}
+  },
+  "valid_storage": {
+    "profile": "mkv/bool_ffv1/v1",
+    "codec": "ffv1",
+    "pixel_format": "gray",
+    "encoded_size": [640, 480],
+    "source_lossy": false,
+    "decoder": {"name": "ffmpeg", "version": "填写实际版本"},
+    "encoder_parameters": {"name": "ffv1", "version": "填写实际版本"}
+  },
+  "provenance": {"kind": "format_conversion", "method": "源深度转米制 z float32；逐位打包为 FFV1"},
+  "source_locator": {"file": "raw/data/depth.zip", "member": "depth/0001.png"}
+}
+```
+
+深度和有效性视频都必须逐帧解码验收：float32 位串相同、bool 相同、T 相同，并检查 valid=true 的正有限值和 valid=false 的 NaN。读取器必须按 profile 还原，不能把 depth.mkv 的编码像素直接当深度值。
+
+## 4. camera 相机、帧索引与标定
+
+### 4.1 frames.jsonl：索引、时间与对应关系
+
+`camera/frames.jsonl` 每行对应统一帧号 `frame_index=0..T-1`，是所有组件的唯一行索引。至少包含 `frame_index`、`timestamp_ns`、`clock_domain`、`source_locator`；原始帧号/文件名保存在 `source_frame_id`，不能被新帧号替代。每行还可有 `annotation_matches`，按组件键保存 `source_frame_id`、`source_timestamp_ns`、`clock_domain`、`match_method` 和 `delta_ns`；方法为 exact/index_map/nearest/interpolated，索引映射无时间依据时 delta_ns=null。nearest 必须记录允许误差；interpolated 必须记录两端源标识和权重。delta_ns 仅在同一时间域中计算为源标注时间减图像时间。多相机共享 `sequence_id`；已知同步关系必须用 `sync_id` 或明确的源帧/时间映射表达，不能仅凭相同数组索引认定同步。
+
+每个视图必须提供此文件。源时间使用整数纳秒及 `clock_domain`，未知写 JSON `null`；不同时间域不能直接比较。逐帧 split 可以覆盖 metainfo 的视图默认划分，并保留来源，见 2.4。
+
+### 4.2 坐标系与标定通则
+
+| 项目 | 统一约定 |
+|---|---|
+| 相机坐标 | 右手系，X 向右、Y 向下、Z 向前，长度单位米 |
+| 齐次变换 | 列向量，`p_target = T_target_from_source @ p_source` |
+| 图像坐标 | `(u,v)`；左上像素中心为 `(0,0)`，u 向右、v 向下，单位 pixel |
+| 固定标定 | 本版展开为 T 份，同一 schema 不混用静态与动态形状 |
+| 分辨率或模型变化 | 分开存储为视图／片段，不在同一组件中混装 |
+| 未知标定 | 相机内外参允许缺省，不填单位阵冒充已知标定 |
+
+### 4.3 intrinsic.pt 与畸变参数
+
+| model / schema_id | intrinsic.pt 的固定结构 |
+|---|---|
+| pinhole / camera/pinhole/v1 | `[T,3,3]`，标准 K，最后一行为 `[0,0,1]`；限无畸变或已校正图像 |
+| fisheye624 / camera/fisheye624/v1 | `[T,15]`，`[f,cx,cy,k0,k1,k2,k3,k4,k5,p0,p1,s0,s1,s2,s3]`，采用 Project Aria Fisheye624 投影定义 |
+| opencv_fisheye4 / camera/opencv_fisheye4/v1 | `intrinsic.pt [T,3,3]` 保存 K；同组件 `distortion_ref` 指向 `[T,4]`，顺序 `[k1,k2,k3,k4]`，使用 OpenCV fisheye 等距角度多项式；已由 ReInterHand 实际原始相机参数验证 |
+| rational8 / camera/rational8/v1 | `intrinsic.pt [T,3,3]` 保存 K；同组件必需 `distortion_ref` 指向 `[T,8]`，顺序 `[k1,k2,p1,p2,k3,k4,k5,k6]` |
+| unknown / null | 不提供可用 intrinsic，不声称可以投影 |
+
+有畸变的其他模型必须注册新 schema，固定参数名、顺序和投影公式；不能塞进针孔 K 后遗失畸变项。`metainfo.camera.schema_id` 必须与 intrinsic 组件一致。同一模型的别名不可隐式改变参数布局。
+
+`opencv_fisheye4`：对前方点令 `x=X/Z, y=Y/Z, r=sqrt(x²+y²), theta=atan(r)`，`theta_d=theta*(1+k1*theta²+k2*theta⁴+k3*theta⁶+k4*theta⁸)`；`u=fx*x*theta_d/r+cx, v=fy*y*theta_d/r+cy`。光轴 r=0 时使用连续极限 `theta_d/r=1`。四系数不能按普通径向畸变解释，也不能补零冒充 Fisheye624。
+
+rational8 对归一化坐标 x=X/Z、y=Y/Z，令 r²=x²+y²，径向项为 `(1+k1*r²+k2*r⁴+k3*r⁶)/(1+k4*r²+k5*r⁴+k6*r⁶)`；再加 p1/p2 切向项并经 K 得到像素。`distortion_ref` 与 intrinsic 共用 `[T]` valid，保存到 camera/distortion.pt。不得把这种畸变三维坐标当作真实相机系 xyz 保存。
+
+内参有效性为 `intrinsic_valid.pt [T] bool`；有畸变时使用对应 `distortion_ref`。同一模型的参数名和顺序固定。
+
+### 4.4 extrinsic.pt 与 extrinsic_valid.pt
+
+`extrinsic.pt` 为 `[T,4,4]`，schema `transform/se3/v1`，方向固定 `T_camera_from_world`，有效性 `[T]`。世界坐标含义及源坐标转换记录在 provenance 中；只有相机坐标标注不要求虚构世界坐标。旋转块须正交且 determinant≈1。
+
+## 5. annotation 标注数据
+
+### 5.1 标注通则：手槽、valid 与 visibility
+
+手槽固定为 0=left、1=right，指解剖学左右，不按画面位置或可见性重排。本阶段只处理左右手两槽，不处理更多手。实体引用使用 `hand_left`、`hand_right`；手槽不证明跨采集片段的个人身份。
+
+#### 5.1.1 valid：标注是否可用于监督
+
+标注的 `valid=true` 表示：有对应实际标注、通过本 schema 数值检查，且通过来源明确提供并适用于该组件的有效性/QA 条件。`valid=false` 可由缺标注、无法建立帧对应、源无效占位或官方 QA 不通过导致；不等于画面没有手或手不可见。各组件独立判断，MANO 按 `[T,2]` 标记左右手，关键点按 `[T,2,K]` 标记。
+
+**2026-09-20 将标注 valid 从“仅表示存在”修订为“可用于监督”，字段形状不变。** 公式为 `source_annotation_present AND numerical_checks_pass AND applicable_official_QA_pass`。没有官方 QA 时省略最后一项，不伪造 QA；不能把未知当成已通过已存在的 QA。适配器在组件 `valid_policy` 中记录具体规则、来源、聚合/广播作用域。缺失官方必需 QA 的记录须明确处理为未知或暂停验收，不能静默通过。无效浮点项仍填 NaN，原始数据保留在 raw；被排除原值可用于 doc 中明确标识的诊断渲染，不能冒充 shared 有效监督。
+
+本地筛选须依据明确的规则，并在 `valid_policy.local_excluded_frame_indices`、排除原因和正式报告中记录。单个可疑投影作为问题记录，不直接硬编码排除该帧。已确认的曝光异常须明确作用范围，不能把一个序列的“前两帧有问题”套到所有序列。RGB 编码完好与几何监督可用是两件事，允许保留原图及帧索引而屏蔽对应标注；未发现问题不等于完成全部人工审核，试点待确认时不能作为已验收发布使用。
+
+源字段必须按官方语义映射，不能直接按名字复制：
+
+| 来源 | 官方含义 | 映射原则 |
+|---|---|---|
+| [H2O](https://github.com/taeinkwon/h2odataset) 的手标注首位 | 0 未标注、1 已标注 | 可作为对应手标注存在性的依据，不推断未标注原因 |
+| [HOT3D](https://github.com/facebookresearch/hot3d#using-mask-files) 的 pose_available、visible、mask_qa_pass | 分别表达姿态存在、可见性、对画面中可见手物位姿的人工 QA | 逐手/物体记录决定存在性，再 AND 当前相机当前帧 QA；QA 是整帧聚合判定，保守排除该帧全部手物几何监督，不声称每个实体均有错误；源可见性基于位姿推导时，其自身 valid 同样受 QA 约束 |
+| [Dex-YCB](https://github.com/NVlabs/dex-ycb-toolkit#loading-dataset-and-visualizing-samples) 的全零 pose_m、全 -1 joints | 不可见的手或缺标注共用占位表示 | 对应组件 valid=false；不能从该值判定 visibility=false，也不能声称原因是动捕缺失 |
+| [ARCTIC](https://github.com/zc-alexfan/arctic/blob/master/docs/data/data_doc.md) 的 is_valid/left_valid/right_valid | 是否有效用于官方评估 | 核实每项筛选依据；不把可见性/评估选择直接等同 QA。本次原始 mano.npy 不含这些派生评估标记，按原记录与数值检查生成 valid，并声明没有额外官方 QA 输入 |
+
+源 valid=false 若代表评估筛选或其他条件，应检查实际标注和源约定后映射；不能一律清空坐标。反之，占位零或 -1 只有在源官方明确规定时才判为缺失，不泛化成所有数据的判断规则。
+
+`valid=true` 的标注应通过其 schema 的数值与形状检查；检查失败必须报告或修复，不能静默隐藏。QA 不通过应报告排除数量与原因，并保留可追溯信息；不能把这类无效称为缺标注。RGB、深度等观测有效性仍按各自 schema；手物 QA 不自动否定 RGB、静态相机内参或物体资产。相机外参是否过滤须依据其自身来源规则；HOT3D 本次保留源外参用于溯源和诊断，不能用其存在性证明 QA 失败帧的几何监督正确。
+
+#### 5.1.2 visibility：可见性属性
+
+附加质量属性只保留 `visibility`，存放在对应模态或标注集内，不设 quality 目录。同一份可见性仅存一次；uv 与 xyz 共用时引用同一个文件。
+
+visibility 通过所属组件 attributes 登记 data_ref、axes、dtype、visibility_type、meaning、provenance、source_locator；未知值通过属性 valid_ref 标识，全已知可声明 valid=true。比例与布尔值不相互强转，也不按任意阈值二值化。没有 MANO 时，整手可见性挂在 keypoints 组件，使用独立的 whole_hand_visibility.pt，明确 meaning=whole_hand，不与逐关键点可见性混用。
+
+`valid` 回答“这项标注能否用于监督”，`visibility` 回答“在当前图像中是否可见（或可见多少）”。不可见的手或关键点仍可有有效标注；不能因 visibility=0 就清空坐标。源没有 visibility 时缺省或标为未知，不由 valid 推断。
+
+| 情况 | 手标注 valid | visibility |
+|---|---|---|
+| RGB 已开始录制，动捕尚未开始，没有其他对应手标注 | false | 以独立源可见性标注为准；没有则未知 |
+| 手被遮挡，但源有标注且通过适用有效性检查 | true | 若源声明不可见，则 false 或源可见比例 |
+| 手可见且有对应标注，通过适用 QA | true | 若源有此信息，则 true 或源可见比例 |
+| 手可见，但该帧漏标或动捕中断 | false | 可以为 true，但必须有独立来源依据 |
+| 有手部参数，但官方 QA 明确不通过 | false | 不据此断言不可见；源可见比例若基于不可靠位姿，其属性 valid 也为 false |
+
+visibility 自己的 valid_ref 表示该可见性标注是否可用，不复用 MANO 或关键点坐标的 valid_ref；明确记录源存在性及适用的 QA 条件。上述例子不要求凭图像自动生成可见性。
+
+不设 quality 组件或目录，不另存拟合误差、曝光、截断比例等通用质量数组。适用的官方 QA 合并进对应 valid，在 `valid_policy` 记录来源与规则；正式校验报告保留原始 QA 时间区间及排除统计。原始 QA 文件仍在 raw，官方 split 保留。
+
+### 5.2 mano：参数与整手可见性
+
+MANO schema `mano/axis_angle61/v1`：`motion.pt [T,2,61]`，顺序为完整 16 关节 axis-angle 48、shape betas 10、全局平移 3。姿态使用弧度，平移米，位于当前相机系。有效性 `[T,2]`；缺少一侧整槽 NaN。PCA 必须先按对应模型展开，不能将 PCA 系数直接填入 axis-angle。
+
+`model_profile` 必须固定 MANO 版本、`flat_hand_mean=true`、左手 shapedirs 修正状态。平移表示模型输出顶点所加的全局平移，不是某个腕关节的坐标；源语义不同须转换。shape 无量纲。模型权重不作为共享数据附带上传。
+
+`mano/visibility.pt [T,2]` 保存源整手可见比例时使用 float32 [0,1]，`visibility_type=ratio`；只有实际采用 0–100 的百分比才除以100，不能只凭表头判断。HOT3D 的 `visibility_ratio[%]` 实值已经是0–1，官方读取器原样读取，必须保留原值。通过 MANO 组件 attributes 登记，使用独立有效性，不复用 motion_valid。
+
+手部共享表示仅保留 MANO 参数与选定关键点，不发布独立手表面几何。需要渲染或接触计算时由 MANO 参数生成，几何引用使用固定 MANO 模型配置与顶点顺序；不影响 object 下的物体模型和材质资产。
+
+### 5.3 keypoints：二维点、三维点与逐点可见性
+
+关键点独立于 MANO 参数存在；没有 motion 也可有关键点。`uv.pt [T,2,K,2]` 与 `xyz.pt [T,2,K,3]`，有效性 `[T,2,K]`，分别采用 `keypoints/uv/v1` 和 `keypoints/xyz/v1`。K 由 `keypoint_schema` 固定，不能在同一数组中逐帧变化；同体系统一顺序。数值使用像素坐标或米制相机系。
+
+| keypoint_schema | K 与固定索引 |
+|---|---|
+| mano21/v1 | 21；wrist 后依次 thumb/index/middle/ring/little，每指由近端至指尖 |
+| rhd21/v1 | 21；保持 wrist，然后五指由近端至指尖；原始每指 tip→palm 反序。只统一顺序，不宣称解剖学位置等价于 MANO |
+
+具体名称与源索引映射见 `schema.json`。当前只登记 MANO21 与 RHD21；不登记 MediaPipe、ReInterHand capture21 或 fit24 中间关键点。
+
+每个发布中的每个视图只提供一套标准手关键点，直接放在 keypoints 下，不设 annotation_set_id 字段或目录。uv 与 xyz 是这套关键点的二维与三维表示，不是两套标注。provenance 分别记录二者来自原始标注还是计算结果；不要求已有 2D 必须由当前 xyz 重新投影覆盖。
+
+ReInterHand 的 Original keypoints���Original fits keypoints 及带前臂关键点不纳入 shared；如需手关键点，从选定 MANO 参数生成 MANO21 并记录模型/指尖回归约定。其他数据集默认使用选定的官方关键点，不额外生成平行的 MANO 派生集合。后续主动更换生成方法或结果时发布新的 dataset_version，不在同一版本内增设方法分支。
+
+manual/projection/fitting 只记录在 provenance，不作为目录或类型分支。不得通过坐标为零、是否出画或 visibility 判断标注是否存在。派生标注仅在实际生成并通过数值检查后声明 valid=true；没有生成的项为 false，不伪造坐标。
+
+`keypoints/visibility.pt [T,2,K]` 保存源逐点可见性，布尔表示使用 `visibility_type=boolean`。uv 与 xyz 共用时引用同一份文件。整手比例属性没有 MANO 可挂载时使用 `whole_hand_visibility.pt [T,2]`，`meaning=whole_hand`；它与逐点可见性分开，通用登记规则见 5.1。
+
+不使用 annotation_set_id；ReInterHand 中间关键点集合不进入 shared，raw 保留来源文件。
+
+### 5.4 object：身份、资产、位姿与几何
+
+#### 5.4.1 metainfo.json：物体身份与跟踪作用域
+
+手用 `hand_left`、`hand_right` 及槽位 0、1 表示，不再另存 entities.json。物体身份登记在 `annotation/object/<object_id>/metainfo.json`，必填 `object_id`、`identity_scope`、`scope_id`、`source_locator`；可含 `category_id`、`source_object_id`、`mesh_ref`、`has_model`、部件引用。即使只有分割、没有 pose/mesh，也可只有这份物体元信息。
+
+`identity_scope` 为 frame/subsequence/sequence，`scope_id` 指定具体作用域；跨相机共享身份只在已有源对应证据时使用。VISOR 按官方 subsequence 与实体名关联时记录 `association_basis=official_subsequence_entity_name`，不能声称这是全视频物理实例跟踪。无需与 object_id 一一对应的标准 track_id；官方独立轨迹标识存在时保留为 source_track_id，并声明作用域。手槽不证明跨采集片段的个人身份。
+
+#### 5.4.2 assets：网格、材质与纹理
+
+资产属于物体，统一存放在 `annotation/object/<object_id>/` 内，可用 `assets/` 子目录组织网格、材质、纹理和部件资产。序列层不设共享 assets。所有引用采用视图根目录为基准；其中物体资产组件的 `data_ref` 与部件的 `mesh_ref` 采用相对于当前视图目录的 POSIX 路径，例如 `annotation/object/cup_01/assets/cup.obj`，且必须指向所属物体目录内的资产。OBJ 内部的材质、纹理引用遵循文件格式自身的相对路径规则，依赖文件一并保留。不同相机视图允许各自保存物体资产，不要求跨视图去重；下载物体时包含其资产依赖。
+
+网格 schema 为 `mesh/obj/v1`，顶点米制，静态有效性可直接声明标量 `valid`，或通过 `valid_ref` 指向标量 bool Tensor；不按 T 重复静态资产。由物体／部件通过引用关联，不仅凭文件名猜测。
+
+#### 5.4.3 pose.pt、pose_valid.pt 与 visibility.pt
+
+刚体 schema 为 `object/rigid/v1`，`pose.pt [T,4,4]` 固定为 `T_camera_from_object`，平移米制，有效性 `[T]`。物体坐标原点、轴向必须与 mesh 一致；旋转块为正交矩阵且 determinant≈1。
+
+`object/<id>/visibility.pt [T]` 保存源物体可见比例，float32 [0,1]，`visibility_type=ratio`。通过所属物体组件 attributes 登记，独立表达其有效性。
+
+#### 5.4.4 articulation.json、部件位姿与 joint_state.pt
+
+关节物体：schema `object/articulated/v1`，`articulation.json` 登记 `parts` 与 `joints`。每个 part 有 `part_id`、`parent_id`（根为 null）、`has_model`、`mesh_ref`；has_model=false 时 mesh_ref=null，结构节点允许没有网格。父链不得成环。每个 joint 有唯一 `joint_id`、`parent_part`、`child_part`、`type`；fixed 单位 null、revolute 弧度、prismatic 米。有源限位时保存 `limits:[lower,upper]`；没有时 null，不伪造上下限。部件姿态统一为 `T_camera_from_part [T,4,4]`，不与父局部变换混装。
+
+若提供 `joint_state.pt [T,J]`，必须登记固定 joint_order、轴在父部件系的表达、零位变换与正方向，valid 为 `[T,J]`；缺少这些运动学定义时只发布部件位姿与已有来源信息，不伪造可驱动的关节模型。关节值与部件位姿同时存在时需验证一致性。
+
+部件层级应声明语义：纯语义包含树允许 `joints=[]`，不将包含关系推断为机械关节。关节状态 schema 为 `object/joint_state/v1`；转动用弧度、移动用米，混合类型按 joint_order 对应的关节定义解释。
+
+#### 5.4.5 dimensions、几何关键点与顶点部件标签
+
+`dimensions.pt [T,3]` 采用 `object/dimensions/v1`，有效性为 `[T]`。
+
+物体/部件 `dimensions` 为 `[length,width,height]` 米，轴顺序与该 mesh 的局部坐标关联，登记 `dimensions_semantics` 和来源。HOI4D dimensions 与 mesh 的具体尺度关���未验证前标为 source_unspecified，保留源值并暂停依赖该关系的几何验收，不能默认为待施加缩放。需要施加缩放时明确 scale_applied_to_mesh，禁止重复应用。
+
+源物体关键点放 `object/<id>/keypoints/xyz.pt [T,K,3]`（相机系）或 `template_xyz.pt [K,3]`（物体系），schema 分别为 object_keypoints/camera/v1 和 object_keypoints/template/v1。明确 keypoint_schema、keypoint_names、单位及有效性；模板点配合 pose 可投影，无须重复生成全部帧。H2O 中心/角点/棱中点，以及 ARCTIC 部件点分别登记具体源顺序，不套用手的 21 点 schema。每个发布选择一套源几何点并记录选择，不另建方法分支。
+
+`vertex_part_ids.pt [V] int64` 绑定 `mesh_ref` 与 topology_id，登记整数到 part_id 的映射；未知用 -1。ARCTIC 不同拓扑的资产分别绑定，不能共用未经转换的顶点标签。部件层级中 is_instance/has_model 等源属性保留，几何文件仍全部归 object。
+
+### 5.5 segment：分割类别、编码与覆盖范围
+
+每个发布选择一套任务使用的分割表示，不建立方法／标注集分支。没有分割就不创建 segment 目录，不为其他模态创建空的实体表。
+
+| schema_id | 文件与数值语义 |
+|---|---|
+| segment/uint16_labels/v1 | mask.mkv；整数区域编号，通过 instances.jsonl 解释 |
+| segment/instance_polygons/v1 | polygons.jsonl；实例多边形，可重叠；当前不支持孔洞拓扑 |
+| segment/foreground_intensity/v1 | mask.mkv；0–255 前景强度，不是区域编号或经过校准的概率 |
+
+#### 5.5.1 uint16 标签图与 instances.jsonl
+
+组件声明 `segmentation_type=semantic/instance/part`；同一组件固定一种类型。`mask.mkv` 解码为 `[T,H,W] uint16`，schema `segment/uint16_labels/v1`，使用 `mkv/uint16_ffv1/v1`，FFV1 gray16le 无损；只有所有区域编码均 ≤255 时允许 gray8（pixel_format=gray），读取后转 uint16，数值不变。禁止调色板和有损编码。有效性 `[T]`，表示该帧有可用分割标注。数值 0 固定为 unassigned，65535 固定为 ignore，1–65534 为区域编码，不能直接等同 entity_id。
+
+`instances.jsonl` 每帧一行，包含 `frame_index` 与 `labels`。每条标签包含 `mask_value`、`category_id`、`entity_id`、`part_id`；无意义或未知字段为 null。semantic 允许 entity_id=null；instance 必须引用 hand_left/hand_right 或登记的 object_id；part 还须关联登记部件。源实例 ID 和其他属性分别保存在 `source_instance_id`、`source_attributes`。mask 中每个非保留编码必须有且仅有一个映射。
+
+FreiHAND 的试点按本任务需要，统一到手／背景类别，保留每个原生区域编码；不要求给原生细分区域猜测手指名称。需要细部件监督时，尚未核实的部件名称必须保持未知，不能因粗粒度手类别已核实便声称部件语义也已统一。
+
+#### 5.5.2 重叠实例多边形
+
+每发布选择一套任务使用的分割表示，不建立方法/标注集分支。VISOR 的实际试点存在重叠实例多边形，单层标签图不能无损表达。对此补充 `segment/instance_polygons/v1`：`segment/polygons.jsonl` 每帧包含 `frame_index` 和 `instances`，每实例包含 `mask_value` 与 `polygons`（列表，每个多边形为源图像像素坐标顶点序列，保留原始精度）。身份和类别仍由同一 `instances.jsonl` 映射，有效性仍为 `[T]`，通过 schema 区分物理编码。允许多实例重叠，不采用后画覆盖前画。消费者按需栅格化为独立实例二值 mask；不能声称合并的单层 mask 无损。
+
+#### 5.5.3 灰度前景强度
+
+ReInterHand 的官方渲染 mask 为双手合并的灰度前景掩码，实测存在 0–255 的中间值，不是左右手实例编号。登记 `segment/foreground_intensity/v1`：仍存 `segment/mask.mkv`，解码为 `[T,H,W] uint16`，使用 `mkv/uint16_ffv1/v1`，此类数据优先编码为 FFV1 gray8（pixel_format=gray），读取后转 uint16。有效值范围 0–255，归一化值为 `float32(value)/255`；0 为背景端点、255 为前景端点。组件声明 `foreground_category=hand`、`entity_id=null` 和双手合并语义，不使用区域编号映射。这里保留原始渲染 mask 强度，不把它称为经过校准的概率。若任务需要二值 mask，阈值化属于任务层派生操作，记录阈值；共享层不丢弃中间灰度。不同 schema 的数值含义不同，不能将该文件按整数类别图解码。
+
+FreiHAND 训练集的 JPEG mask 使用 `segment/foreground_intensity/v1`，逐像素保留 JPEG 解码后的灰度，`entity_id=hand_right`。该 schema 不限定双手合并：单手或合并范围由 `entity_id` 与 `coverage` 明确声明。评估集整数区域图仍用 `segment/uint16_labels/v1`，两者不能仅凭文件名使用同一种解码语义。
+
+#### 5.5.4 coverage 与有效性
+
+`coverage.kind=full/selected_entities/partial/unknown`。full 指声明���标注范围完整；selected_entities 还应列出目标范围。无论哪种，0 本身不自动成为背景；背景要有明确类别映射，未标注区域不能用于构造负样本。保留源逐类/逐实例 exhaustive 信息，未知不可改写为完整。
+
+三种表示的帧级有效性均为 `[T]`，表示该帧是否提供此分割标注；对应 valid_ref 在组件中登记，仍用小型 bool `.pt` 数组。栅格 mask 必须登记 storage，格式见 3.1.2，所有帧的整数编码或强度逐值完全相同。编码语义由 schema_id 决定，读取器不能仅依据 mask.mkv 文件名选择解码方式。
+
+### 5.6 contact：接触、抓取、区域与距离
+
+#### 5.6.1 relations.jsonl 与 relations_valid.pt
+
+`annotation/contact/relations.jsonl`，schema contact/relations/v1，每帧一行含 frame_index、relations。每条记录含 relation_type（contact/grasp）、subject_id（手槽或登记实体）、object_id、status、source_locator、provenance。status 固定为 positive/negative/unknown/target_unannotated：positive 必须有可解析目标，negative 表示源明确否定该关系，unknown 为不确定，target_unannotated 为确有接触但目标未标注。非 positive 的 object_id 可 null，不能用 null 冒充“不接触”。稀疏源无记录的帧不自动补 negative。
+
+VISOR 的对象 mask ID 必须先按同帧 source_instance_id 解析成 object_id；hand-not-in-contact、none-of-the-above、inconclusive 分别映射 negative、target_unannotated、unknown，保留原始字符串。Dex ycb_grasp_ind 通过 ycb_ids 映射到登记物体，以 relation_type=grasp 保存；不得当作逐顶点接触。
+
+relations 组件的 valid_ref 指向 `relations_valid.pt [T] bool`，表示该帧是否有可用源关系标注。有效帧中可以存在 status=unknown 的明确不确定标注；无源标注的帧为 valid=false、relations=[]。组件仍声明 available/provenance/source_locator。
+
+#### 5.6.2 实体对的顶点区域与距离
+
+已发布的接触区域/距离按参与关系的 subject_id 与 object_id 组织，每对实体保留选定的一套结果，以精确 geometry_ref/topology_id 关联到手或物体/部件；不要求每套数据都有。顶点区域 schema contact/vertex_region/v1：bool `[T,V]` 加同形 valid；顶点距离 schema contact/vertex_distance/v1：float32 `[T,V]`、米、同形 valid，声明 source/target geometry_ref、distance_definition（signed/unsigned、测量到点集或表面等明确源定义）。geometry_ref 必须指向已登记 mesh 或由固定 MANO 模型配置确定的拓扑；拓扑/顶点数变化时按拓扑拆分片段。其他源区域表示只有在实际接入并登记 schema 后才可转换，不能随意栅格化宣称等价。
+
+顶点区域／距离已有存储定义，但尚未完成真实输入试点；接入时必须提供源语义与几何验收证据，不因已经登记 schema 就视为通过。
+
+## 附录：任务范围
+
+不强制收录 2D bbox、完整高频动捕、动作程序、身体 SMPL-X、点云或网络特征。范围内的接触、visibility、选定手关键点、物体几何不能因不便处理而静默丢弃。分割采用的物理编码由第 5.5 节决定，存在重叠时不能以单层标签图声称无损。
+
+不设置 entities_ref/segment/entities.json，不要求与 object_id 重复的 track_id。MediaPipe 不在当前关键点定义中；旧版本迁移必须保留可追溯关系，不能直接删表。手部共享表示不含独立 hand_mesh。
+
+schema.json 是普通注册表，不是 JSON Schema 文档或可执行验收器；定义存在不代表真实数据已验证。验收须保留实测范围与未决项。
+
+本存储约定只更新标准，不代表既有 FFV1／depth.pt 试点已迁移。新发布必须显式写 storage 配置；旧产物按其旧定义读取，不能只改文件后缀或版本标识伪装为合规。

EgoPressure/shared-v1.1/doc/media_hashes/p_001_calibration_routine_left__cam-d-rgb.json

@@ -0,0 +1,74 @@
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EgoPressure/shared-v1.1/doc/media_hashes/p_001_calibration_routine_right__cam-d-rgb.json

@@ -0,0 +1,74 @@
+[
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+    "depth_float32_sha256": "0b1bfdcaa77fedaad98952de196c2986f514f30b7ea16103ce60b82487efb843",
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+  }
+]

EgoPressure/shared-v1.1/doc/media_hashes/p_001_draw_word_5x_left__cam-d-rgb.json

@@ -0,0 +1,74 @@
+[
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+  {
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+    "rgb_decoded_sha256": "7c2ba151f3957b83e6f507e7b5b034d351c04e87cfa53e89295147e36e02d6ca",
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EgoPressure/shared-v1.1/doc/media_hashes/p_001_draw_word_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_curled_thumb-down_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_curled_thumb-down_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_curled_thumb-up_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_curled_thumb-up_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_uncurled_thumb-down_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_grasp-edge_uncurled_thumb-down_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_high_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_high_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_low_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_low_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_no-contact_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_no-contact_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_pull_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_pull_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_push_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_push_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_rotate-left_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_rotate-left_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_rotate-right_x5_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_index_press_rotate-right_x5_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch-zoom_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch-zoom_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_high_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_high_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_low_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_low_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_no-contact_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_pinch_thumb-down_no-contact_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_cupped_onebyone_high_3x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_cupped_onebyone_high_3x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_cupped_onebyone_low_3x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_cupped_onebyone_low_3x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_fingers_high_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_fingers_high_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_fingers_low_5x_left__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/media_hashes/p_001_press_fingers_low_5x_right__cam-d-rgb.json

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EgoPressure/shared-v1.1/doc/schema.json

@@ -0,0 +1,1590 @@
+{
+  "schema_version": "hand-warehouse/1.1",
+  "validity_revision": "usable-annotation-2026-09-20",
+  "annotation_validity": {
+    "meaning": "annotation usable for supervision, not merely record presence",
+    "formula": "source_annotation_present AND numerical_checks_pass AND applicable_official_QA_pass AND NOT explicitly_reviewed_local_exclusion",
+    "without_official_qa": "omit QA term; declare source rules; do not fabricate QA",
+    "policy_field": "components.<name>.valid_policy",
+    "visibility_is_independent": true,
+    "invalid_float_value": "NaN",
+    "hot3d": "broadcast per-camera frame manual QA conservatively to hand/object labels and pose-derived visibility; retain RGB and source calibration; keep native QA in raw and review report",
+    "hot3d_visibility": "native visibility_ratio[%] already ranges from 0 to 1; do not divide by 100"
+  },
+  "hand_slots": [
+    "left",
+    "right"
+  ],
+  "view_metadata": {
+    "required_fields": [
+      "schema_version",
+      "dataset_id",
+      "release_id",
+      "sequence_id",
+      "camera_id",
+      "sample_type",
+      "num_frames",
+      "hand_slots",
+      "sampling",
+      "camera",
+      "components",
+      "split",
+      "view_type"
+    ],
+    "view_type_values": [
+      "ego",
+      "exo",
+      "unknown"
+    ],
+    "view_type_policy": "required per camera view; use ego or exo whenever the source data or capture setup establishes the viewpoint; use unknown only when no trustworthy source determines it; never omit or guess",
+    "schema_version": "hand-warehouse/1.1",
+    "release_id": "shared-v1.1"
+  },
+  "keypoints": {
+    "mano21/v1": {
+      "count": 21,
+      "names": [
+        "wrist",
+        "thumb_1",
+        "thumb_2",
+        "thumb_3",
+        "thumb_4",
+        "index_1",
+        "index_2",
+        "index_3",
+        "index_4",
+        "middle_1",
+        "middle_2",
+        "middle_3",
+        "middle_4",
+        "ring_1",
+        "ring_2",
+        "ring_3",
+        "ring_4",
+        "little_1",
+        "little_2",
+        "little_3",
+        "little_4"
+      ],
+      "source_index_map": null,
+      "note": "adapter maps official MANO joint and fingertip convention"
+    },
+    "rhd21/v1": {
+      "count": 21,
+      "names": [
+        "wrist",
+        "thumb_1",
+        "thumb_2",
+        "thumb_3",
+        "thumb_4",
+        "index_1",
+        "index_2",
+        "index_3",
+        "index_4",
+        "middle_1",
+        "middle_2",
+        "middle_3",
+        "middle_4",
+        "ring_1",
+        "ring_2",
+        "ring_3",
+        "ring_4",
+        "little_1",
+        "little_2",
+        "little_3",
+        "little_4"
+      ],
+      "source_index_map_per_hand": [
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+        4,
+        3,
+        2,
+        1,
+        8,
+        7,
+        6,
+        5,
+        12,
+        11,
+        10,
+        9,
+        16,
+        15,
+        14,
+        13,
+        20,
+        19,
+        18,
+        17
+      ]
+    }
+  },
+  "camera": {
+    "opencv_fisheye4": {
+      "K": [
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+        3
+      ],
+      "distortion": [
+        "k1",
+        "k2",
+        "k3",
+        "k4"
+      ],
+      "projection": "theta=atan(r); theta_d=theta*(1+k1*theta^2+k2*theta^4+k3*theta^6+k4*theta^8); source ReInterHand"
+    },
+    "pinhole": {
+      "K": [
+        3,
+        3
+      ]
+    },
+    "fisheye624": {
+      "parameters": [
+        "f",
+        "cx",
+        "cy",
+        "k0",
+        "k1",
+        "k2",
+        "k3",
+        "k4",
+        "k5",
+        "p0",
+        "p1",
+        "s0",
+        "s1",
+        "s2",
+        "s3"
+      ]
+    },
+    "rational8": {
+      "K": [
+        3,
+        3
+      ],
+      "distortion": [
+        "k1",
+        "k2",
+        "p1",
+        "p2",
+        "k3",
+        "k4",
+        "k5",
+        "k6"
+      ]
+    }
+  },
+  "segmentation": {
+    "segment/uint16_labels/v1": {
+      "storage": "mask.mkv",
+      "dtype": "uint16",
+      "mapping": "instances.jsonl",
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
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+        "coverage",
+        "mapping_ref",
+        "storage"
+      ],
+      "shape": [
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+        "H",
+        "W"
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+      "reserved_codes": {
+        "0": "unassigned",
+        "65535": "ignore"
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+      "region_codes": [
+        1,
+        65534
+      ],
+      "allowed_storage_profiles": [
+        "mkv/uint16_ffv1/v1"
+      ]
+    },
+    "segment/instance_polygons/v1": {
+      "storage": "polygons.jsonl",
+      "mapping": "instances.jsonl",
+      "frame_keys": [
+        "frame_index",
+        "instances"
+      ],
+      "instance_keys": [
+        "mask_value",
+        "polygons"
+      ],
+      "coordinate_unit": "pixel",
+      "overlap_allowed": true,
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
+        "segmentation_type",
+        "coverage",
+        "mapping_ref"
+      ],
+      "polygon_shape": [
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+        2
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+      "holes_supported": false
+    },
+    "segment/foreground_intensity/v1": {
+      "storage": "mask.mkv",
+      "dtype": "uint16",
+      "value_range": [
+        0,
+        255
+      ],
+      "normalization_scale": 0.00392156862745098,
+      "axes": [
+        "T",
+        "height",
+        "width"
+      ],
+      "meaning": "native hand foreground intensity; individual hand or union declared in metadata; not instance codes or calibrated probability",
+      "zero": "background",
+      "full_scale": "foreground",
+      "mapping": "foreground_category in component metadata",
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
+        "segmentation_type",
+        "coverage",
+        "value_range",
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+        "foreground_category",
+        "entity_id",
+        "storage"
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+      "shape": [
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+        "W"
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+      "allowed_storage_profiles": [
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+  },
+  "note": "Registry for hand-warehouse/1.1. Read CONTRACT.md and MIGRATION.md. This is a declarative registry, not a JSON Schema document or executable validator. Runtime readers/converters/validators still require adaptation.",
+  "components": {
+    "mano/axis_angle61/v1": {
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+      "dtype": "float32",
+      "shape": [
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+      "valid_shape": [
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+      "unit": "m",
+      "angle_unit": "rad",
+      "coordinate_frame": "camera",
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+          48
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+          58
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+      "allowed_storage_profiles": [
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+      "allowed_valid_storage_profiles": [
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+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
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+    },
+    "keypoints/uv/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
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+        2,
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+        2
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+      "valid_shape": [
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+        2,
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+      "unit": "pixel",
+      "required_metadata": [
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+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
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+      "allowed_storage_profiles": [
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+      "allowed_valid_storage_profiles": [
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+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
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+    "keypoints/xyz/v1": {
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+      "valid_storage": "pt",
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+      "dtype": "float32",
+      "shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "valid_shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "unit": "m",
+      "depth_type": "z",
+      "pixel_grid": "current_rgb",
+      "coordinate_frame": "current_rgb_camera",
+      "valid_storage": "mkv",
+      "allowed_storage_profiles": [
+        "mkv/depth_float32_bits/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "mkv/bool_ffv1/v1"
+      ],
+      "required_metadata": [
+        "storage",
+        "valid_storage",
+        "depth_origin"
+      ],
+      "depth_origin_values": [
+        "measured",
+        "rendered",
+        "unknown"
+      ]
+    },
+    "transform/se3/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        4,
+        4
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "unit": "m",
+      "required_metadata": [
+        "convention",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "object/rigid/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        4,
+        4
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "unit": "m",
+      "required_metadata": [
+        "convention",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "camera/pinhole/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        3,
+        3
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ]
+    },
+    "camera/rational8/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        3,
+        3
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage",
+        "distortion_ref",
+        "distortion_key",
+        "distortion_valid_ref",
+        "distortion_valid_key"
+      ]
+    },
+    "camera/opencv_fisheye4/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        3,
+        3
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage",
+        "distortion_ref",
+        "distortion_key",
+        "distortion_valid_ref",
+        "distortion_valid_key"
+      ]
+    },
+    "camera/fisheye624/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        15
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ]
+    },
+    "camera/distortion8/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        8
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ]
+    },
+    "camera/fisheye4_distortion/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        4
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool",
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ]
+    },
+    "object/joint_state/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        "J"
+      ],
+      "valid_shape": [
+        "T",
+        "J"
+      ],
+      "required_metadata": [
+        "joint_order",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "unit_rule": "revolute radians; prismatic metres; mixed types declared per joint",
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "object_keypoints/camera/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        "K",
+        3
+      ],
+      "valid_shape": [
+        "T",
+        "K"
+      ],
+      "unit": "m",
+      "coordinate_frame": "camera",
+      "required_metadata": [
+        "keypoint_schema",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "object/dimensions/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        3
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "unit": "m",
+      "required_metadata": [
+        "dimensions_semantics",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "axis_order": [
+        "length",
+        "width",
+        "height"
+      ],
+      "scale_rule": "do not apply to mesh without source-supported size/scale relation",
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "object_keypoints/template/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "K",
+        3
+      ],
+      "valid_shape": [
+        "K"
+      ],
+      "unit": "m",
+      "coordinate_frame": "object",
+      "static": true,
+      "required_metadata": [
+        "keypoint_schema",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "mesh/obj/v1": {
+      "storage": "obj",
+      "unit": "m",
+      "static": true,
+      "valid_shape": [],
+      "dependencies": "MTL and textures retained under owning object"
+    },
+    "rgb/uint8/v1": {
+      "storage": "mkv",
+      "dtype": "uint8",
+      "shape": [
+        "T",
+        "H",
+        "W",
+        3
+      ],
+      "valid_shape": [
+        "T"
+      ],
+      "color_order": "RGB",
+      "allowed_storage_profiles": [
+        "mkv/mjpeg_copy/v1",
+        "mkv/source_copy/v1",
+        "mkv/h264_rgb_lossless/v1",
+        "mkv/ffv1_rgb/v1"
+      ],
+      "required_metadata": [
+        "storage"
+      ]
+    },
+    "contact/relations/v1": {
+      "storage": "jsonl",
+      "valid_shape": [
+        "T"
+      ],
+      "frame_keys": [
+        "frame_index",
+        "relations"
+      ],
+      "absence_semantics": "no record is not a negative contact annotation"
+    },
+    "contact/vertex_region/v1": {
+      "storage": "pt",
+      "dtype": "bool",
+      "shape": [
+        "T",
+        "V"
+      ],
+      "valid_shape": [
+        "T",
+        "V"
+      ],
+      "required_metadata": [
+        "source_geometry_ref",
+        "target_geometry_ref",
+        "topology_id",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "pilot_status": "defined_not_empirically_validated",
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "contact/vertex_distance/v1": {
+      "storage": "pt",
+      "dtype": "float32",
+      "shape": [
+        "T",
+        "V"
+      ],
+      "valid_shape": [
+        "T",
+        "V"
+      ],
+      "unit": "m",
+      "required_metadata": [
+        "source_geometry_ref",
+        "target_geometry_ref",
+        "topology_id",
+        "distance_definition",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "pilot_status": "defined_not_empirically_validated",
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt",
+      "tensor_container": "dict",
+      "valid_dtype": "bool"
+    },
+    "object/articulated/v1": {
+      "storage": "json",
+      "required_keys": [
+        "parts",
+        "joints"
+      ],
+      "part_keys": [
+        "part_id",
+        "parent_id",
+        "has_model",
+        "mesh_ref"
+      ],
+      "hierarchy_semantics": "declare mechanical articulation or semantic containment; containment alone does not imply joints",
+      "acyclic": true
+    },
+    "segment/uint16_labels/v1": {
+      "storage": "mkv",
+      "dtype": "uint16",
+      "mapping": "instances.jsonl",
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
+        "segmentation_type",
+        "coverage",
+        "mapping_ref",
+        "storage"
+      ],
+      "shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "reserved_codes": {
+        "0": "unassigned",
+        "65535": "ignore"
+      },
+      "region_codes": [
+        1,
+        65534
+      ],
+      "allowed_storage_profiles": [
+        "mkv/uint16_ffv1/v1"
+      ]
+    },
+    "segment/instance_polygons/v1": {
+      "storage": "jsonl",
+      "mapping": "instances.jsonl",
+      "frame_keys": [
+        "frame_index",
+        "instances"
+      ],
+      "instance_keys": [
+        "mask_value",
+        "polygons"
+      ],
+      "coordinate_unit": "pixel",
+      "overlap_allowed": true,
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
+        "segmentation_type",
+        "coverage",
+        "mapping_ref"
+      ],
+      "polygon_shape": [
+        "N",
+        2
+      ],
+      "holes_supported": false
+    },
+    "segment/foreground_intensity/v1": {
+      "storage": "mkv",
+      "dtype": "uint16",
+      "value_range": [
+        0,
+        255
+      ],
+      "normalization_scale": 0.00392156862745098,
+      "axes": [
+        "T",
+        "height",
+        "width"
+      ],
+      "meaning": "native hand foreground intensity; individual hand or union declared in metadata; not instance codes or calibrated probability",
+      "zero": "background",
+      "full_scale": "foreground",
+      "mapping": "foreground_category in component metadata",
+      "valid_shape": [
+        "T"
+      ],
+      "required_metadata": [
+        "segmentation_type",
+        "coverage",
+        "value_range",
+        "normalization_scale",
+        "foreground_category",
+        "entity_id",
+        "storage"
+      ],
+      "shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "allowed_storage_profiles": [
+        "mkv/uint16_ffv1/v1"
+      ]
+    },
+    "object/vertex_part_ids/v1": {
+      "storage": "pt",
+      "tensor_container": "dict",
+      "dtype": "int64",
+      "shape": [
+        "V"
+      ],
+      "valid_shape": [
+        "V"
+      ],
+      "valid_dtype": "bool",
+      "static": true,
+      "unknown_value": -1,
+      "valid_rule": "data != -1; every valid integer resolves in part_id_mapping",
+      "required_metadata": [
+        "mesh_ref",
+        "topology_id",
+        "part_id_mapping",
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "allowed_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "allowed_valid_storage_profiles": [
+        "pt/tensor_bundle/v1"
+      ],
+      "valid_storage": "pt"
+    }
+  },
+  "storage_revision": "lossless-video-2026-09-18",
+  "sampling": {
+    "image": {
+      "single": {
+        "T": 1
+      },
+      "independent": {
+        "T": ">=2",
+        "required_frame_fields": [
+          "sample_id",
+          "source_locator"
+        ],
+        "temporal_relationship": false
+      },
+      "source_fps": null
+    },
+    "video": {
+      "sampling_types": [
+        "dense",
+        "sparse"
+      ]
+    }
+  },
+  "storage_profiles": {
+    "mkv/mjpeg_copy/v1": {
+      "container": "matroska",
+      "codec": "mjpeg",
+      "method": "stream_copy_from_source_jpeg",
+      "logical_dtype": "uint8",
+      "decoded_pixel_format": "rgb24",
+      "validation": [
+        "source_jpeg_packet_sha256_exact",
+        "all_packet_count_order_and_dimensions_exact",
+        "deterministic_decoded_rgb_sample_exact",
+        "pilot_and_final_selected_whole_sequences_decoded_rgb_exact"
+      ],
+      "validation_policy": {
+        "id": "jpeg-packets-all-rgb-sample16/v1",
+        "sample_count_per_view": 16,
+        "short_views": "all_frames_if_T_less_than_16",
+        "fixed_indices": "0,T-1,T//4,T//2,3*T//4, deduplicated",
+        "remaining_indices": "sample without replacement to min(T,16) using Python random.Random(seed)",
+        "seed": "first 8 bytes of SHA256(sequence_id/camera_id/20260920), big-endian integer",
+        "report": "policy, exact selected frame indices, seed, separate packet and pixel coverage",
+        "legacy_all_frame_pixel_proofs": "still accepted; preserve historical evidence"
+      }
+    },
+    "mkv/source_copy/v1": {
+      "container": "matroska",
+      "codec": "source_codec_declared_in_metadata",
+      "method": "stream_copy_only",
+      "logical_dtype": "uint8",
+      "decoded_pixel_format": "rgb24",
+      "validation": [
+        "no_reencoding",
+        "all_decoded_rgb_frames_exact",
+        "presentation_frame_order_exact"
+      ]
+    },
+    "mkv/h264_rgb_lossless/v1": {
+      "container": "matroska",
+      "codec": "h264",
+      "encoder": "libx264rgb",
+      "crf": 0,
+      "decoded_pixel_format": "rgb24",
+      "logical_dtype": "uint8",
+      "gop": "declared_in_encoder_parameters",
+      "validation": [
+        "all_decoded_rgb_frames_exact"
+      ],
+      "forbidden": [
+        "lossy_rate_control",
+        "rgb_to_yuv420_subsampling"
+      ]
+    },
+    "mkv/ffv1_rgb/v1": {
+      "container": "matroska",
+      "codec": "ffv1",
+      "decoded_pixel_format": "rgb24",
+      "logical_dtype": "uint8",
+      "validation": [
+        "all_decoded_rgb_frames_exact"
+      ]
+    },
+    "mkv/depth_float32_bits/v1": {
+      "container": "matroska",
+      "codec": "ffv1",
+      "pixel_format": "gray16le",
+      "logical_dtype": "float32",
+      "logical_shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "encoded_shape": [
+        "T",
+        "H",
+        "2*W"
+      ],
+      "packing": "IEEE754 little-endian float32 bits; low uint16 in first W columns, high uint16 in last W columns",
+      "decode": "reinterpret_float32(uint32(low) | (uint32(high) << 16))",
+      "validation": [
+        "all_float32_bits_exact_including_nan"
+      ]
+    },
+    "mkv/bool_ffv1/v1": {
+      "container": "matroska",
+      "codec": "ffv1",
+      "pixel_format": "gray",
+      "logical_dtype": "bool",
+      "stored_values": [
+        0,
+        1
+      ],
+      "validation": [
+        "all_bool_values_exact"
+      ]
+    },
+    "mkv/uint16_ffv1/v1": {
+      "container": "matroska",
+      "codec": "ffv1",
+      "pixel_formats": [
+        "gray",
+        "gray16le"
+      ],
+      "logical_dtype": "uint16",
+      "gray_condition": "all values <=255; decode by exact uint8-to-uint16 promotion",
+      "validation": [
+        "all_integer_values_exact"
+      ]
+    },
+    "pt/tensor_bundle/v1": {
+      "container": "pytorch_pt",
+      "root_type": "dict",
+      "dictionary_key_type": "nonempty_string",
+      "allowed_value_types": [
+        "dict",
+        "CPU torch.Tensor"
+      ],
+      "tensor_entry": {
+        "required_keys": [
+          "data",
+          "valid"
+        ],
+        "additional_keys": false,
+        "data_type": "CPU torch.Tensor",
+        "valid_type": "CPU torch.Tensor",
+        "valid_dtype": "bool"
+      },
+      "metadata_location": "metainfo.json; do not duplicate strings, paths or custom objects inside bundles",
+      "missing_entry": "omit entire entry; never fabricate absent modalities",
+      "load": {
+        "map_location": "cpu",
+        "weights_only": true
+      },
+      "valid_shape_rule": "Use the specific component or attribute valid_shape; do not infer broadcasting or share validity across independent fields.",
+      "validation": [
+        "registered layout and key resolution",
+        "CPU tensors only",
+        "schema dtype and shape",
+        "independent bool validity",
+        "frame alignment unchanged",
+        "invalid floating positions NaN",
+        "pure migration exact data bytes and validity equality"
+      ],
+      "not_applicable_to": [
+        "media payloads",
+        "media standalone validity tensors",
+        "JSONL standalone validity tensors"
+      ]
+    }
+  },
+  "video_metadata": {
+    "required": [
+      "profile",
+      "codec",
+      "pixel_format",
+      "encoded_size",
+      "decoder",
+      "encoder_parameters",
+      "source_lossy"
+    ],
+    "source_lossy_values": [
+      true,
+      false,
+      "unknown"
+    ],
+    "timebase_role": "index_only",
+    "lossless_reference": "source compressed packets or fixed-decoder source pixels; depth uses normalized standard float32 bits",
+    "selection": "choose smaller complete candidate only after exact roundtrip validation"
+  },
+  "tensor_storage_revision": "tensor-bundle-2026-10-09",
+  "release_layout": {
+    "directory": "shared-v1.1",
+    "release_id": "shared-v1.1",
+    "migration": "Upgrade each dataset in place under shared-v1.0 during maintenance, validate completely, then rename to shared-v1.1; do not retain duplicate published trees. See MIGRATION.md."
+  },
+  "tensor_attributes": {
+    "visibility": {
+      "storage_profile": "pt/tensor_bundle/v1",
+      "allowed_dtypes": [
+        "bool",
+        "float32"
+      ],
+      "visibility_types": [
+        "boolean",
+        "ratio"
+      ],
+      "ratio_range": [
+        0,
+        1
+      ],
+      "scopes": {
+        "whole_hand": {
+          "shape": [
+            "T",
+            2
+          ],
+          "valid_shape": [
+            "T",
+            2
+          ]
+        },
+        "hand_keypoint": {
+          "shape": [
+            "T",
+            2,
+            "K"
+          ],
+          "valid_shape": [
+            "T",
+            2,
+            "K"
+          ]
+        },
+        "object": {
+          "shape": [
+            "T"
+          ],
+          "valid_shape": [
+            "T"
+          ]
+        }
+      },
+      "required_metadata": [
+        "data_ref",
+        "data_key",
+        "axes",
+        "dtype",
+        "visibility_type",
+        "meaning",
+        "valid_ref",
+        "valid_key",
+        "valid_axes",
+        "storage",
+        "valid_storage",
+        "provenance",
+        "source_locator"
+      ],
+      "valid_dtype": "bool",
+      "unknown": "valid=false; ratio data NaN; boolean data is not interpretable without valid",
+      "all_known": "explicit all-true bool tensor; do not infer from pose validity",
+      "note": "No source visibility means omit. Expand explicitly declared all-known scalar validity during migration without changing semantics."
+    }
+  },
+  "tensor_bundles": {
+    "camera": {
+      "path": "camera/camera.pt",
+      "entries": {
+        "intrinsic": {
+          "schema_ids": [
+            "camera/pinhole/v1",
+            "camera/rational8/v1",
+            "camera/opencv_fisheye4/v1",
+            "camera/fisheye624/v1"
+          ]
+        },
+        "extrinsic": {
+          "schema_ids": [
+            "transform/se3/v1"
+          ]
+        },
+        "distortion": {
+          "schema_ids": [
+            "camera/distortion8/v1",
+            "camera/fisheye4_distortion/v1"
+          ]
+        }
+      }
+    },
+    "mano": {
+      "path": "annotation/mano/mano.pt",
+      "entries": {
+        "motion": {
+          "schema_ids": [
+            "mano/axis_angle61/v1"
+          ]
+        },
+        "visibility": {
+          "attribute_id": "visibility",
+          "scope": "whole_hand"
+        }
+      }
+    },
+    "keypoints": {
+      "path": "annotation/keypoints/keypoints.pt",
+      "entries": {
+        "uv": {
+          "schema_ids": [
+            "keypoints/uv/v1"
+          ]
+        },
+        "xyz": {
+          "schema_ids": [
+            "keypoints/xyz/v1"
+          ]
+        },
+        "visibility": {
+          "attribute_id": "visibility",
+          "scope": "hand_keypoint"
+        },
+        "whole_hand_visibility": {
+          "attribute_id": "visibility",
+          "scope": "whole_hand"
+        }
+      }
+    },
+    "object": {
+      "path": "annotation/object/<object_id>/object.pt",
+      "entries": {
+        "pose": {
+          "schema_ids": [
+            "object/rigid/v1"
+          ]
+        },
+        "visibility": {
+          "attribute_id": "visibility",
+          "scope": "object"
+        },
+        "dimensions": {
+          "schema_ids": [
+            "object/dimensions/v1"
+          ]
+        },
+        "joint_state": {
+          "schema_ids": [
+            "object/joint_state/v1"
+          ]
+        },
+        "keypoints/xyz": {
+          "schema_ids": [
+            "object_keypoints/camera/v1"
+          ]
+        },
+        "keypoints/template_xyz": {
+          "schema_ids": [
+            "object_keypoints/template/v1"
+          ]
+        },
+        "parts/<part_id>/pose": {
+          "schema_ids": [
+            "transform/se3/v1"
+          ],
+          "convention": "T_camera_from_part"
+        },
+        "parts/<part_id>/dimensions": {
+          "schema_ids": [
+            "object/dimensions/v1"
+          ]
+        },
+        "parts/<part_id>/keypoints/xyz": {
+          "schema_ids": [
+            "object_keypoints/camera/v1"
+          ]
+        },
+        "parts/<part_id>/keypoints/template_xyz": {
+          "schema_ids": [
+            "object_keypoints/template/v1"
+          ],
+          "coordinate_frame": "part"
+        },
+        "meshes/<mesh_id>/vertex_part_ids": {
+          "schema_ids": [
+            "object/vertex_part_ids/v1"
+          ]
+        }
+      }
+    },
+    "contact_pair": {
+      "path": "annotation/contact/<subject_id>__<object_id>/contact.pt",
+      "entries": {
+        "vertex_region": {
+          "schema_ids": [
+            "contact/vertex_region/v1"
+          ]
+        },
+        "vertex_distance": {
+          "schema_ids": [
+            "contact/vertex_distance/v1"
+          ]
+        }
+      }
+    }
+  },
+  "bundle_layout_rules": {
+    "entry_path_syntax": "Slash-separated dictionary keys in this registry only; serialize references as string arrays. Angle-bracket placeholders resolve to registered IDs, not literal keys.",
+    "entry_leaves": [
+      "data",
+      "valid"
+    ],
+    "additional_entries": false,
+    "all_entries_optional": true,
+    "omit_empty_bundles": true,
+    "identifiers": "object/part/mesh and contact entity IDs must resolve in metadata; reject empty, dot, dot-dot or slash-containing IDs",
+    "per_view": true,
+    "no_cross_object_or_camera_merge": true,
+    "numeric_field_valid_ref_equals_data_ref": true,
+    "attributes_must_be_registered": true
+  },
+  "reference_rules": {
+    "file_paths": {
+      "base": "current camera view root",
+      "format": "relative POSIX",
+      "reject": [
+        "absolute paths",
+        "parent traversal",
+        "external URLs",
+        "unresolved placeholders"
+      ]
+    },
+    "dictionary_keys": {
+      "type": "array",
+      "item_type": "nonempty_string",
+      "min_items": 1,
+      "traversal": "literal nested dictionary lookup; never eval; no automatic flattening",
+      "data_terminal": "data",
+      "valid_terminal": "valid",
+      "target_type": "CPU torch.Tensor"
+    },
+    "bundle_component": {
+      "required": [
+        "data_ref",
+        "data_key",
+        "valid_ref",
+        "valid_key",
+        "storage",
+        "valid_storage"
+      ],
+      "same_file": true,
+      "same_entry_prefix": true,
+      "storage_profile": "pt/tensor_bundle/v1",
+      "valid_storage_profile": "pt/tensor_bundle/v1"
+    },
+    "media_jsonl": {
+      "forbidden": [
+        "data_key",
+        "valid_key"
+      ],
+      "preserve_original_valid_ref": true,
+      "standalone_valid_pt_root": "CPU bool torch.Tensor; not dict",
+      "do_not_label_standalone_valid_as_bundle": true
+    },
+    "camera_distortion": {
+      "models": {
+        "rational8": "camera/distortion8/v1",
+        "opencv_fisheye4": "camera/fisheye4_distortion/v1"
+      },
+      "required": [
+        "distortion_ref",
+        "distortion_key",
+        "distortion_valid_ref",
+        "distortion_valid_key"
+      ],
+      "distortion_ref": "camera/camera.pt",
+      "distortion_key": [
+        "distortion",
+        "data"
+      ],
+      "distortion_valid_ref": "camera/camera.pt",
+      "distortion_valid_key": [
+        "distortion",
+        "valid"
+      ],
+      "valid_equals_intrinsic_valid": true,
+      "models_without_separate_distortion": [
+        "pinhole",
+        "fisheye624"
+      ]
+    },
+    "reader_cache": "Cache bundle by resolved file path; loading different fields must not repeatedly deserialize the file."
+  },
+  "standalone_validity": {
+    "rgb": {
+      "data_ref": "observation/rgb.mkv",
+      "valid_ref": "observation/rgb_valid.pt",
+      "dtype": "bool",
+      "shape": [
+        "T"
+      ],
+      "container": "pt",
+      "root_type": "CPU Tensor"
+    },
+    "segment": {
+      "data_refs": [
+        "annotation/segment/mask.mkv",
+        "annotation/segment/polygons.jsonl"
+      ],
+      "valid_ref": "preserve source release reference; normally annotation/segment/mask_valid.pt",
+      "dtype": "bool",
+      "shape": [
+        "T"
+      ],
+      "container": "pt",
+      "root_type": "CPU Tensor"
+    },
+    "relations": {
+      "data_ref": "annotation/contact/relations.jsonl",
+      "valid_ref": "annotation/contact/relations_valid.pt",
+      "dtype": "bool",
+      "shape": [
+        "T"
+      ],
+      "container": "pt",
+      "root_type": "CPU Tensor"
+    },
+    "depth": {
+      "data_ref": "observation/depth.mkv",
+      "valid_ref": "observation/depth_valid.mkv",
+      "dtype": "bool",
+      "shape": [
+        "T",
+        "H",
+        "W"
+      ],
+      "profile": "mkv/bool_ffv1/v1"
+    }
+  }
+}