| --- |
| license: mit |
| task_categories: |
| - robotics |
| tags: |
| - autonomous-driving |
| - world-model |
| - tanitad |
| - ego-driving |
| - camera |
| - webdataset |
| size_categories: |
| - n<1K |
| extra_gated_prompt: >- |
| TanitDataSet-C is the commercially-clean tier of TanitDataSet. Its contents are |
| redistributable under their upstream licenses (today: 100% comma2k19, MIT). |
| Access is request-gated so the maintainer can see who is using it and notify |
| consumers of corrections; the gate is an access log, NOT an additional license |
| restriction — your rights are the upstream ones. |
| extra_gated_fields: |
| Name: text |
| Affiliation: text |
| Intended use: text |
| --- |
| |
| # TanitDataSet-C — the commercially-clean tier |
|
|
| **Seed release · 90 episodes · 15.93 GB · 14 WebDataset shards** |
|
|
| TanitDataSet-C is the **commercially-clean, redistributable** tier of TanitDataSet, |
| the camera-first autonomous-driving corpus behind the [TanitAD](https://huggingface.co/Sayood) |
| sub-300M hierarchical latent world model. Every record is `owned-safe` **and** |
| `commercial_ok`: a permissive upstream license, **no** share-alike, **no** gated, |
| non-commercial, or `refuse`-class source. |
|
|
| The tier is a **per-record stamp derived structurally** from a per-source license |
| CONSTANT (`SOURCE_REGISTRY`), never inferred from prose, and a hard export guard |
| refuses egress if a single row falls outside that scope. |
|
|
| > **Read the [Honest limits](#honest-limits--read-this-before-you-plan-around-it) |
| > section before planning around this dataset.** This is a *seed-scale* release |
| > (90 episodes, one source, one road type), not a training corpus. |
|
|
| --- |
|
|
| ## Contents |
|
|
| | | | |
| |---|---| |
| | **Episodes** | **90** (train 72 · val 18) | |
| | **Sources** | `comma2k19` (MIT) × 90 — **100 %** | |
| | **License classes present** | `owned-safe` × 90 — no `nc-research`, no `gated-confidential`, no `refuse` | |
| | **Share-alike rows** | 0 | |
| | **Shards** | 14 tar (11 train + 3 val), ~1.24 GB each | |
| | **Total size** | 15.93 GB | |
| | **Frame format** | `uint8 [T, 9, 256, 256]` — 100 % of records | |
| | **Catalog** | Hive-partitioned Parquet, 90 rows | |
|
|
| ### Sources & licenses |
|
|
| | source | license | class | `commercial_ok` | `share_alike` | episodes | |
| |---|---|---|---|---|---| |
| | [`comma2k19`](https://github.com/commaai/comma2k19) | MIT | `owned-safe` | ✅ | ❌ | 90 | |
|
|
| The **C tier admits** any permissive source (MIT / Apache-2.0 / CC-BY-4.0 / |
| OpenMDW-1.1). Today exactly one of them is built — see *Honest limits*. |
|
|
| --- |
|
|
| ## Record schema — the world-model contract |
|
|
| Each episode is the byte-identical contract every TanitAD adapter emits: |
|
|
| - **`frames`** — `uint8 [T, 9, 256, 256]` — a 3-frame RGB stack (9 = 3×RGB), |
| canonicalized to `f_eff ≈ 266 px` (the TanitAD D-016 geometry canon). |
| - **`actions`** — `f32 [T, 2]` — `(steer, accel)`, the action applied between |
| *t* and *t+1*. |
| - **`poses`** — `f32 [T, 4]` — `(x, y, yaw, v)` ego trajectory. |
| - **per-episode metadata** — `source`, `license_class`, `license_name`, |
| `commercial_ok`, `share_alike`, `split`, `sha256` of the frame blob, |
| `build_params_hash`, native intrinsics, modality flags. |
|
|
| ### Shard layout |
|
|
| ``` |
| shards/<license_class>/<source>/<split>/shard-XXXXX.tar |
| └── shards/owned-safe/comma2k19/train/shard-00000.tar … shard-00010.tar (72 eps) |
| └── shards/owned-safe/comma2k19/val/shard-00000.tar … shard-00002.tar (18 eps) |
| ``` |
|
|
| Partitioning by `license_class` is **layer 1 of the license firewall** — a |
| share-alike source would live under a segregated `sharealike/` prefix and could |
| never share a tar with non-SA data. There is none in this release. |
|
|
| Each tar holds three members per episode (WebDataset convention): |
|
|
| ``` |
| {episode_id}.frames.npy uint8 [T, 9, 256, 256] the canonical blob |
| {episode_id}.motion.npz actions / poses / timestamps |
| {episode_id}.meta.json the full catalog row + provenance |
| ``` |
|
|
| ### Loading |
|
|
| A shard is a plain tar — no `webdataset` package required. |
|
|
| ```python |
| import io, json, tarfile, hashlib, numpy as np |
| |
| with tarfile.open("shards/owned-safe/comma2k19/val/shard-00000.tar") as tf: |
| blobs, metas = {}, {} |
| for ti in tf: |
| key, _, ext = ti.name.partition(".") |
| data = tf.extractfile(ti).read() |
| if ext == "frames.npy": blobs[key] = data |
| elif ext == "meta.json": metas[key] = json.loads(data) |
| |
| for key, meta in metas.items(): |
| frames = np.load(io.BytesIO(blobs[key]), allow_pickle=False) # [T,9,256,256] |
| assert hashlib.sha256(frames.tobytes()).hexdigest() == meta["sha256"] |
| ``` |
|
|
| The `catalog/` Parquet index carries one row per episode (everything except the |
| frame blob) Hive-partitioned by `license_class / source / split`, so you can plan |
| a subset with a predicate before touching a single byte of video: |
|
|
| ```python |
| import pyarrow.dataset as pads |
| cat = pads.dataset("catalog", partitioning="hive") |
| rows = cat.to_table(filter=(pads.field("split") == "val")).to_pylist() |
| ``` |
|
|
| > **Note:** no `configs:` auto-loader block is declared. `datasets`' |
| > WebDataset builder has no decoder for the `.npz` motion member, so an |
| > auto-config would silently drop actions and poses. Use the snippet above. |
|
|
| --- |
|
|
| ## Provenance & verification |
|
|
| Every episode carries a **`sha256` of its exact frame bytes** and a |
| `build_params_hash`, so a consumer can verify any shard member **without |
| rebuilding it** — a rotted shard fails loudly instead of training on garbage. |
|
|
| Verified on **2026-07-25** immediately before this release, over the actual |
| payload bytes (not the metadata claim): |
|
|
| | check | result | |
| |---|---| |
| | shards present | **14 / 14** | |
| | episodes in payload | **90** (train 72 · val 18) | |
| | `sha256` re-verified over `frames.npy` bytes | **90 / 90 PASS**, 0 fail | |
| | catalog ↔ payload episode-id bijection | ✅ exact | |
| | catalog ↔ payload `sha256` agreement | ✅ exact | |
| | frame shape / dtype uniformity | 90 / 90 `[T,9,256,256]` `uint8` | |
| | distinct source corpora in payload | `{comma2k19: 90}` — **only** | |
| | distinct license classes in payload | `{owned-safe: 90}` — **only** | |
| | duplicate episode ids across shards | **0** | |
| | train/val episode-id overlap | **0** | |
| | shard-path ↔ metadata split mismatches | **0** | |
| | gated / `refuse` / NC / share-alike rows | **0 / 0 / 0 / 0** | |
|
|
| Machine-readable: **`LICENSE_VERIFICATION.json`** (both legs — the repo's own |
| `license_guard` and the independent payload audit), **`build_report_C.json`**, |
| **`MANIFEST.json`**, **`BUILD_MANIFEST.json`**, **`NOTICE`**. |
| |
| --- |
| |
| ## Honest limits — read this before you plan around it |
| |
| This is a **seed release**. We would rather publish the gaps than let the size of |
| the repo imply a corpus that does not exist. |
| |
| 1. **90 episodes is seed-scale, not training-scale.** This is a working proof of |
| the schema, the license firewall and the shard/catalog contract — with real |
| records attached. It is **not** enough data to train a driving world model. |
| TanitAD's own flagship trains on a different, larger, internal corpus. |
|
|
| 2. **One source, one road type.** All 90 episodes are comma2k19: US highway, |
| forward camera, largely free-flow. There is **no** urban, no intersection, no |
| VRU-dense, no night/adverse-weather coverage in this release, and no surround |
| camera, LiDAR, map or route annotation. |
|
|
| 3. **L2D contributed 0 records — no adapter exists yet.** [L2D](https://huggingface.co/datasets/yaak-ai/L2D) |
| (Apache-2.0) is the source that would make this tier complete across the |
| strategic (map / speed limit / route), tactical (CAN turn-indicator) and |
| operative (ego trajectory) layers. It is correctly registered as shippable, but |
| the LeRobot-v3 `parquet+mp4` → 9-channel-stack adapter is ~2–3 engineering days |
| of work that has **not** been done. Until it lands, L2D cannot enter the corpus. |
| Two known traps are already recorded for whoever builds it: **L2D ships no |
| camera intrinsics** (a risk to the `f_eff ≈ 266` canon), and its sliding-window |
| episodes **double-count ~50 %** unless de-duplicated by timestamp and split on |
| reconstructed drives rather than episodes. |
|
|
| 4. **PhysicalAI-AV is deliberately excluded and always will be.** TanitAD's main |
| internal training corpus is NVIDIA's gated PhysicalAI-AV. It is |
| `gated-confidential`: **not redistributable**, firewalled, recipe-only. It is |
| structurally unable to become a record in this lake — the ingestor raises |
| `PermissionError` — and it will never appear in this dataset or in |
| TanitDataSet-R. Nothing here is derived from it. |
|
|
| 5. **Waymo Open / WOD-E2E and Waymax are refused outright**, not merely excluded. |
| Their terms follow the *trained weights* into the model and vehicle operation, |
| so the contamination would survive training and no tier could contain them. |
| They are encoded as a distinct `refuse` license class that raises on ingest. |
|
|
| 6. **The split is episode-level, not route-disjoint.** The cache this build read |
| had already lost comma2k19's route ids, so train/val were split per episode. |
| comma2k19 is one commute route re-driven, so **train and val episodes can share |
| road segments.** Do not report a generalization number from this split without |
| saying so; rebuild from the comma2k19 origin if you need a strictly |
| route-disjoint split. |
|
|
| 7. **Near-duplicates are kept on purpose, and the near-dup detector over-collapses |
| here.** A two-pass perceptual dedup flagged 67 of 90 as near-duplicates of 23 |
| exemplars. That is a **detector artifact**, not duplication: the 90 have |
| distinct ids and distinct exact-frame hashes, and near-dup pairs sit at |
| mid-keyframe L1 ≈ 0.10 vs 0.15 for random pairs — genuinely different highway |
| scenes. A single-keyframe 8×8 aHash with transitive union-find chains |
| homogeneous highway footage into one smear. **All 90 records ship**; the |
| exemplar flag is a sampling hint, and the repeats are wanted multi-traversal |
| signal. Control frequency by sampling weight, not by deletion. |
|
|
| 8. **No semantic / VLM labels in this release.** The v3 goal vocabulary |
| (`VTARGET` / `LONMODE` / `HEADWAY` / lead-state / scene tags) and the |
| Chain-of-Causation traces are designed and piloted but are **not** in these |
| records. Records carry frames, actions, poses and provenance only. |
|
|
| 9. **Anonymization is inherited, not re-applied.** comma2k19 is already publicly |
| distributed under MIT as forward-facing US-highway dashcam footage, where PII |
| exposure is low; **no additional face/plate blurring was applied by us**, and |
| nothing was added that is not already in the upstream release. If your |
| jurisdiction requires a face/plate pass before *your* redistribution, run it. |
|
|
| 10. **Numbers here are measured on this bundle only.** No TanitAD model result is |
| quoted on this card; model facts live in the program's model registry, and |
| quoting them from a data card is exactly the error class this program logs. |
| |
| --- |
|
|
| ## Relationship to TanitDataSet-R |
|
|
| `R = C ∪ NC` over one schema. **As of this release, [TanitDataSet-R](https://huggingface.co/datasets/Sayood/TanitDataSet-R) |
| contains exactly the same 90 records as C** — no non-commercial source is |
| ingested yet, so R currently adds nothing. If you want the commercial tier, this |
| repo is the one to use. |
|
|
| ## Citation / attribution |
|
|
| This dataset is a re-packaging, into the TanitAD canonical world-model contract, |
| of publicly released data. **Cite the upstream source:** |
|
|
| ```bibtex |
| @article{schafer2018commute, |
| title = {A Commute in Data: The comma2k19 Dataset}, |
| author = {Schafer, Harald and Santana, Eder and Haden, Andrew and Biasini, Riccardo}, |
| journal= {arXiv preprint arXiv:1812.05752}, |
| year = {2018} |
| } |
| ``` |
|
|
| Attribution and per-source license text ship in **`NOTICE`**. |
|
|
| _Built by the TanitAD Phase-A lake pipeline. Provenance travels with the data._ |
|
|
