--- license: cc-by-sa-4.0 pretty_name: Cubed Solve Captures (cubed-data-v1) tags: - rubiks-cube - video - computer-vision - imu - sensor-fusion - robotics task_categories: - video-classification - other size_categories: - n<1K --- # Cubed Solve Captures (`cubed-data-v1`) 35 self-recorded captures of a GAN 12 ui Bluetooth smart cube being solved: portrait 1080×1920 H.264 video at ~120 fps with no audio (3.15 GB total), paired with the cube's own BLE move log, phone IMU samples, and a replay-verified scramble record. The corpus exists for camera-only decode research — reconstructing a solve from ordinary phone video — and is the input set for Cubed Core's Benchmark v0. It is a corpus, not a benchmark: no train/validation/test split is assigned here. ## Suites | suite | captures | what it is | | --- | ---: | --- | | `cs` | 25 | Complete solves. Full BLE + IMU. Video covers the whole solve on 24 of 25. | | `gt` | 6 | Research captures (gt17–gt22). Video ends before the solve's final move on five of six. Video + BLE + scramble record; no IMU. | | `gtD` | 4 | On-camera scramble from a verified solved start (gtD2–gtD5). The scramble itself is filmed. Full BLE + IMU. | All 35 BLE move logs replay bit-exact to solved on two independent cube engines: starting state, then the recorded move sequence, ends on the solved state. The per-move `facelets` strings embedded in a log are the cube's own periodic state broadcast and lag the move stream, so they are not the replay source of truth — use the scramble/start state plus the move tokens. ## Layout and fields One directory per capture under `captures//`. | file | captures | contents | | --- | ---: | --- | | `video.mp4` | 35 | Stream-copied from source: bitstream untouched, audio removed, container metadata stripped. | | `scramble.json` | 35 | Scramble in standard notation, derived start state, replay-verification and truncation status. | | `rights_record.json` | 35 | Per-artifact rights binding by byte count and SHA-256. | | `cube_session.json` | 35 | BLE move log: moves, facelet states, quaternions. `moves[].t_ms` and `orientations[].t_ms` are present as integer-millisecond deltas from session start; wall-clock time is still removed. | | `imu.json` | 29 | Phone IMU orientation samples. | | `app_cube_session.json` | 15 | App-side BLE log, verified move-identical to `cube_session.json`. | | `capture_manifest.json` | 14 | Capture-app manifest. | | `clip_ble_ground_truth.json` | 1 | Frame-indexed BLE ground truth (gtD1 only). | `dataset/manifest.json` is the authoritative inventory; `SHA256SUMS` lists a digest for every published file. Every JSON validates against a schema in the `schemas/` directory of the cubed-core repository. As of this release, `cube_session.json` adds relative timestamps. `moves[].t_ms` and `orientations[].t_ms` are integer-millisecond deltas from the start of the session. This makes frame registration (aligning the move log to the video) computable from public data alone, for every capture that ships a BLE session. Wall-clock date, time of day, and every private ingest handle stay out of the corpus, unchanged from the prior release. The relative timestamps follow the same disclosure the corpus already made for gtD1: `clip_ble_ground_truth.json` has shipped a frame-indexed BLE record with its own `scrub` block since the first release, and this update brings the other captures' BLE sessions to the same standard. **No calibration or camera-metadata artifact ships per capture.** The corpus was recorded with one cube and one camera setup family, and decode uses the single shared six-colour calibration (`calibration_gan12.json`) distributed as a cubed-core release asset. That calibration was measured under one lighting condition while the corpus spans three recording cohorts — treat colour evidence away from the gtD1 session accordingly. ## Benchmark v0 results Measured on this corpus; per-row tables, per-capture narratives and hash-bound receipts are under `benchmark/`. | suite | metric | result | | --- | --- | --- | | gt suite | reach-LL | **5 / 6** | | gtD1s | reach-solved | **1 / 1** | | cs suite | reach-LL | **4 / 24** | gt19 is reported informationally and excluded from the tallies: it was used to train an upstream verifier, so any result on it is contaminated. Reach-LL asks whether the raw predicted state path reaches last-layer onset with the correct pre-last-layer state, up to whole-cube orientation. These figures come from the evaluation lane, which supplies a ground-truth terminal; the productized camera-only path is a separate lane with its own contract and is not tabulated. ## Intended use This corpus is for camera-only cube-decode research: reconstructing a solve from ordinary phone video, with the cube's own BLE move log available as ground truth. It is also the input set for Cubed Core's Benchmark v0. It is a corpus, not a benchmark — no train/validation/test split is assigned here, and results measured on it are within-solver, within-setup findings. Decoding requires a CUDA host. The pipeline, the runner and the authoritative configuration live in [cubed-core](https://github.com/KingBobJoeIV/cubed-core) — see `docs/tutorials/DECODE.md` for the workflow and `config/decode-runtime-v1.json` for the profiles of record: `local_camera_v1` (camera-only, CFG_HASH `1852738634`) and `canonical_eval_reference` (evaluation lane, CFG_HASH `2587091255`). ```python from huggingface_hub import snapshot_download snapshot_download("cubed-core/cubed-data-v1", repo_type="dataset") ``` ## Licenses and attribution Released under CC-BY-SA-4.0. Attribution: Manas (). Every capture carries a `rights_record.json` binding each published artifact by byte count and SHA-256, with its own licence and attribution; those per-artifact licences are authoritative. The collection licence in `LICENSES/DATASET.md` covers selection and arrangement only. ## Privacy All captures were self-recorded by the dataset author solving a GAN 12 ui smart cube filmed with an iPhone, using the project's own capture tooling. No other person appears in or contributed to the recordings. The videos have no audio track and no container metadata: hands and the cube on a desk are the whole frame. The published sidecars carry move tokens, facelet states, quaternions, scrambles and frame indices — no absolute wall-clock times, filesystem paths, device serial numbers, hostnames or account identifiers. ## Limitations - One solver, one cube, one camera setup family. These captures cannot establish generalization across users, cameras, cubes, grips or lighting. - Video ends before the recorded solve's final move on six captures (five of `gt17`–`gt22`, plus `gtD4`); each capture's `scramble.json` records its own truncation status. The BLE log is complete regardless. - No per-capture colour calibration ships; decode uses one shared calibration measured under a single lighting condition across a corpus spanning three recording cohorts. - The Benchmark v0 figures above come from the evaluation lane, which supplies a ground-truth terminal. They are not camera-only results.