docs/DATA.md

Data card

Covers what this repository actually produced, and what the design doc calls for but could not be obtained here. Design-doc sections 6, 8, 9, 13.

Line A — exact synthetic panorama video

Source. OpenPano, the panorama collection assembled for GeoCalib and reused by AnyCalib. Public HTTPS download from ETH: https://cvg-data.inf.ethz.ch/GeoCalib_ECCV2024/openpano.zip (7.5 GB).

What arrived. 749 panoramas: 670 train / 39 val / 40 test, at 10000x5000 or 16k, in the authors' own panorama-level split. Provenance groups: 618 poly-haven-style *_16k, 130 hdrmaps_com_free, 1 other.

What is missing. The split lists name 2,908 panoramas. The remaining 2,162 are Laval Indoor HDR, which requires a manual application to the authors (tools/download/fetch.py info laval). The indexer reports the shortfall per split instead of silently skipping, and select_panos prints it on every run. Consequence: the synthetic tier here is built from the outdoor/HDRI part of OpenPano only, so indoor scenes are under-represented relative to the paper configuration.

Split policy. The authors' panorama-level split is honoured rather than re-drawn — re-splitting would silently invalidate the AnyCalib/GeoCalib comparison, since those models were trained on this partition.

Generated tiers.

tier	panoramas	clips	frames total	resolution	size	wall time
smoke	20	200	16,200	832x480	732 MB	285 s (12 workers)
MVP	749	11,984	970,704	832x480	51 GB	5.2 h (12 workers)

MVP splits: 10,720 train / 624 val / 640 test clips from 749 distinct panorama sources. Camera-model counts 4,065 pinhole / 4,008 Brown-Conrady / 3,911 EUCM (0.339 / 0.334 / 0.326 against the 0.34 / 0.33 / 0.33 target). Trajectory families 7,185 rotation-only / 3,514 smooth 6-DoF / 1,285 difficult. Zero split leakage, zero manifest integrity errors, 1,169 clips (9.8%) flagged resolution_limited.

Camera-model mixture reproduces AnyCalib's openpano_v2_gen config exactly: pinhole 0.34 / radial:1 0.33 / EUCM 0.33, with vfov ~ U(20, 105) deg for the first two and U(50, 180) deg for EUCM, k1 = k1_hat * f / h with k1_hat ~ truncnorm(+-0.3, sigma 0.07), alpha ~ U(0.5, 0.8), beta ~ U(0.5, 2.0). On top of that ViDiCalib samples what the doc asks for and AnyCalib's generator does not: 30% of clips have an off-centre principal point (within +-10% of W/H) and 20% have non-square pixels (+-5%).

Trajectory mixture (doc section 7.1): rotation-only 0.34, smooth 6-DoF 0.29, real-motion replay 0.27, difficult 0.09. The real-motion share is a fallback: no CameraBench / TUM VI pose files were available here, so those clips are sampled rotation-only trajectories tagged fallback=True with intended_family="real_replay". pool_summary reports both the actual and the intended mixture so this cannot be misread.

Per-clip storage. One MP4 (H.264, CRF 14, preset medium), one Stage-1a overlay MP4, one Stage-1b overlay MP4, and a compact NPZ. The NPZ stores only what cannot be recomputed — camera parameters, validity mask, per-frame gravity and rotations, non-trivial coverage — so it is ~8.5 KiB per clip instead of the 93 MiB a stored 81 x 480 x 832 x 3 float16 ray field would take. Latitude, up field and the ray field are regenerated by expand_dense_gt.

Resolution honesty. A 480-row clip at 100 deg vertical FoV needs ~0.21 deg/px, i.e. a panorama of at least ~1,729 rows before supersampling. Panoramas are loaded at 2,560 rows. Clips whose target camera is narrower than the panorama can resolve are flagged resolution_limited in the manifest, with the achieved ratio recorded in generator.pano_resolution_ratio. In the smoke tier 21 of 200 clips carry that flag.

Line B — physical lens distortion

Lensfun (public git, third_party/lensfun). Parsed: 6,432 measured distortion calibrations across 1,429 lens families — ptlens 5,554, poly3 873, poly5 5. For scale, AlignDiff's LensView bank is 3,187 profiles and is not downloadable.

Built bank (/data/derived/lenses/profiles.jsonl): 6,474 profiles including Optiland, across 1,436 families.

distortion family	profiles
pincushion	2,732
barrel	2,203
negligible	1,326
moustache	177
fisheye	36

Near-duplicate clustering found 2,169 distinct radial signatures among the 6,474 profiles, i.e. 4,255 are near-copies of another entry at the analysis resolution. That is worth knowing before quoting the raw count as diversity.

Family split: 999 train families and 296 test families, with test_families_unseen_fraction = 1.0 -- every test family is absent from training, against the doc's 20% requirement.

Brown-Conrady k1 fitted from 120 real profiles spans [-0.376, 0.221], which brackets the range AnyCalib's synthetic k1_hat ~ truncnorm(+-0.3) produces; p1 and p2 come out within +-2e-4 of zero, because the open profile formats are purely radial.

Coverage gap: decentred / asymmetric distortion. None of Lensfun's three present models (ptlens, poly3, poly5) can express it -- they are radial in one variable -- and the database contains no acm entries, the one format that carries tangential terms. The v1 synthetic sampling does not cover it either, because it follows AnyCalib's radial:1 with p1 = p2 = 0. In this repository asymmetric distortion is therefore represented only by the non-parametric residual field, which handles it by construction but gives the model no training signal for it. Closing this needs acm-format profiles, decentred Optiland designs, or measured LUTs from the real rig.

Every profile is converted to the canonical pixel -> unit ray grid plus a 64x64 ideal-pixel -> distorted-pixel warp grid, with the Hugin-to-normalised unit conversion taken from lensfun's own source rather than guessed. Per-profile analysis records maximum displacement, monotonicity, Jacobian sign consistency, valid fraction, effective image circle and fittable FoV. Splits are by lens family, so the 24 mm and 70 mm nodes of one zoom never straddle a split.

Optiland (pip install optiland, MIT). Perturbed variants of its sample designs, traced with real rays to get image height versus field angle, then inverted. 42 valid profiles from 78 attempts across 7 designs (cooke_triplet, double_gauss, reverse_telephoto, telephoto, tessar, heliar, aspheric_singlet); petzval and field_corrector never traced successfully and are reported as rejected rather than quietly dropped. Coverage is barrel and pincushion only — the sample designs are rectilinear photographic objectives, so fisheye and moustache come from Lensfun and from the synthetic KB / EUCM / Double-Sphere sampling.

LensView (AlignDiff's commercial source) is not used and not required; the open path above is the main line, exactly as doc section 8.1 plan B specifies.

Line C — real 7V capture

Not collected. This requires vehicle access, the camera rig, and the calibration workflow of doc section 9 (Kalibr / BabelCalib / Basalt, AprilGrid sequences, IMU static segments, temperature sweeps). What exists here is the plumbing: ClipRecord carries domain_id, vehicle_id, route_id, gt_confidence and gt_ray_sigma_rad; check_split_leakage enforces the instance / vehicle / route / firmware split policy of doc section 9.3; and SourceCalibration.ray_sigma propagates the uncertainty of an estimated source calibration so re-distorted real footage is never treated as exact GT.

Registration-gated sources

Not obtained, and not scriptable. tools/download/fetch.py info <name> prints the exact procedure for each.

source	reason
Laval Indoor HDR	manual application to the authors
KITTI-360	registration + non-commercial licence
WoodScape	proprietary licence
Aria Digital Twin	registration, then a per-user CDN JSON
CameraBench train split	may require a form

Public-but-not-fetched sources

360-1M, UCPE/PanShot, CO3Dv2 and MegaDepth/TartanAir have working fetchers in tools/download/fetch.py but were not downloaded here. For 360-1M the fetcher deliberately stops after writing a filtered pilot selection: the full set is ~200 TB, the filtered 24k subset ~5 TB, the YouTube URLs decay, and the licence has to be checked per source.

Licences

• OpenPano — per-panorama; the poly-haven and hdrmaps portions are the permissively licensed part of the collection. Check the upstream terms before redistribution.
• Lensfun — CC-BY-SA / GPL depending on component; the profile data is an open database.
• Optiland — MIT.
• Wan2.1-VACE-1.3B — Apache-2.0.
• AnyCalib, GeoCalib checkpoints — see their repositories.
• CO3Dv2 — CC BY-NC 4.0 (non-commercial).

Raw downloads live outside the repository (/data/raw, /data/models) and are referenced by configuration. No data, weights or cookies are committed.