Cubed camera tracker v1
Two setup-specific ONNX models provide camera evidence for
Cubed Core:
artifacts/alignment-classifier.onnx classifies whether the cube is alignedartifacts/face-pose.onnx detects a face and four ordered keypoints
Cubed Core uses their outputs for alignment, pose, motion, and visible-face
color reads. The models do not emit moves, establish cube state, or complete a
decode.
Files
| File | Purpose |
|---|
artifacts/alignment-classifier.onnx | Batch-one alignment classifier |
artifacts/face-pose.onnx | Batch-one face-pose model |
manifest.json | Runtime roles, paths, sizes, licenses, and SHA-256 values |
audit.json | Mechanical package and ONNX interface checks |
warm-start/camera-tracker-v1-warm-start.tar.gz | Optional PyTorch training checkpoints |
SHA256SUMS covers the published payload. Version:
camera-tracker-v1-2026-07-24.
For the supported setup, follow Cubed Core's
Decode guide.
To package or train compatible models, see
Train tracker.
Pin an exact repository revision for reproducible use.
Limits
These models are tied to the maintainer's cube, camera geometry, hands,
lighting, and backgrounds. They are unmeasured on unrelated setups, and no
tracker-quality, move-accuracy, or generalization claim is made. The historic
training snapshots are not included, so these exact artifacts cannot be
rebuilt from the public materials.
The warm-start archive contains PyTorch checkpoints. Loading a checkpoint uses
Python pickle and can execute code; verify its checksum and load it only in an
environment you trust. Inference users do not need it.
The published files are AGPL-3.0-only; see LICENSE. The license does not
cover unavailable historic training media.
