Cubed camera tracker v1

Two setup-specific ONNX models provide camera evidence for Cubed Core:

artifacts/alignment-classifier.onnx classifies whether the cube is aligned
artifacts/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.

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