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name: bapps_2afc_protocol description: Evaluate BAPPS-style two-alternative forced choice perceptual similarity triplets with auditable per-item predictions.

BAPPS 2AFC Protocol

Use this skill when evaluating a perceptual distance function on reference, p0, p1, and human-choice triplets.

Do not use this skill to compute LPIPS distances internally; it owns the protocol and scoring contract only.

Inputs

• Triplets with id, ref, p0, p1, and judge fields.
• A distance provider that returns d0 = distance(ref, p0) and d1 = distance(ref, p1), or precomputed d0 and d1 values.
• Labels where judge = 0 means p0 is closer and judge = 1 means p1 is closer.

Outputs

• Aggregate 2afc_accuracy.
• Per-item predictions, distances, labels, and correctness.

Workflow

1. Validate every triplet label.
2. Compute or consume d0 and d1.
3. Predict 1 when d1 < d0; otherwise predict 0.
4. Average correctness over items.
5. Save per-item records for recovery analysis.

Validation

Run:

python scripts/evaluate_2afc.py --self-test
python tests/test_evaluate_2afc.py

Limitations

Ties default to prediction 0 for deterministic scoring. If a benchmark specifies probabilistic tie handling, record that deviation outside this skill.