Face Alignment Skill

Use this skill to debug face alignment artifacts and embedding gating behavior.

When to Use

• Faces being rejected but you don't know why
• Identity fragmentation that might be alignment-related
• Need to adjust alignment quality thresholds
• Debugging how alignment_quality is computed and consumed
• Planning promotion/integration (FEATURE sandbox → production)

Sub-agents

Key Skills

Run FAN alignment on a face bbox

Run alignment on detected face boxes (produces 68-point landmarks; optional aligned crop).

from FEATURES.face_alignment.src.run_fan_alignment import FANAligner, align_face_crop

aligner = FANAligner(model_type="2d", landmarks_type="2D", device="cpu")
landmarks = aligner.align_face(image, bbox)  # 68 x 2
aligned_crop = align_face_crop(image, landmarks, output_size=112)

Compute alignment_quality (heuristic today)

Get a per-face quality score (0–1). Current implementation is heuristic-based.

from FEATURES.face_alignment.src.alignment_quality import compute_alignment_quality

quality = compute_alignment_quality(bbox=bbox, landmarks_68=landmarks)

Generate episode artifacts

python -m FEATURES.face_alignment --episode-id <EP_ID>

Config Reference

Alignment Artifact Config: config/pipeline/face_alignment.yaml

Embedding Gating Config: config/pipeline/embedding.yaml

Common Issues

Faces unexpectedly skipped before embedding

Cause: Face below quality threshold

Check: alignment_quality in data/manifests/{ep_id}/face_alignment/aligned_faces.jsonl

Fix: Lower threshold in config/pipeline/embedding.yaml:

face_alignment:
  min_alignment_quality: 0.2  # default is 0.3

High landmark_jitter

Cause: Unstable landmarks across frames

Check: Per-frame landmark variance in track

Fix:

• Ensure FAN model loaded correctly
• Check input face crop quality
• May need temporal smoothing

3D head pose / profile gating isn’t available

Cause: 3DDFA_V2 isn’t implemented yet (planned).

Diagnostic Output

{
  "face_id": "F_42_100",
  "alignment_quality": 0.72,
  "landmarks_detected": 68,
  "head_pose": {
    "yaw": -25.5,
    "pitch": 10.2,
    "roll": 3.1
  },
  "quality_breakdown": {
    "eyes": 0.85,
    "nose": 0.80,
    "mouth": 0.65,
    "chin": 0.55
  },
  "aligner_used": "fan_2d"
}

Key Files

Related Skills

• pipeline-insights - General pipeline debugging
• cluster-quality - Clustering metrics