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jbaruch/face-recognition-calibration

Production-grade dlib face_recognition toolkit: piecewise confidence formula, enrollment quality diagnostics, and producer-side persistence for flicker suppression.

96

2.70x
Quality

93%

Does it follow best practices?

Impact

100%

2.70x

Average score across 6 eval scenarios

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

Evaluation results

100%

80%

Building a Face Recognition Confidence Display

Criteria
Without context
With context

Piecewise clamp at 0.30

0%

100%

Piecewise clamp at 0.60

0%

100%

Linear mid-range formula

0%

100%

No naive formula

100%

100%

Sanity check value at 0.38

0%

100%

Threshold constants correct

0%

100%

100%

78%

Face Enrollment Pipeline for an Access Control System

Criteria
Without context
With context

Blur threshold is 40

0%

100%

Blur threshold not 80

100%

100%

Intra-class mean target lower bound

0%

100%

Intra-class mean target upper bound

0%

100%

Intra-class max check

0%

100%

Pickle for enrollment storage

0%

100%

No re-enrollment in load path

100%

100%

Pale skin rationale

0%

100%

100%

31%

Eliminating Flicker in a Smart Meeting Room Presence System

Criteria
Without context
With context

miss_streak counter

100%

100%

Persist below threshold

100%

100%

Commit zero above threshold

100%

100%

last_conf reset on expiry

70%

100%

Persistence ~0.8s at 10Hz

12%

100%

Producer-side placement

100%

100%

Separate actuator debounce layer

0%

100%

Reset streak on detection

100%

100%

Evaluated
Agent
Claude
Model
Claude Sonnet 4.6

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