Production-grade dlib face_recognition toolkit: piecewise confidence formula, enrollment quality diagnostics, and producer-side persistence for flicker suppression.
96
93%
Does it follow best practices?
Impact
100%
2.70xAverage score across 6 eval scenarios
Passed
No known issues
A facilities team runs a smart meeting room system that dims the lights and locks the booking display whenever the room is detected as empty. The system uses a webcam with a face detector running at roughly 10 frames per second. The lights and lock state are controlled by an IoT actuator that listens for a presence signal.
The team has raised a support ticket: "The lights flicker constantly even when someone is sitting still in the room. The system seems to flip between occupied/empty multiple times a minute, which is distracting and makes the booking display unreadable."
An engineer has confirmed the detector itself is working — it just drops roughly 1 in 8 frames even with a subject clearly in frame, which is normal for this class of detector. The current pipeline connects the detector directly to the actuator.
Your task is to write a Python module presence_buffer.py that eliminates the flicker without modifying the detector or actuator code. The buffer should smooth out these short detection dropouts so the actuator sees stable presence state rather than frame-by-frame noise.
Also write demo_simulation.py: a self-contained simulation that instantiates your buffer, runs 60 synthetic frames with roughly 15% random dropout, and prints a frame-by-frame log showing the raw detector output alongside the effective presence signal the actuator would receive. Capture the simulation output to simulation_output.txt.
Additionally write architecture_notes.md explaining where this buffer fits in the overall pipeline relative to any actuator-side stability filtering, and how you chose the persistence duration.
presence_buffer.py — the buffer moduledemo_simulation.py — runnable simulation (no external dependencies beyond standard library and the buffer module)simulation_output.txt — stdout captured from running demo_simulation.pyarchitecture_notes.md — architecture notes on buffer placement and persistence duration choice