probes/core_ab.py with the headset on (3 rounds, the same replayed frames in
every block): on 5-7 a step took 8.4 ms against 13.2 ms on 2-4, where XRService's
head tracking also runs, and latency fell from 14.1 to 9.6 ms. The compositor's
late frames and CPU/GPU time per frame didn't change.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
fh-ringplay plays a recording into a frame ring in real time, and fh-tracker
--ring reads it (cameras without a device node are mapped by name). With the
same frames in every run, probes/core_ab.py compares the tracker on CPUs 2-4,
on 5-7, and not running, measuring the tracker's step time and latency, the
compositor's late frames and CPU/GPU time, XRService's timing warnings, CPU
temperature and clocks.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
fh-camd (camd/) borrows XRService's camera buffers and publishes the tracking
cameras' frames to a shared ring. fh-tracker (trackd/) finds hands in them with
MediaPipe's palm and landmark models on ncnn, triangulates them in 3D, and
publishes them for ft-screens. fh-replay replays recordings offline. tracker/ is
the earlier Python version; tools/ and probes/ hold the checks and experiments.
As of this commit: crop contrast defaults to CLAHE for the palm search and plain
crops for the landmarks, --swap-sides works around fh-camd naming the side
cameras backwards after some XRService restarts (tools/check_sides.py detects
it), and --record-only, --with-dark, --cpus and --keep-presence support the
bright-light and CPU-placement tests.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
