Some environments default matplotlib to Agg (non-interactive), which
silently no-ops plt.show() — the picker would print "FigureCanvasAgg
is non-interactive" and never display the thumbnail grid. Probe TkAgg
> QtAgg > Qt5Agg > GTK3Agg before pyplot import.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Watching the video play turns out to be much faster than scanning a
thumbnail grid. The coarse 10-min thumbnail grid still does rough
localisation; after picking, a video player launches at coarse_t-30s
paused with frame-accurate scrubbing controls. The analyst reads the
exact opening time off the player's OSD and types it into the
terminal prompt (default = the coarse pick, so a single Enter keeps
the coarse pick if the player is hard to use).
Backend auto-detects mpv > vlc > ffplay; gracefully degrades to "use
the coarse pick" if no player is installed.
New `bad_rois` column captures non-opening sub-arenas (partial-opening
videos like the 2024-10-21 set where only the lower half opens). The
prompt validates entries are integers in 1..6.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Some videos have late barrier opening (e.g. 5:46) that fell outside
the original 5-min search window. Default coarse-grid span is now
600 s (10 s spacing in the 60-thumb grid). Add --coarse-span CLI flag
to widen further if needed; auto-suggest scans the same 10-min window.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Old version showed inter-fly distance plots and asked the analyst to
click a timeline. The new version reads frames directly from the .mp4
and shows a 10×6 grid of timestamped thumbnails — the analyst just
clicks the frame where the barrier opens.
Two-stage refinement:
- Coarse grid: 60 thumbs spanning the 5-min search window at ~5 s
spacing. Pick the rough moment.
- Fine grid: 60 thumbs at 0.2 s spacing centred on the coarse pick.
Pick the exact frame.
Auto-detector still feeds the starting position. Sequential video
decode (one cv2 pass through the relevant range) instead of seek-per-
frame, so each grid loads in a few seconds.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
pick_barrier.py loops over every tracked DB referenced by the merged
TSV, plots windowed mean inter-fly distance for all 6 ROIs in a single
figure, and lets the analyst click the moment the barrier opens. Saves
to data/metadata/barrier_opening.csv after each pick (crash-safe).
Auto-detector best-effort guess shown as orange dotted line — the
analyst always has the final say.
Output schema:
machine_name, session_date, session_time, opening_s, trim_first_s, notes
`trim_first_s` lets us record misframed starts so downstream code can
ignore the affected window. The 5 2025-07-15 entries are seeded from
the original legacy CSV so they're not re-picked.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
