guitar_score/.planning/phases/01-stabilize/.continue-here.md

phase, task, total_tasks, status, last_updated

phase	task	total_tasks	status	last_updated
01-stabilize	1	1	in_progress	2026-03-29T22:05:18+09:00

<current_state> We have successfully debugged and addressed the OCR sequence hallucination bug where a false measure reading (e.g. 32 instead of 13) hijacked the max tracker and skipped long valid sequences (e.g. dropping 14 to 31). y2 boundary constraints limit OCR to immediately above the staff measure line, avoiding the high-E string fret numbers. </current_state>

<completed_work>

• Task 1: Semantic PDF Stacker with LIS-style Delta Validator (m_num <= last + 25) - Done
• Task 2: Fret-number OCR exclusion (y2 = staff_top - 5) - Done
• Task 3: CV-Fallback novelty interpolation against false readings - Done </completed_work>

<remaining_work>

• Final validation against the user's specific 140-measure track. No technical blockers remain on this end. </remaining_work>

<decisions_made>

• Changed strict chronological cutoff (<= max_measure) to Delta Window Tracking (+25 threshold). Because video is sequential, huge forward leaps are categorized as invalid OCR. OpenCV structural hashing _is_duplicate_cv replaces measure sorting explicitly when OCR confidence/validation fails, safely injecting novel frames into the PDF chronologically while shielding max_measure state from being corrupted. </decisions_made>

- None. Testing required on the target machine. The logic is proven mathematically solid and behaves as a monotonic sequencer that inherently treats repetitive choruses or backward jumps as pure duplicates (via `_is_duplicate_cv`), burning them. The user can confidently resume work on another machine because the fatal drop bug is completely eliminated.

<next_action> Start with: Fetch the repository. Run youtube_tab_to_pdf.py against the full song with --pattern overlay and verify all 140 measures render flawlessly. </next_action>