1. page_crop: Score all dark runs by center-proximity × darkness ×
narrowness instead of picking the widest. Fixes ad810209 where a
wide dark area at 35% was chosen over the actual spine at 50%.
2. cv_words_first: Replace x-center-only word→column assignment with
overlap-based three-pass strategy (overlap → midpoint-range → nearest).
Fixes truncated German translations like "Schal" instead of
"Schal - die Schals" in session 079cd0d9.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The border strip filter (Step 4e) used the LARGEST x-gap which incorrectly
removed base words along with edge artifacts. Now uses a two-stage approach:
1. _filter_border_strip_words() pre-filters raw words BEFORE column detection,
scanning from the page edge inward to find the FIRST significant gap (>30px)
2. Step 4e runs as fallback only when pre-filter didn't apply
Session 4233 now correctly detects 3 columns (base word | oder | synonyms)
instead of 2. Threshold raised from 15% to 20% to handle pages with many
edge artifacts. All 4 ground-truth sessions pass regression.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Content word_boxes in test used x-spacing (i%3)*100 which created
internal gaps larger than the border-to-content gap. Changed to
(i%2)*51 so content words overlap and the border gap remains dominant.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Textbooks with decorative alphabet strips along page edges produce
OCR artifacts (scattered colored letters at x<150 while real content
starts at x>=179). Step 4e detects a significant x-gap (>30px) between
a small cluster (<15% of total word_boxes) near the page edge and the
main content, then removes the border-strip word_boxes.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The frontend renders colored cells from the word_boxes array order,
not from cell.text. After post-processing steps (5i bullet removal etc),
word_boxes could remain in their original insertion order instead of
left-to-right reading order. Step 5j now explicitly sorts word_boxes
using _group_words_into_lines before the result is built.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Step 5i: For word_boxes with >90% x-overlap and different text, use IPA
dictionary to decide which to keep (e.g. "tightly" in dict, "fighily" not).
Red threshold raised from 80 to 90 to catch remaining scanner artifacts
like "tight" and "5" that were still misclassified as red.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Scanner artifacts on black text produce slight warm tint (hue ~0, sat ~60)
that was misclassified as red. Now requires median_sat >= 80 specifically
for red classification, since genuine red text always has high saturation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Reject /.../ matches containing spaces, parens, or commas (e.g. sb/sth up)
- Second pass converts trailing /ipa2/ after [ipa1] (double pronunciation)
- Validate standalone /ipa/ at start against same reject pattern
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Dictionary-style pages print IPA between slashes (e.g. tiger /'taiga/).
Step 5h detects these patterns, looks up the headword in the IPA dictionary
for proper Unicode IPA, and falls back to OCR text when not found.
Converts /ipa/ to [ipa] bracket notation matching the rest of the pipeline.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Step 4d removes "|" and "||" word_boxes that OCR produces when reading
physical vertical divider lines between columns. Also strips stray pipe
chars from cell text.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Two fixes:
1. Add pl, sg, no, also, ae, be etc. to _GRAMMAR_BRACKET_WORDS so
annotations like (pl) and (no pl) are not replaced with IPA.
2. Skip articles (the, a, an) in fix_ipa_continuation_cell — they
never get IPA in vocabulary books.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three fixes:
1. fix_ipa_continuation_cell: when headword has inline IPA like
"beat [bˈiːt] , beat, beaten", only generate IPA for uncovered
words (beaten), not words already shown (beat). When bracket is
at end like "the Highlands [ˈhaɪləndz]", return inline IPA directly.
2. Step 5d: recover garbled IPA from word_boxes when Step 5c emptied
the cell text (e.g. "[n, nn]" → "").
3. Added 2 tests for inline IPA behavior (35 total).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Page numbers like "two hundred and twelve" in the last row were falsely
detected as headings. Now first and last non-header rows are excluded.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Color headings now preserve actual starting col_index instead of hardcoded 0
- New _detect_heading_rows_by_single_cell: detects rows with only 1 content
cell (excl. page_ref) as headings — catches black headings like "Theme"
that have normal color/height but are alone in their row
- Runs after Step 5d (IPA continuation) to avoid false positives
- 5 new tests (32 total)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Two fixes:
1. Step 5d now only treats cells as continuation when text is entirely
inside brackets (e.g. "[n, nn]"). Cells with headwords outside brackets
(e.g. "employee [im'ploi:]") are no longer overwritten.
2. fix_ipa_continuation_cell no longer skips grammar words like "down" —
they are part of the headword in phrasal verbs like "close sth. down".
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Detect bracketed text without real IPA symbols as garbled OCR phonetics
- Allow IPA continuation fix even when other columns have content (for rows
where EN cell is clearly garbled bracketed IPA)
- Strip parenthetical grammar annotations like (no pl) from headword before
IPA lookup in fix_ipa_continuation_cell
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1. Skip ghost filtering for boxes with border_thickness=0 (images/graphics
have no border lines to produce OCR artifacts like |, I)
2. Remove individual word_boxes with height > 3x zone median (OCR from
graphics like a huge "N" from a map image below text)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
1. Filter words inside image_overlays (removes OCR from images)
2. Ghost filter: only remove single-char border artifacts, not multi-char
like (= which is real content
3. Skip first-row header detection for zones with image_overlays
(merged geometry creates artificial gaps)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Zone merging: content zones separated by box zones (images) are merged
into a single zone with image_overlays, so split tables reconnect.
Heading detection: after color annotation, rows where all words are
non-black and taller than 1.2x median are merged into spanning heading cells.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The _detect_spine_shadow function was triggering on normal text content
because shadow_range > 20 was too low and convolution edge artifacts
created artificially low values. Now requires: range > 40, darkest < 180,
narrow valley (not text plateau), and brightness rise toward page content.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Enrich column geometries with original full-page words (box-filtered)
so _detect_sub_columns() finds narrow sub-columns across box boundaries
- Add inline marker guard: bullet points (1., 2., •) are not split into
sub-columns (minimum gap check: 1.2× word height or 20px)
- Add box_rects parameter to build_grid_from_words() — words inside boxes
are excluded from X-gap column clustering
- Pass box rects from zones to words_first grid builder
- Add 9 tests for box-aware column detection
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add /rapid-kombi backend endpoint using local RapidOCR + Tesseract merge,
KombiCompareStep component for parallel execution and side-by-side overlay,
and wordResultOverride prop on OverlayReconstruction for direct data injection.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend: Add spatial overlap check (>=50% horizontal IoU) to Kombi merge
so words at the same position are deduplicated even when OCR text differs.
Frontend: Add yPct/hPct to WordPosition so each word renders at its actual
vertical position instead of all words collapsing to the cell center Y.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
PaddleOCR returns entire phrases as single boxes (e.g. "More than 200
singers took part in the"). The merge algorithm compared word-by-word
but Paddle had multi-word boxes vs Tesseract's individual words, so
nothing matched and all Tesseract words were added as "extras" causing
duplicates. Now splits Paddle boxes into individual words before merge.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replaces position-based word matching with row-based sequence alignment
to fix doubled words and cross-line averaging in Kombi-Modus.
New algorithm:
1. Group words into rows by Y-position clustering
2. Match rows between engines by vertical center proximity
3. Within each row: walk both sequences left-to-right, deduplicating
4. Unmatched rows kept as-is
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Even after multi-criteria matching, near-duplicate words can slip through
(same text, centers within 30px horizontal / 15px vertical). The new
_deduplicate_words() removes these, keeping the higher-confidence copy.
Regression test with real session data (row 2 with 145 near-dupes)
confirms no duplicates remain after merge + deduplication.
Tests: 37 → 45 (added TestDeduplicateWords, TestMergeRealWorldRegression).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The merge algorithm now uses 3 criteria instead of just IoU > 0.3:
1. IoU > 0.15 (relaxed threshold)
2. Center proximity < word height AND same row
3. Text similarity > 0.7 AND same row
This prevents doubled overlapping words when both PaddleOCR and
Tesseract find the same word at similar positions. Unique words
from either engine (e.g. bullets from Tesseract) are still added.
Tests expanded: 19 → 37 (added _box_center_dist, _text_similarity,
_words_match tests + deduplication regression test).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
PaddleOCR als neue engine=paddle Option in der OCR-Pipeline.
Microservice auf Hetzner (paddleocr-service/), async HTTP-Client
(paddleocr_remote.py), Frontend-Dropdown, automatisch words_first.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
fix_cell_phonetics() ersetzt fehlerhafte IPA-Klammern UND fuegt fehlende
Lautschrift fuer englische Woerter ein (z.B. badge, film, challenge, profit).
Wird auf alle Zellen mit col_type column_en/column_text angewandt.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Spalten-, Zeilen-, Woerter-Overlay und alle nachfolgenden Steps
(LLM-Review, Rekonstruktion) lesen jetzt image/cropped mit Fallback
auf image/dewarped. Tests fuer page_crop.py hinzugefuegt (25 Tests).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
process-single-page now runs the full CV pipeline (deskew → dewarp → columns →
rows → cell-first OCR v2 → LLM review) for much better extraction quality.
Falls back to LLM vision if pipeline imports are unavailable.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Cell-First OCR (v2): Each cell is cropped and OCR'd in isolation,
eliminating neighbour bleeding (e.g. "to", "ps" in marker columns).
Uses ThreadPoolExecutor for parallel Tesseract calls.
Document type detection: Classifies pages as vocab_table, full_text,
or generic_table using projection profiles (<2s, no OCR needed).
Frontend dynamically skips columns/rows steps for full-text pages.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Frontend: Replace hardcoded EN/DE/Example vocab table with unified dynamic
table driven by columns_used from backend. Labeling, confirmation, counts,
and summary badges are now all cell-based instead of branching on isVocab.
Backend: Change _cells_to_vocab_entries() entry filter from checking only
english/german/example to checking ANY mapped field. This preserves rows
with only marker or source_page content, fixing the issue where marker
sub-columns disappeared at the end of OCR processing.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Header/footer words (page numbers, chapter titles) could pollute the
left-edge alignment bins and trigger false sub-column splits. Now
_detect_header_footer_gaps() runs early and its boundaries are passed
to _detect_sub_columns() to filter those words from clustering and
the split threshold check.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Word 'left' values in ColumnGeometry.words are relative to the content
ROI (left_x), but geo.x is in absolute image coordinates. The split
position was computed from relative word positions and then compared
against absolute geo.x, resulting in negative widths and no splits on
real data. Pass left_x through to _detect_sub_columns to bridge the
two coordinate systems.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replace gap-based splitting with alignment-bin approach: cluster word
left-edges within 8px tolerance, find the leftmost bin with >= 10% of
words as the true column start, split off any words to its left as a
sub-column. This correctly handles both page references ("p.59") and
misread exclamation marks ("!" → "I") even when the pixel gap is small.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Detects hidden sub-columns (e.g. page references like "p.59") within
already-recognized columns by clustering word left-edge positions and
splitting when a clear minority cluster exists. The sub-column is then
classified as page_ref and mapped to VocabRow.source_page.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Gaps that extend to the image boundary (top/bottom edge) are not valid
content separators — they typically represent dewarp padding. Only gaps
with content on both sides qualify as header/footer boundaries.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Check for actual ink content in detected top/bottom regions:
- 'header'/'footer' when text is present (e.g. title, page number)
- 'margin_top'/'margin_bottom' when the region is empty page margin
Also update all skip-type sets and color maps for the new types.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
