The cell grid IS the result. Each cell stays at its detected position.
Removed _split_comma_entries and _attach_example_sentences from the
pipeline — they were shuffling content between rows/columns, causing
"Mäuse" to appear in a separate row, "stand..." to move to Example,
and "Ei" to disappear.
Now: cells → _cells_to_vocab_entries (1:1 row mapping) →
_fix_character_confusion → _fix_phonetic_brackets → done.
Also lowered pixel-density threshold from 2% to 0.5% for the cell-OCR
fallback so small text like "Ei" is not filtered out.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three non-generic solutions replaced with universal heuristics:
1. Cell-OCR fallback: instead of restricting to column_en/column_de,
now checks pixel density (>2% dark pixels) for ANY column type.
Truly empty cells are skipped without running Tesseract.
2. Example-sentence detection: instead of checking for example-column
text (worksheet-specific), now uses sentence heuristics (>=4 words
or ends with sentence punctuation). Short EN text without DE is
kept as a vocab entry (OCR may have missed the translation).
3. Comma-split: re-enabled with singular/plural detection. Pairs like
"mouse, mice" / "Maus, Mäuse" are kept together. Verb forms like
"break, broke, broken" are still split into individual entries.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three bugs in the post-processing pipeline were overwriting correct
streaming results with wrong ones:
1. _split_comma_entries was splitting "Maus, Mäuse" into two separate
entries. Disabled — word forms belong together.
2. _attach_example_sentences treated "Ei" (2 chars) as OCR noise due
to `len(de) > 2` threshold. Lowered to `len(de) > 1`.
3. _attach_example_sentences wrongly classified rows with EN text but
no DE (like "stand ...") as example sentences, merging them into
the previous entry. Now only treats rows as examples if they also
have no text in the example column.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The row_result stored in DB excludes words to keep payload small.
When Step 5 reconstructs RowGeometry from DB, words were empty,
causing word-lookup to find nothing and return blank cells.
Now re-populates row.words from cached _word_dicts (or re-runs
detect_column_geometry if cache is cold) before cell grid building.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Cells now appear one-by-one in the UI as they are OCR'd, with a live
progress bar, instead of waiting for the full result.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Extract build_cell_grid() as layout-agnostic foundation from
build_word_grid(). Step 5 now produces a generic cell grid (columns x
rows) and auto-detects whether vocab layout is present. Frontend
dynamically switches between vocab table (EN/DE/Example) and generic
cell table based on layout type.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Two fixes:
1. Grid validation: reject word-center grid if it produces MORE rows
than gap-based detection (more rows = lines were split = worse).
Falls back to gap-based rows in that case.
2. Words overlay: draw clean grid cells (column × row intersections)
instead of padded entry bboxes. Eliminates confusing double lines.
OCR text labels are placed inside the grid cells directly.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When columns change (Step 3), invalidate row_result and word_result.
When rows change (Step 4), invalidate word_result.
This ensures Step 5 always uses the latest row boundaries instead of
showing stale cached word_result from a previous run.
Applies to both auto-detection and manual override endpoints.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Integrate Britfone dictionary (MIT, 15k British English IPA entries)
- Add pronunciation parameter: 'british' (default) or 'american'
- British uses Britfone (Received Pronunciation), falls back to CMU
- American uses eng_to_ipa/CMU, falls back to Britfone
- Frontend: dropdown to switch pronunciation, default = British
- API: ?pronunciation=british|american query parameter
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fix A: Use _group_words_into_lines() with adaptive Y-tolerance to
correctly order words in multi-line cells (fixes word reordering bug).
RapidOCR: Add as alternative OCR engine (PaddleOCR models on ONNX
Runtime, native ARM64). Engine selectable via dropdown in UI or
?engine= query param. Auto mode prefers RapidOCR when available.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Backend: build_word_grid() intersects column regions with content rows,
OCRs each cell with language-specific Tesseract, and returns vocabulary
entries with percent-based bounding boxes. New endpoints: POST /words,
GET /image/words-overlay, ground-truth save/retrieve for words.
Frontend: StepWordRecognition with overview + step-through labeling modes,
goToStep callback for row correction feedback loop.
MkDocs: OCR Pipeline documentation added.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add Step 4 (row detection) between column detection and word recognition.
Uses horizontal projection profiles + whitespace gaps (same method as columns).
Includes header/footer classification via gap-size heuristics.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Side-by-side view: auto result (readonly) vs GT editor where teacher
draws correct columns. Diff table shows Auto vs GT with IoU matching.
GT data persisted per session for algorithm tuning.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Ersetzt hardcodierte Positionsregeln durch ein zweistufiges System:
Phase A erkennt Spaltengeometrie (Clustering), Phase B klassifiziert
Typen per Inhalt (Sprache/Rolle) mit 3-stufiger Fallback-Kette.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace projection-profile layout analysis with Tesseract word bounding
box clustering to detect 5-column vocabulary layouts (page_ref, EN, DE,
markers, examples). Falls back to projection profiles when < 3 clusters.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Sessions werden jetzt in PostgreSQL gespeichert statt in-memory.
Neue Session-Liste mit Name, Datum, Schritt. Sessions ueberleben
Browser-Refresh und Container-Neustart. Step 3 nutzt analyze_layout()
fuer automatische Spaltenerkennung mit farbigem Overlay.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The old displacement-map approach shifted entire rows by a parabolic
profile, creating a circle/barrel distortion. The actual problem is
a linear vertical shear: after deskew aligns horizontal lines, the
vertical column edges are still tilted by ~0.5°.
New approach:
- Detect shear angle from strongest vertical edge slope (not curvature)
- Apply cv2.warpAffine shear to straighten vertical features
- Manual slider: -2.0° to +2.0° in 0.05° steps
- Slider initializes to auto-detected shear angle
- Ground truth question: "Spalten vertikal ausgerichtet?"
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The old -3.0 to +3.0 scale multiplied the full displacement map (up to ~79px)
directly, causing extreme distortion at values >1. New slider:
- 0% = no correction
- 100% = auto-detected correction (default)
- 200% = double correction
- Step size: 5%
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Fix dewarp method selection: prefer methods with >5px curvature over
higher confidence (vertical_edge 79px was being ignored for text_baseline 2px)
- Add grid overlay on left image in Dewarp step for side-by-side comparison
- Add GET /sessions/{id} endpoint to reload session data
- StepDeskew accepts sessionId prop to restore state when navigating back
- SessionInfo type extended with optional deskew_result and dewarp_result
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Neue Route /ai/ocr-pipeline mit schrittweiser Begradigung (Deskew),
Raster-Overlay und Ground Truth. Schritte 2-6 als Platzhalter.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
