Backend: _ocr_cell_crop speichert jetzt word_boxes mit exakten
Tesseract/RapidOCR Wort-Koordinaten (left, top, width, height)
im Cell-Ergebnis. Absolute Bildkoordinaten, bereits zurueckgemappt.
Frontend: Slide-Hook nutzt word_boxes direkt wenn vorhanden —
jedes Wort wird exakt an seiner OCR-Position platziert. Kein
Pixel-Scanning noetig. Fallback auf alten Slide wenn keine Boxes.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Box-Sub-Sessions haben bereits ein zugeschnittenes Bild. Orientierung,
Begradigung, Entzerrung und Crop werden uebersprungen (skipped).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
detect_and_fix_orientation() wird jetzt vor dem Deskew-Schritt in der
OCR-Pipeline ausgefuehrt, sodass 90/180/270°-gedrehte Scans automatisch
korrigiert werden. Frontend zeigt Orientierungskorrektur als Info-Banner.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
handleNext() did nothing on the last step (early return). Now resets
session, steps and navigates back to the session overview.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add umlaut confusion rules (i→ü, a→ä, o→ö, u→ü) to _spell_fix_token
for German text — fixes "iberqueren" → "überqueren" etc.
- Add _detect_bold() using OpenCV stroke-width analysis on cell crops
- Integrate bold detection in both narrow (cell-crop) and broad (word-lookup) paths
- Add is_bold field to GridCell TypeScript interface
- Render bold text in StepGroundTruth reconstruction view
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replaces the stub StepGroundTruth with a full side-by-side Original vs
Reconstruction view. Adds VLM-based image region detection (qwen2.5vl),
mflux image generation proxy, sync scroll/zoom, manual region drawing,
and score/notes persistence.
New backend endpoints: detect-images, generate-image, validate, get validation.
New standalone mflux-service (scripts/mflux-service.py) for Metal GPU generation.
Dockerfile.base: adds fonts-liberation (Apache-2.0).
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>
- Add DewarpDetection type with per-method results
- Expand method labels for all 4 detectors (A-D)
- Show green/amber banner: applied vs quality-gate-rejected
- Expandable "Details" panel showing all 4 methods with confidence bars
- Visual confidence bars instead of plain percentage
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add marker/bbox_marker fields to WordEntry type
- Add page_ref/column_marker colors to StepReconstruction
- Make StepLlmReview table dynamic based on columns_used metadata,
showing all detected columns (EN, DE, Example, page_ref, marker)
instead of hardcoded EN/DE/Beispiel only
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Three fixes for sub-columns disappearing at end of streaming:
1. Backend: add column_marker mapping in _cells_to_vocab_entries()
so marker text is included in vocab entries (not silently dropped)
2. Frontend types: add source_page and bbox_ref to WordEntry interface
3. Frontend table: show page_ref column (Seite) in vocab table when
entries have source_page data, instead of only EN/DE/Example
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1. Unit tests: 76 new parametrized tests for noise filter, phonetic detection,
cell text cleaning, and row merging (116 total, all green)
2. Continuation-row merge: detect multi-line vocab entries where text wraps
(lowercase EN + empty DE) and merge into previous entry
3. Empty DE fallback: secondary PSM=7 OCR pass for cells missed by PSM=6
4. Batch-OCR: collect empty cells per column, run single Tesseract call on
column strip instead of per-cell (~66% fewer calls for 3+ empty cells)
5. StepReconstruction UI: font scaling via naturalHeight, empty EN/DE field
highlighting, undo/redo (Ctrl+Z), per-cell reset button
6. Session reprocess: POST /sessions/{id}/reprocess endpoint to re-run from
any step, with reprocess button on completed pipeline steps
Also fixes pre-existing dewarp_image tuple unpacking bug in run_cv_pipeline
and updates dewarp tests to match current (image, info) return signature.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
StepLlmReview: Show full vocab table with image overlay, row-level
status tracking (pending/active/reviewed/corrected/skipped), and
auto-scroll during SSE streaming. Load previous results on mount.
StepReconstruction: New step 7 with editable text fields at original
bbox positions over dewarped image. Zoom controls, tab navigation,
color-coded columns, save to backend.
Backend: Add POST /sessions/{id}/reconstruction endpoint.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace the placeholder "Koordinaten" step with an LLM review step that
sends vocab entries to qwen3:30b-a3b via Ollama for OCR error correction
(e.g. "8en" → "Ben"). Teachers can review, accept/reject individual
corrections in a diff table before applying them.
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>
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>
Insert rows step between columns and words in the pipeline wizard.
Shows overlay image, row list with type badges, and ground truth controls.
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>
- 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>
