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>
After iterative projection (pass 1) and word-alignment (pass 2), a third
pass uses Tesseract word positions + linear regression per text line to
measure and correct residual rotation. This catches cases where passes 1-2
leave significant slope (e.g. 1.7° residual on heavily skewed scans).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Increase iterative deskew coarse_range from ±2° to ±5° to handle
heavily skewed scans
- New deskew_two_pass(): runs iterative projection first, then
word-alignment on the corrected image to detect/fix residual skew
(applied when residual ≥ 0.3°)
- OCR pipeline API auto_deskew now uses deskew_two_pass by default
- Vocab worksheet _run_ocr_pipeline_for_page uses deskew_two_pass
- Deskew result now includes angle_residual and two_pass_debug
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds deskew_image_iterative() as 3rd deskew method that directly optimizes
for projection-profile sharpness instead of proxy signals (Hough/word alignment).
Coarse sweep on horizontal profile, fine sweep on vertical profile.
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>
- Remove _fix_character_confusion() from words endpoint (now only in Phase 0)
- Extend spell checker to find real OCR errors via spell.correction()
- Add field-aware dictionary selection (EN/DE) for spell corrections
- Add _normalize_page_ref() for page_ref column (p-60 → p.60)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Batch OCR takes 30-60s with 3x upscaling. Without keepalive events,
proxy servers (Nginx) drop the SSE connection after their read timeout.
Now sends keepalive events every 5s to prevent timeout, with elapsed
time for debugging. Also checks for client disconnect between keepalives.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Frontend: retry /words POST once after 2s delay if it gets 400/404,
which happens when navigating via wizard after container restart
(session cache not yet warm).
Backend: log when session needs DB reload and when dewarped_bgr is missing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The old per-cell streaming timed out because sequential cell OCR was
too slow to send the first event before proxy timeout. Now uses
build_cell_grid_v2 (parallel ThreadPoolExecutor) via run_in_executor,
then streams all cells at once after batch completes.
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>
The narrow column expansion was running inside detect_column_geometry()
on the 4 main columns, but the narrowest columns (marker ~14px,
page_ref ~93px) are created AFTERWARDS by _detect_sub_columns().
Extracted expand_narrow_columns() as standalone function and call it
after sub-column splitting in the columns API endpoint.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The try/except block for the deskew step had 4 extra spaces of
indentation from a previous edit. Python rejected the file with
IndentationError at startup.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1. Word-to-column assignment now uses overlap-based matching instead of
center-point matching. This fixes narrow page_ref columns losing
their last digit (e.g. "p.59" → "p.5") when the digit's center
falls slightly past the midpoint boundary into the next column.
2. Post-OCR empty row filter: rows where ALL cells have empty text
are removed after OCR. This catches inter-row gaps that had stray
Tesseract artifacts giving word_count > 0 but no actual content.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The streaming word endpoint excluded page_ref from _skip_types,
causing sub-column splits to be lost in the meta event and final
grid_shape. Aligned _skip_types with build_cell_grid_streaming().
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>
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>
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>
Replace the trivial top_y/bottom_y threshold check with horizontal
projection gap analysis that finds large whitespace gaps separating
header/footer content from the main body. This correctly detects
headers (e.g. "VOCABULARY" banners) and footers (page numbers) even
when _find_content_bounds includes them in the content area.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The ocr_pipeline_api.py code path called classify_column_types without
left_x/right_x, so margin regions were never created. Also add logging
to _build_margin_regions for debugging.
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>
- Stream LLM review results batch-by-batch (8 entries per batch) via SSE
- Frontend shows live progress bar, batch log, and corrections appearing
- Skip entries with IPA phonetic transcriptions (already dictionary-corrected)
- Refactor llm_review_entries into reusable helpers for both streaming and non-streaming paths
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add /no_think tag to prompt (qwen3 thinking mode causes massive slowdown)
- Increase httpx timeout from 120s to 300s for large vocab tables
- Improve error logging with traceback and exception type
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>
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>
