Restructure: Move ocr_pipeline + labeling + crop into ocr/ package

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

klausur-service/backend/ocr_pipeline_words.py

@@ -1,185 +1,4 @@
-"""
-OCR Pipeline Words — composite router for word detection, PaddleOCR direct,
-and ground truth endpoints.
-
-Split into sub-modules:
-  ocr_pipeline_words_detect  — main detect_words endpoint (Step 7)
-  ocr_pipeline_words_stream  — SSE streaming generators
-
-This barrel module contains the PaddleOCR direct endpoint and ground truth
-endpoints, and assembles all word-related routers.
-
-Lizenz: Apache 2.0
-DATENSCHUTZ: Alle Verarbeitung erfolgt lokal.
-"""
-
-import logging
-import time
-from datetime import datetime
-from typing import Any, Dict, List, Optional
-
-import cv2
-import numpy as np
-from fastapi import APIRouter, HTTPException
-from pydantic import BaseModel
-
-from cv_words_first import build_grid_from_words
-from ocr_pipeline_session_store import (
-    get_session_db,
-    get_session_image,
-    update_session_db,
-)
-from ocr_pipeline_common import (
-    _cache,
-    _append_pipeline_log,
-)
-from ocr_pipeline_words_detect import router as _detect_router
-
-logger = logging.getLogger(__name__)
-
-_local_router = APIRouter(prefix="/api/v1/ocr-pipeline", tags=["ocr-pipeline"])
-
-
-# ---------------------------------------------------------------------------
-# Pydantic models
-# ---------------------------------------------------------------------------
-
-class WordGroundTruthRequest(BaseModel):
-    is_correct: bool
-    corrected_entries: Optional[List[Dict[str, Any]]] = None
-    notes: Optional[str] = None
-
-
-# ---------------------------------------------------------------------------
-# PaddleOCR Direct Endpoint
-# ---------------------------------------------------------------------------
-
-@_local_router.post("/sessions/{session_id}/paddle-direct")
-async def paddle_direct(session_id: str):
-    """Run PaddleOCR on the preprocessed image and build a word grid directly."""
-    img_png = await get_session_image(session_id, "cropped")
-    if not img_png:
-        img_png = await get_session_image(session_id, "dewarped")
-    if not img_png:
-        img_png = await get_session_image(session_id, "original")
-    if not img_png:
-        raise HTTPException(status_code=404, detail="No image found for this session")
-
-    img_arr = np.frombuffer(img_png, dtype=np.uint8)
-    img_bgr = cv2.imdecode(img_arr, cv2.IMREAD_COLOR)
-    if img_bgr is None:
-        raise HTTPException(status_code=400, detail="Failed to decode original image")
-
-    img_h, img_w = img_bgr.shape[:2]
-
-    from cv_ocr_engines import ocr_region_paddle
-
-    t0 = time.time()
-    word_dicts = await ocr_region_paddle(img_bgr, region=None)
-    if not word_dicts:
-        raise HTTPException(status_code=400, detail="PaddleOCR returned no words")
-
-    cells, columns_meta = build_grid_from_words(word_dicts, img_w, img_h)
-    duration = time.time() - t0
-
-    for cell in cells:
-        cell["ocr_engine"] = "paddle_direct"
-
-    n_rows = len(set(c["row_index"] for c in cells)) if cells else 0
-    n_cols = len(columns_meta)
-    col_types = {c.get("type") for c in columns_meta}
-    is_vocab = bool(col_types & {"column_en", "column_de"})
-
-    word_result = {
-        "cells": cells,
-        "grid_shape": {"rows": n_rows, "cols": n_cols, "total_cells": len(cells)},
-        "columns_used": columns_meta,
-        "layout": "vocab" if is_vocab else "generic",
-        "image_width": img_w,
-        "image_height": img_h,
-        "duration_seconds": round(duration, 2),
-        "ocr_engine": "paddle_direct",
-        "grid_method": "paddle_direct",
-        "summary": {
-            "total_cells": len(cells),
-            "non_empty_cells": sum(1 for c in cells if c.get("text")),
-            "low_confidence": sum(1 for c in cells if 0 < c.get("confidence", 0) < 50),
-        },
-    }
-
-    await update_session_db(
-        session_id,
-        word_result=word_result,
-        cropped_png=img_png,
-        current_step=8,
-    )
-
-    logger.info(
-        "paddle_direct session %s: %d cells (%d rows, %d cols) in %.2fs",
-        session_id, len(cells), n_rows, n_cols, duration,
-    )
-
-    await _append_pipeline_log(session_id, "paddle_direct", {
-        "total_cells": len(cells),
-        "non_empty_cells": word_result["summary"]["non_empty_cells"],
-        "ocr_engine": "paddle_direct",
-    }, duration_ms=int(duration * 1000))
-
-    return {"session_id": session_id, **word_result}
-
-
-# ---------------------------------------------------------------------------
-# Ground Truth Words Endpoints
-# ---------------------------------------------------------------------------
-
-@_local_router.post("/sessions/{session_id}/ground-truth/words")
-async def save_word_ground_truth(session_id: str, req: WordGroundTruthRequest):
-    """Save ground truth feedback for the word recognition step."""
-    session = await get_session_db(session_id)
-    if not session:
-        raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
-
-    ground_truth = session.get("ground_truth") or {}
-    gt = {
-        "is_correct": req.is_correct,
-        "corrected_entries": req.corrected_entries,
-        "notes": req.notes,
-        "saved_at": datetime.utcnow().isoformat(),
-        "word_result": session.get("word_result"),
-    }
-    ground_truth["words"] = gt
-
-    await update_session_db(session_id, ground_truth=ground_truth)
-
-    if session_id in _cache:
-        _cache[session_id]["ground_truth"] = ground_truth
-
-    return {"session_id": session_id, "ground_truth": gt}
-
-
-@_local_router.get("/sessions/{session_id}/ground-truth/words")
-async def get_word_ground_truth(session_id: str):
-    """Retrieve saved ground truth for word recognition."""
-    session = await get_session_db(session_id)
-    if not session:
-        raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
-
-    ground_truth = session.get("ground_truth") or {}
-    words_gt = ground_truth.get("words")
-    if not words_gt:
-        raise HTTPException(status_code=404, detail="No word ground truth saved")
-
-    return {
-        "session_id": session_id,
-        "words_gt": words_gt,
-        "words_auto": session.get("word_result"),
-    }
-
-
-# ---------------------------------------------------------------------------
-# Composite router
-# ---------------------------------------------------------------------------
-
-router = APIRouter()
-router.include_router(_detect_router)
-router.include_router(_local_router)
+# Backward-compat shim -- module moved to ocr/pipeline/words.py
+import importlib as _importlib
+import sys as _sys
+_sys.modules[__name__] = _importlib.import_module("ocr.pipeline.words")