fix: Sub-Session Zeilenerkennung nutzt Word-Grouping statt Gap-Detection

Gap-basierte Erkennung findet bei kleinen Box-Bildern zu wenige Gaps
und mergt Zeilen (7 raw gaps -> 4 validated -> nur 3 rows statt 6).
Sub-Sessions nutzen jetzt direkt _build_rows_from_word_grouping(),
das Woerter nach Y-Position clustert — robuster fuer komplexe Box-Layouts.

Zusaetzlich: alle zones=None Crashes gefixt (replace_all .get("zones") or []).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

klausur-service/backend/ocr_pipeline_api.py

@@ -419,7 +419,7 @@ async def create_box_sessions(session_id: str):
     if not column_result:
         raise HTTPException(status_code=400, detail="Column detection must be completed first")
 
-    zones = column_result.get("zones", [])
+    zones = column_result.get("zones") or []
     box_zones = [z for z in zones if z.get("zone_type") == "box" and z.get("box")]
     if not box_zones:
         return {"session_id": session_id, "sub_sessions": [], "message": "No boxes detected"}
@@ -1532,7 +1532,7 @@ async def _get_columns_overlay(session_id: str) -> Response:
     cv2.addWeighted(overlay, 0.2, img, 0.8, 0, img)
 
     # Draw detected box boundaries as dashed rectangles
-    zones = column_result.get("zones", [])
+    zones = column_result.get("zones") or []
     for zone in zones:
         if zone.get("zone_type") == "box" and zone.get("box"):
             box = zone["box"]
@@ -1600,6 +1600,21 @@ async def detect_rows(session_id: str):
     # Read zones from column_result to exclude box regions
     session = await get_session_db(session_id)
     column_result = (session or {}).get("column_result") or {}
+    is_sub_session = bool((session or {}).get("parent_session_id"))
+
+    # Sub-sessions (box crops): use word-grouping instead of gap-based
+    # row detection.  Box images are small with complex internal layouts
+    # (headings, sub-columns) where the horizontal projection approach
+    # merges rows.  Word-grouping directly clusters words by Y proximity,
+    # which is more robust for these cases.
+    if is_sub_session and word_dicts:
+        from cv_layout import _build_rows_from_word_grouping
+        rows = _build_rows_from_word_grouping(
+            word_dicts, left_x, right_x, top_y, bottom_y,
+            right_x - left_x, bottom_y - top_y,
+        )
+        logger.info(f"OCR Pipeline: sub-session {session_id}: word-grouping found {len(rows)} rows")
+    else:
         zones = column_result.get("zones") or []  # zones can be None for sub-sessions
 
         # Collect box y-ranges for filtering
@@ -1677,6 +1692,7 @@ async def detect_rows(session_id: str):
 
     # Assign zone_index based on which content zone each row falls in
     # Build content zone list with indices
+    zones = column_result.get("zones") or []
     content_zones = [(i, z) for i, z in enumerate(zones) if z.get("zone_type") == "content"] if zones else []
 
     # Build serializable result (exclude words to keep payload small)
@@ -1909,7 +1925,7 @@ async def detect_words(
             row.word_count = len(row.words)
 
     # Exclude rows that fall within box zones
-    zones = column_result.get("zones", [])
+    zones = column_result.get("zones") or []
     box_ranges = []
     for zone in zones:
         if zone.get("zone_type") == "box" and zone.get("box"):
@@ -2676,7 +2692,7 @@ async def get_fabric_json(session_id: str):
     subs = await get_sub_sessions(session_id)
     if subs:
         column_result = session.get("column_result") or {}
-        zones = column_result.get("zones", [])
+        zones = column_result.get("zones") or []
         box_zones = [z for z in zones if z.get("zone_type") == "box" and z.get("box")]
 
         for sub in subs:
@@ -2733,7 +2749,7 @@ async def get_merged_vocab_entries(session_id: str):
     subs = await get_sub_sessions(session_id)
     if subs:
         column_result = session.get("column_result") or {}
-        zones = column_result.get("zones", [])
+        zones = column_result.get("zones") or []
         box_zones = [z for z in zones if z.get("zone_type") == "box" and z.get("box")]
 
         for sub in subs:
@@ -3289,7 +3305,7 @@ async def _get_rows_overlay(session_id: str) -> Response:
 
     # Draw zone separator lines if zones exist
     column_result = session.get("column_result") or {}
-    zones = column_result.get("zones", [])
+    zones = column_result.get("zones") or []
     if zones:
         img_w_px = img.shape[1]
         zone_color = (0, 200, 255)  # Yellow (BGR)
@@ -3445,7 +3461,7 @@ async def _get_words_overlay(session_id: str) -> Response:
 
     # Red semi-transparent overlay for box zones
     column_result = session.get("column_result") or {}
-    zones = column_result.get("zones", [])
+    zones = column_result.get("zones") or []
     _draw_box_exclusion_overlay(img, zones)
 
     success, result_png = cv2.imencode(".png", img)