debug: add detailed skip-reason logging to graphic detection

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

klausur-service/backend/cv_graphic_detect.py

@@ -264,19 +264,28 @@ def detect_graphic_elements(
 
     # --- 5. Analyse and classify ---
     candidates: List[GraphicElement] = []
+    skip_reasons: Dict[str, int] = {}
     for cnt in contours:
         area = cv2.contourArea(cnt)
         if area < min_area or area > max_area:
+            bx, by, bw, bh = cv2.boundingRect(cnt)
+            reason = f"area={int(area)}<{min_area}" if area < min_area else f"area={int(area)}>{max_area}"
+            logger.debug("GraphicDetect SKIP: %s at (%d,%d) %dx%d", reason, bx, by, bw, bh)
+            skip_reasons[f"area_filter"] = skip_reasons.get("area_filter", 0) + 1
             continue
 
         bx, by, bw, bh = cv2.boundingRect(cnt)
         if bw < 8 or bh < 8:
+            skip_reasons["too_small_dim"] = skip_reasons.get("too_small_dim", 0) + 1
             continue
 
         # Skip elements that overlap significantly with the exclusion zone
         roi_excl = exclusion[by:by + bh, bx:bx + bw]
         excl_ratio = np.sum(roi_excl > 0) / (bw * bh) if bw * bh > 0 else 0
         if excl_ratio > 0.4:
+            logger.debug("GraphicDetect SKIP excl_ratio=%.2f at (%d,%d) %dx%d area=%d",
+                         excl_ratio, bx, by, bw, bh, int(area))
+            skip_reasons["excl_overlap"] = skip_reasons.get("excl_overlap", 0) + 1
             continue
 
         # Classify shape
@@ -284,6 +293,9 @@ def detect_graphic_elements(
 
         # Skip noise (too small or text-like)
         if shape == "noise":
+            logger.debug("GraphicDetect SKIP noise at (%d,%d) %dx%d area=%d",
+                         bx, by, bw, bh, int(area))
+            skip_reasons["noise"] = skip_reasons.get("noise", 0) + 1
             continue
 
         # Determine dominant color
@@ -304,6 +316,10 @@ def detect_graphic_elements(
             contour=cnt,
         ))
 
+    if skip_reasons:
+        logger.info("GraphicDetect: skipped contours: %s",
+                     ", ".join(f"{k}={v}" for k, v in sorted(skip_reasons.items())))
+
     # Sort by area descending, limit count
     candidates.sort(key=lambda g: g.area, reverse=True)
     result = candidates[:max_elements]