贴边 + 过小框过滤

core/detect_plate_process.py

@@ -50,6 +50,25 @@ def _load_filter_names(config):
     return {str(n).strip() for n in (names or []) if str(n).strip()}
 
 
+def _load_edge_filter_params(config):
+    """贴边/过小框过滤参数；可用 Config 覆盖，否则读 settings。"""
+    def _get(name, default):
+        if hasattr(config, name):
+            return getattr(config, name)
+        try:
+            from dao import settings as S
+            return getattr(S, name, default)
+        except Exception:
+            return default
+
+    return {
+        "edge_margin": int(_get("DISH_DETECT_EDGE_MARGIN_PX", 8)),
+        "edge_min_area_ratio": float(_get("DISH_DETECT_EDGE_MIN_AREA_RATIO", 0.02)),
+        "edge_min_side": int(_get("DISH_DETECT_EDGE_MIN_SIDE_PX", 48)),
+        "min_area_ratio": float(_get("DISH_DETECT_MIN_AREA_RATIO", 0.008)),
+    }
+
+
 class YOLOv11PlateExtractor:
     def __init__(self, config):
         self.config = config
@@ -64,10 +83,18 @@ class YOLOv11PlateExtractor:
         except Exception:
             pass
         self.filter_class_names = _load_filter_names(config)
+        self.edge_filter = _load_edge_filter_params(config)
         print(f"✅ Plate 模型加载成功: {weights}")
         print(f"[OK] detect classes: {self.config.LABEL_NAMES}")
         if self.filter_class_names:
             print(f"[OK] detect filter drop: {sorted(self.filter_class_names)}")
+        ef = self.edge_filter
+        print(
+            f"[OK] edge/small box filter: margin={ef['edge_margin']}px "
+            f"edge_area<{ef['edge_min_area_ratio']:.3f} "
+            f"edge_side<{ef['edge_min_side']} "
+            f"min_area<{ef['min_area_ratio']:.3f}"
+        )
 
     def predict(self, source):
         """source 可为图片路径或 BGR ndarray。"""
@@ -92,8 +119,42 @@ class YOLOv11PlateExtractor:
             return False
         return name in self.filter_class_names
 
-    def iter_kept_detections(self, results):
+    def _should_drop_incomplete_box(self, box, img_w, img_h):
-        """产出保留的检测框：(box, conf, class_name)。手/空盘等已过滤。"""
+        """贴边且过小 / 面积过小 → 视为入画不完整，丢弃。"""
+        try:
+            x1, y1, x2, y2 = [float(v) for v in box[:4]]
+        except Exception:
+            return True
+        bw = max(0.0, x2 - x1)
+        bh = max(0.0, y2 - y1)
+        if bw <= 1 or bh <= 1 or img_w <= 0 or img_h <= 0:
+            return True
+        area_ratio = (bw * bh) / float(img_w * img_h)
+        ef = self.edge_filter or {}
+        min_area = float(ef.get("min_area_ratio") or 0)
+        if min_area > 0 and area_ratio < min_area:
+            return True
+
+        margin = max(0, int(ef.get("edge_margin") or 0))
+        touches = (
+            x1 <= margin
+            or y1 <= margin
+            or x2 >= (img_w - 1 - margin)
+            or y2 >= (img_h - 1 - margin)
+        )
+        if not touches:
+            return False
+        edge_area = float(ef.get("edge_min_area_ratio") or 0)
+        edge_side = int(ef.get("edge_min_side") or 0)
+        # 贴边且「面积小」或「短边过短」→ 多半是只露一角
+        if edge_area > 0 and area_ratio < edge_area:
+            return True
+        if edge_side > 0 and min(bw, bh) < edge_side:
+            return True
+        return False
+
+    def iter_kept_detections(self, results, image_shape=None):
+        """产出保留的检测框：(box, conf, class_name)。类别/贴边不完整已过滤。"""
         if results is None or results.boxes is None:
             return
         boxes = results.boxes.xyxy.cpu().numpy()
@@ -102,20 +163,29 @@ class YOLOv11PlateExtractor:
             clss = results.boxes.cls.cpu().numpy()
         else:
             clss = [0] * len(boxes)
-        dropped = 0
+        img_h = img_w = None
+        if image_shape is not None and len(image_shape) >= 2:
+            img_h, img_w = int(image_shape[0]), int(image_shape[1])
+        dropped_cls = 0
+        dropped_edge = 0
         for box, conf, cls_id in zip(boxes, confs, clss):
             cname = self._class_name(results, cls_id)
             if self._should_drop_class(cname):
-                dropped += 1
+                dropped_cls += 1
+                continue
+            if img_w and img_h and self._should_drop_incomplete_box(box, img_w, img_h):
+                dropped_edge += 1
                 continue
             yield box, float(conf), cname
-        if dropped:
+        if dropped_cls:
-            print(f"[detect] filtered {dropped} box(es) in {sorted(self.filter_class_names)}")
+            print(f"[detect] filtered {dropped_cls} box(es) by class {sorted(self.filter_class_names)}")
+        if dropped_edge:
+            print(f"[detect] filtered {dropped_edge} incomplete/edge box(es)")
 
     def crop_plate(self, image, results):
         cropped_regions = []
         h, w = image.shape[:2]
-        for box, conf, cname in self.iter_kept_detections(results):
+        for box, conf, cname in self.iter_kept_detections(results, image_shape=image.shape):
             x1, y1, x2, y2 = map(int, box)
             x1 = max(0, x1)
             y1 = max(0, y1)
@@ -197,7 +267,7 @@ class YOLOv11PlateExtractor:
         """
         img = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
         font = self._load_font()
-        kept = list(self.iter_kept_detections(results))
+        kept = list(self.iter_kept_detections(results, image_shape=image.shape))
         for i, (box, conf, cname) in enumerate(kept):
             if labels is not None and i < len(labels):
                 text = str(labels[i])

dao/settings.py

@@ -130,6 +130,15 @@ DISH_DETECT_FILTER_NAMES = [
     x.strip() for x in os.environ.get('DISH_DETECT_FILTER_NAMES', '手,空盘').split(',')
     if x.strip()
 ]
+# 贴边不完整框过滤：托盘刚入画只露一角时 YOLO 常会检出，直接丢弃
+# 框任一边缘距画面边界 ≤ margin 像素，视为贴边
+DISH_DETECT_EDGE_MARGIN_PX = int(os.environ.get('DISH_DETECT_EDGE_MARGIN_PX', '8'))
+# 贴边且框面积占整图比例低于此值 → 丢弃（默认 2%）
+DISH_DETECT_EDGE_MIN_AREA_RATIO = float(os.environ.get('DISH_DETECT_EDGE_MIN_AREA_RATIO', '0.02'))
+# 贴边且框较短边像素低于此值 → 丢弃
+DISH_DETECT_EDGE_MIN_SIDE_PX = int(os.environ.get('DISH_DETECT_EDGE_MIN_SIDE_PX', '48'))
+# 任意框（不论是否贴边）面积占比低于此值也丢弃；0=关闭
+DISH_DETECT_MIN_AREA_RATIO = float(os.environ.get('DISH_DETECT_MIN_AREA_RATIO', '0.008'))
 
 # 用本地视频文件夹代替相机实时流（调试/回放，主要给海康入口用）。
 # 1=读 DISH_VIDEO_SOURCE_DIR，0=读相机。usb_camera_app 固定读 USB 相机，不受此项影响。