室内导盲增加数据集

workflow_indoor.py

@@ -30,24 +30,27 @@ CLASS_CORRIDOR = 1
 CLASS_SIDEWALK = 2
 
 # 静态障碍物 (家具 + 杂物)
-OBSTACLE_CLASSES = {3, 4, 5, 11, 12, 14, 15, 16, 17, 18, 19}
+OBSTACLE_CLASSES = {3, 4, 5, 11, 12, 14, 15, 16, 17, 18}
 CLASS_CHAIR = 3
 CLASS_TABLE = 4
 CLASS_SOFA_BED = 5
 CLASS_CABINET = 11
 CLASS_TRASH_CAN = 12
-CLASS_CUP_BOTTLE = 14
-CLASS_BAG = 15
-CLASS_ELECTRONICS = 16
-CLASS_PLANT = 17
-CLASS_CLOCK = 18
-CLASS_OBSTACLE = 19
+CLASS_TRASH_CAN = 12
+# CLASS_CUP_BOTTLE = 14 (Removed)
+CLASS_BAG = 14
+CLASS_ELECTRONICS = 15
+CLASS_PLANT = 16
+CLASS_OBSTACLE = 17
+CLASS_APPLIANCE = 18
 
 # 兴趣点
-POI_CLASSES = {6, 7, 8}  # door, elevator, stairs
+POI_CLASSES = {6, 7, 8, 19, 20}  # door, elevator, stairs, toilet, sink
 CLASS_DOOR = 6
 CLASS_ELEVATOR = 7
 CLASS_STAIRS = 8
+CLASS_TOILET = 19
+CLASS_SINK = 20
 
 # 边界
 BOUNDARY_CLASSES = {9, 10}  # wall, window
@@ -63,22 +66,31 @@ CLASS_NAMES = {
     3: 'chair', 4: 'table', 5: 'sofa_bed',
     6: 'door', 7: 'elevator', 8: 'stairs',
     9: 'wall', 10: 'window', 11: 'cabinet',
-    12: 'trash_can', 13: 'person', 14: 'cup_bottle',
-    15: 'bag', 16: 'electronics', 17: 'plant',
-    18: 'clock', 19: 'obstacle'
+    12: 'trash_can', 13: 'person',
+    14: 'bag', 15: 'electronics', 16: 'plant',
+    17: 'obstacle', 18: 'appliance',
+    19: 'toilet', 20: 'sink',
+    21: 'tableware'
 }
 
+
 # 中文名称（用于语音）
 CLASS_NAMES_CN = {
     0: '地面', 1: '走廊', 2: '人行道',
     3: '椅子', 4: '桌子', 5: '沙发',
     6: '门', 7: '电梯', 8: '楼梯',
     9: '墙壁', 10: '窗户', 11: '柜子',
-    12: '垃圾桶', 13: '行人', 14: '杯子瓶子',
-    15: '包', 16: '电子设备', 17: '绿植',
-    18: '时钟', 19: '障碍物'
+    12: '垃圾桶', 13: '行人',
+    14: '包', 15: '电子设备', 16: '绿植',
+    17: '障碍物', 18: '家电',
+    19: '卫生间', 20: '洗手台',
+    21: '餐具'
 }
 
+# 物品类 (不播报，除非寻找模式)
+ITEM_CLASSES = {21}
+CLASS_TABLEWARE = 21
+
 # ========== 配置参数 ==========
 CONF_THRESHOLD = float(os.getenv('INDOOR_CONF_THRESHOLD', '0.25'))
 WALKABLE_MIN_AREA = int(os.getenv('INDOOR_WALKABLE_MIN_AREA', '3000'))
@@ -259,10 +271,15 @@ class IndoorNavigator:
                 masks = r0.masks.data.cpu().numpy()
                 boxes = r0.boxes
                 
-                for i, (mask, cls_id, conf) in enumerate(zip(masks, boxes.cls, boxes.conf)):
                     cls_id = int(cls_id.item())
                     conf_val = float(conf.item())
                     
+                    # 过滤物品类 (默认不参与导航逻辑，防止刷屏)
+                    if cls_id in ITEM_CLASSES:
+                         # 可以选择存入特定的 items 列表供"找东西"功能使用
+                         # 这里暂时忽略，避免干扰避障
+                         continue
+                         
                     # 调整 mask 尺寸
                     mask_resized = cv2.resize(mask, (w, h), interpolation=cv2.INTER_NEAREST)
                     mask_bin = (mask_resized > 0.5).astype(np.uint8)
@@ -430,8 +447,8 @@ class IndoorNavigator:
                 if cy > h * 0.5:  # 比较近
                     return f"注意前方有{name_cn}"
             
-            # 门/电梯提示
-            elif cls_id in (CLASS_DOOR, CLASS_ELEVATOR):
+            # 门/电梯/卫生间/洗手台提示
+            elif cls_id in (CLASS_DOOR, CLASS_ELEVATOR, CLASS_TOILET, CLASS_SINK):
                 if cy > h * 0.3:  # 在视野内
                     position = "左侧" if cx < w * 0.4 else ("右侧" if cx > w * 0.6 else "前方")
                     return f"{position}有{name_cn}"