corrcected msitakes

backend/src/utils/cluster_manager.py

@@ -6,7 +6,7 @@ import numpy as np
 from sklearn.cluster import DBSCAN
 from pydantic import BaseModel
 
-from ..overpass.overpass import Overpass
+from ..overpass.overpass import Overpass, get_base_info
 from ..structs.landmark import Landmark
 from .get_time_distance import get_distance
 from ..constants import OSM_CACHE_DIR
@@ -116,17 +116,11 @@ class ClusterManager:
             points = []
             for osm_type in osm_types :
                 for elem in result.findall(osm_type):
-
-                    if osm_type != 'node' :
-                        center = elem.find('center')
-                        lat = float(center.get('lat'))
-                        lon = float(center.get('lon'))
-                        points.append(tuple((lat, lon)))
-
-                    else :
-                        lat = float(elem.get('lat'))
-                        lon = float(elem.get('lon'))
-                        points.append(tuple((lat, lon)))
+                    
+                    # Get coordinates and append them to the points list
+                    _, coords = get_base_info(elem, osm_type)
+                    if coords is not None :
+                        points.append(coords)
 
             if points :
                 self.all_points = np.array(points)
@@ -263,32 +257,18 @@ class ClusterManager:
 
             for osm_type in osm_types :
                 for elem in result.findall(osm_type):
-                    name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
-                    center = elem.find('center')
 
-                    # Extract the center latitude and longitude if available.
-                    if name is None :
-                        continue
+                    id, coords, name = get_base_info(elem, osm_type, with_name=True)
 
-                    if osm_type != 'node' :
-                        lat = float(center.get('lat'))
-                        lon = float(center.get('lon'))
-
-                    else :
-                        lat = float(elem.get('lat'))
-                        lon = float(elem.get('lon'))
-
-                    coords = tuple((lat, lon))
-
-                    if coords is None :
+                    if name is None or coords is None :
                         continue
 
                     d = get_distance(cluster.centroid, coords)
                     if  d < min_dist :
                         min_dist = d
                         new_name = name
-                        osm_type = osm_type         # Add type: 'way' or 'relation'
-                        osm_id = elem.get('id')     # Add OSM id
+                        osm_type = osm_type     # Add type: 'way' or 'relation'
+                        osm_id = id             # Add OSM id
 
         return Landmark(
             name=new_name,