Changed l2_distance to np/linalg.norm for distance calculation

demos/place_recognition_demo/python/place_recognition_demo/common.py

@@ -38,14 +38,3 @@ def crop_resize(image, input_size):
     image = cv2.resize(image, (input_size[1], input_size[0]))
     image = np.expand_dims(image, axis=0)
     return image
-
-
-def l2_distance(query_embedding, gallery_embedding):
-    query_embedding = np.array(query_embedding)
-    gallery_embedding = np.array(gallery_embedding)
-    distance = (
-        np.sum(query_embedding ** 2, axis=1, keepdims=True)
-        + np.sum(gallery_embedding ** 2, axis=1)
-        - 2 * np.dot(query_embedding, gallery_embedding.transpose())
-    )
-    return distance

demos/place_recognition_demo/python/place_recognition_demo/place_recognition.py

@@ -19,7 +19,7 @@
 import cv2
 from tqdm import tqdm
 
-from place_recognition_demo.common import crop_resize, l2_distance
+from place_recognition_demo.common import crop_resize
 
 from openvino.inference_engine import IECore # pylint: disable=no-name-in-module
 
@@ -66,8 +66,10 @@ def compute_embedding(self, image):
     def search_in_gallery(self, embedding):
         ''' Takes input embedding vector and searches it in the gallery. '''
 
-        distances = l2_distance(embedding, self.embeddings)
-        distances = distances.reshape([-1])
+        query_embedding = np.array(embedding)
+        gallery_embeddings = np.array(self.embeddings)
+        distances = np.array([np.linalg.norm(query_embedding - np.expand_dims(gallery_embedding, axis=0), ord=2)
+                              for gallery_embedding in gallery_embeddings])
         sorted_indexes = np.argsort(distances)
         return sorted_indexes, distances