optimize import numpy (#451)

Co-authored-by: zheng.shen <[email protected]>

face_recognition/face_recognition_manager.py

@@ -1,7 +1,6 @@
 import logging
 import time
 from datetime import datetime, timedelta
-import numpy as np
 import json
 
 from sqlalchemy.sql import text
@@ -104,6 +103,7 @@ def ensure_face_vectors(self, repo_id):
     def face_cluster(self, repo_id):
         try:
             from sklearn.cluster import HDBSCAN
+            import numpy as np
         except ImportError:
             logger.warning('Package scikit-learn is not installed. ')
             return

face_recognition/utils.py

@@ -2,7 +2,6 @@
 import os
 import posixpath
 
-import numpy as np
 from seaserv import seafile_api
 
 from seafevents.repo_metadata.utils import query_metadata_rows, get_file_content
@@ -19,18 +18,21 @@
 
 
 def feature_distance(feature1, feature2):
+    import numpy as np
     diff = np.subtract(feature1, feature2)
     dist = np.sum(np.square(diff), 0)
     return dist
 
 
 def b64encode_embeddings(embeddings):
+    import numpy as np
     embedding_array = np.array(embeddings).astype(np.float32)
     encode = base64.b64encode(embedding_array.tobytes())
     return encode.decode('utf-8')
 
 
 def b64decode_embeddings(encode):
+    import numpy as np
     decode = base64.b64decode(encode)
     embedding_array = np.frombuffer(decode, dtype=np.float32)
     face_num = len(embedding_array) // FACE_EMBEDDING_DIM