Update app.py

app.py

@@ -81,12 +81,10 @@ def KNN_predict(train_features, train_labels, test_feature, K):
   label_record = []
   for i in range(len(train_features)):
     train_point_feature = train_features[i]
-    test_point_feature = test_feature
+    test_point_feature = test_feature.flatten()
     ### (1) calculate distance between test feature and each of training data points
 
-    # get distance for data point i 
-    print("train_point_feature: ",train_point_feature.shape)
-    print("test_point_feature: ",test_point_feature.shape)
+    # get distance for data point i
     dis = scipy.spatial.distance.euclidean(train_point_feature, test_point_feature)
     
     # collect lable for datapoint i