diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py
index 5441ba4..3f82141 100644
--- a/deepface/DeepFace.py
+++ b/deepface/DeepFace.py
@@ -145,23 +145,10 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
 				ensemble_features_string += "]"
 				
 				#-------------------------------
-				#find deepface path
+
+				deepface_ensemble = functions.boosting_method()
 				
-				home = str(Path.home())
-				
-				if os.path.isfile(home+'/.deepface/weights/face-recognition-ensemble-model.txt') != True:
-					print("face-recognition-ensemble-model.txt will be downloaded...")
-					url = 'https://raw.githubusercontent.com/serengil/deepface/master/deepface/models/face-recognition-ensemble-model.txt'
-					output = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
-					gdown.download(url, output, quiet=False)
-					
-				ensemble_model_path = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
-				
-				#print(ensemble_model_path)
-				
-				#-------------------------------
-				
-				deepface_ensemble = lgb.Booster(model_file = ensemble_model_path)
+				#---------------------------
 				
 				prediction = deepface_ensemble.predict(np.expand_dims(np.array(ensemble_features), axis=0))[0]
 				
@@ -680,18 +667,8 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
 				x = df[feature_names].values
 				
 				#----------------------------------
-				#lightgbm model
-				home = str(Path.home())
-				
-				if os.path.isfile(home+'/.deepface/weights/face-recognition-ensemble-model.txt') != True:
-					print("face-recognition-ensemble-model.txt will be downloaded...")
-					url = 'https://raw.githubusercontent.com/serengil/deepface/master/deepface/models/face-recognition-ensemble-model.txt'
-					output = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
-					gdown.download(url, output, quiet=False)
-					
-				ensemble_model_path = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
-				
-				deepface_ensemble = lgb.Booster(model_file = ensemble_model_path)
+				#lightgbm model				
+				deepface_ensemble = functions.boosting_method()
 				
 				y = deepface_ensemble.predict(x)
 				
diff --git a/deepface/commons/functions.py b/deepface/commons/functions.py
index 645ab83..89ba10e 100644
--- a/deepface/commons/functions.py
+++ b/deepface/commons/functions.py
@@ -447,3 +447,21 @@ def preprocess_face(img, target_size=(224, 224), grayscale = False, enforce_dete
 	img_pixels /= 255 #normalize input in [0, 1]
 	
 	return img_pixels
+
+def boosting_method():
+	
+	import lightgbm as lgb #lightgbm==2.3.1
+	
+	home = str(Path.home())
+	
+	if os.path.isfile(home+'/.deepface/weights/face-recognition-ensemble-model.txt') != True:
+		print("face-recognition-ensemble-model.txt will be downloaded...")
+		url = 'https://raw.githubusercontent.com/serengil/deepface/master/deepface/models/face-recognition-ensemble-model.txt'
+		output = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
+		gdown.download(url, output, quiet=False)
+		
+	ensemble_model_path = home+'/.deepface/weights/face-recognition-ensemble-model.txt'
+	
+	deepface_ensemble = lgb.Booster(model_file = ensemble_model_path)
+	
+	return deepface_ensemble
diff --git a/tests/unit_tests.py b/tests/unit_tests.py
index 1d01c3f..e5a02e8 100644
--- a/tests/unit_tests.py
+++ b/tests/unit_tests.py
@@ -242,19 +242,3 @@ print(df)
 #-----------------------------------
 print("--------------------------")
 
-print("Different face detector backends")
-
-backends = ['opencv', 'ssd', 'dlib', 'mtcnn']
-
-for backend in backends:
-	
-	tic = time.time()
-	
-	processed_img = functions.preprocess_face(img = "dataset/img11.jpg", detector_backend = backend)
-	
-	toc = time.time()
-	
-	print("Backend ", backend, " is done in ", toc-tic," seconds")
-
-#-----------------------------------
-print("--------------------------")