diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py
index a0d434b..c5620c3 100644
--- a/deepface/DeepFace.py
+++ b/deepface/DeepFace.py
@@ -219,19 +219,14 @@ def verify(img1_path, img2_path = '', model_name = 'VGG-Face', distance_metric =
 	#face recognition models have different size of inputs
 	#my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue.
 		
-	if model_name == 'Dlib': #this is not a regular keras model
-		input_shape = (150, 150, 3)
+	input_shape = model.layers[0].input_shape
 	
-	else: #keras based models
-		input_shape = model.layers[0].input_shape
-		
-		if type(input_shape) == list:
-			input_shape = input_shape[0][1:3]
-		else:
-			input_shape = input_shape[1:3]
-	  
-	input_shape_x = input_shape[0]
-	input_shape_y = input_shape[1]
+	if type(input_shape) == list:
+		input_shape = input_shape[0][1:3]
+	else:
+		input_shape = input_shape[1:3]
+	
+	input_shape_x = input_shape[0]; input_shape_y = input_shape[1]
 
 	#------------------------------
 
@@ -590,20 +585,15 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
 				employee = employees[index]
 				
 				if model_name != 'Ensemble':
-				
-					if model_name == 'Dlib': #non-keras model
-						input_shape = (150, 150, 3)
-					else:
-						#input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue.
-						
-						input_shape = model.layers[0].input_shape
-						
-						if type(input_shape) == list:
-							input_shape = input_shape[0][1:3]
-						else:
-							input_shape = input_shape[1:3]
 					
-					#---------------------
+					#input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue.
+					
+					input_shape = model.layers[0].input_shape
+					
+					if type(input_shape) == list:
+						input_shape = input_shape[0][1:3]
+					else:
+						input_shape = input_shape[1:3]
 					
 					input_shape_x = input_shape[0]; input_shape_y = input_shape[1]
 					
@@ -754,22 +744,19 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine',
 			
 			if model_name != 'Ensemble':
 				
-				if model_name == 'Dlib': #non-keras model
-					input_shape = (150, 150, 3)
-				else:
-					#input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue.
-					
-					input_shape = model.layers[0].input_shape
-					
-					if type(input_shape) == list:
-						input_shape = input_shape[0][1:3]
-					else:
-						input_shape = input_shape[1:3]
+				#input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue.
 				
-				#------------------------
+				input_shape = model.layers[0].input_shape
+				
+				if type(input_shape) == list:
+					input_shape = input_shape[0][1:3]
+				else:
+					input_shape = input_shape[1:3]
 				
 				input_shape_x = input_shape[0]; input_shape_y = input_shape[1]
 				
+				#------------------------
+				
 				img = functions.preprocess_face(img = img_path, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)
 				target_representation = model.predict(img)[0,:]
 		
diff --git a/deepface/basemodels/DlibResNet.py b/deepface/basemodels/DlibResNet.py
index 8e1c188..1a859db 100644
--- a/deepface/basemodels/DlibResNet.py
+++ b/deepface/basemodels/DlibResNet.py
@@ -9,6 +9,10 @@ from pathlib import Path
 class DlibResNet:
 	
 	def __init__(self):
+	
+		self.layers = [DlibMetaData()]
+		
+		#---------------------
 		
 		home = str(Path.home())
 		weight_file = home+'/.deepface/weights/dlib_face_recognition_resnet_model_v1.dat'
@@ -59,4 +63,8 @@ class DlibResNet:
 		img_representation = np.array(img_representation)
 		img_representation = np.expand_dims(img_representation, axis = 0)
 		
-		return img_representation
\ No newline at end of file
+		return img_representation
+
+class DlibMetaData:
+	def __init__(self):
+		self.input_shape = [[1, 150, 150, 3]]
\ No newline at end of file