diff --git a/deepdreamer/deepdreamer.py b/deepdreamer/deepdreamer.py
index e147d02..2522937 100644
--- a/deepdreamer/deepdreamer.py
+++ b/deepdreamer/deepdreamer.py
@@ -23,20 +23,20 @@
 
 def _select_network(netname):
     if netname == 'bvlc_googlenet':
-        NET_FN = "deploy.prototxt"  # Make sure force_backward: true
-        PARAM_FN = "bvlc_googlenet.caffemodel"
-        CHANNEL_SWAP = (2, 1, 0)
+        net_fn = "deploy.prototxt"  # Make sure force_backward: true
+        param_fn = "bvlc_googlenet.caffemodel"
+        channel_swap = (2, 1, 0)
         # ImageNet mean, training set dependent
-        CAFFE_MEAN = np.float32([104.0, 116.0, 122.0])
-        return NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN
+        caffe_mean = np.float32([104.0, 116.0, 122.0])
+        return net_fn, param_fn, channel_swap, caffe_mean
     elif netname == 'googlenet_place205':
         # TODO: refit SWAP and MEAN for places205? These work for now.
-        NET_FN = "deploy_places205.protxt"  # Make sure force_backward: true
-        PARAM_FN = "googlelet_places205_train_iter_2400000.caffemodel"
-        CHANNEL_SWAP = (2, 1, 0)
+        net_fn = "deploy_places205.protxt"  # Make sure force_backward: true
+        param_fn = "googlelet_places205_train_iter_2400000.caffemodel"
+        channel_swap = (2, 1, 0)
         # ImageNet mean, training set dependent
-        CAFFE_MEAN = np.float32([104.0, 116.0, 122.0])
-        return NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN
+        caffe_mean = np.float32([104.0, 116.0, 122.0])
+        return net_fn, param_fn, channel_swap, caffe_mean
     else:
         print("Error: network {} not implemented".format(netname))
 
@@ -138,9 +138,9 @@ def _create_video(video, frame_rate=24):
 
 def list_layers(network="bvlc_googlenet"):
     # Load DNN model
-    NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
+    net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
     net = Classifier(
-        NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
+        net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)
     net.blobs.keys()
 
 
@@ -159,9 +159,9 @@ def deepdream(
         set_mode_gpu()
 
     # Select, load DNN model
-    NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
+    net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
     net = Classifier(
-        NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
+        net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)
 
     img_pool = [img_path]
 
@@ -205,9 +205,9 @@ def deepdream_video(
         frame_rate=24):
 
     # Select, load DNN model
-    NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
+    net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
     net = Classifier(
-        NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
+        net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)
 
     print("Extracting video...")
     _extract_video(video)