diff --git a/ComixGAN/model.py b/ComixGAN/model.py
new file mode 100644
index 0000000..d0cba49
--- /dev/null
+++ b/ComixGAN/model.py
@@ -0,0 +1,22 @@
+import errno
+import os
+
+import tensorflow as tf
+from django.conf import settings
+from keras.models import load_model
+from keras_contrib.layers import InstanceNormalization
+
+
+class ComixGAN:
+    def __init__(self):
+        if not os.path.exists(settings.COMIX_GAN_MODEL_PATH):
+            raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), settings.COMIX_GAN_MODEL_PATH)
+        self.graph = tf.Graph()
+        config = tf.ConfigProto()
+        config.gpu_options.per_process_gpu_memory_fraction = 0.7
+        config.gpu_options.allow_growth = True
+        self.session = tf.Session(graph=self.graph, config=config)
+        with self.graph.as_default():
+            with tf.device('/GPU:0'):
+                self.model = load_model(settings.COMIX_GAN_MODEL_PATH,
+                                        custom_objects={'InstanceNormalization': InstanceNormalization})
diff --git a/ComixGAN/generator_model.h5 b/ComixGAN/pretrained_models/generator_model.h5
similarity index 77%
rename from ComixGAN/generator_model.h5
rename to ComixGAN/pretrained_models/generator_model.h5
index ebe0ee1..48c80dc 100644
Binary files a/ComixGAN/generator_model.h5 and b/ComixGAN/pretrained_models/generator_model.h5 differ
diff --git a/ComixGAN/pretrained_models/generator_model2.h5 b/ComixGAN/pretrained_models/generator_model2.h5
new file mode 100644
index 0000000..f5ca621
Binary files /dev/null and b/ComixGAN/pretrained_models/generator_model2.h5 differ
diff --git a/settings/settings.py b/settings/settings.py
index 609a644..c43e962 100644
--- a/settings/settings.py
+++ b/settings/settings.py
@@ -147,4 +147,4 @@ DEFAULT_RL_MODE = 0
 DEFAULT_IMAGE_ASSESSMENT_MODE = 0
 
 DEFAULT_STYLE_TRANSFER_MODE = 0
-COMIX_GAN_MODEL_PATH = os.path.join(BASE_DIR, 'ComixGAN', 'generator_model.h5')
+COMIX_GAN_MODEL_PATH = os.path.join(BASE_DIR, 'ComixGAN', 'pretrained_models', 'generator_model.h5')
diff --git a/style_transfer/style_transfer.py b/style_transfer/style_transfer.py
index 7d3a3eb..6750d36 100644
--- a/style_transfer/style_transfer.py
+++ b/style_transfer/style_transfer.py
@@ -1,32 +1,28 @@
-import gc
 import os
 
 import cv2
 import numpy as np
-import tensorflow as tf
 import torch
 import torchvision.transforms as transforms
 from django.conf import settings
 from django.core.cache import cache
-from keras import backend as K
-from keras.backend.tensorflow_backend import set_session
-from keras.models import load_model
-from keras_contrib.layers import InstanceNormalization
 from torch.autograd import Variable
 
 from CartoonGAN.network.Transformer import Transformer
+from ComixGAN.model import ComixGAN
 from utils import profile
 
-config = tf.ConfigProto()
-config.gpu_options.allow_growth = True  # dynamically grow the memory used on the GPU
-sess = tf.Session(config=config)
-set_session(sess)  # set this TensorFlow session as the default session for Keras.
+# load pretrained model
+comixGAN = ComixGAN()
 
 
 class StyleTransfer():
     @classmethod
     @profile
     def get_stylized_frames(cls, frames, style_transfer_mode=0, gpu=settings.GPU):
+        print(frames[0].shape)
+        print(frames[0].max())
+        print(frames[0].min())
         if style_transfer_mode == 0:
             return cls._comix_gan_stylize(frames=frames)
         elif style_transfer_mode == 1:
@@ -53,19 +49,17 @@ class StyleTransfer():
 
     @classmethod
     def _comix_gan_stylize(cls, frames):
-        # load pretrained model
-        comixGAN_model = load_model(settings.COMIX_GAN_MODEL_PATH,
-                                    custom_objects={'InstanceNormalization': InstanceNormalization})
         frames = cls._resize_images(frames, size=450)
-        batch_size = 2
-        stylized_imgs = []
-        for i in range(0, len(frames), batch_size):
-            batch_of_frames = np.stack(frames[i:i + batch_size]) / 255
-            stylized_batch_of_imgs = comixGAN_model.predict(batch_of_frames)
-            stylized_imgs.append(255 * stylized_batch_of_imgs)
-        K.clear_session()
-        del comixGAN_model
-        gc.collect()
+
+        with comixGAN.graph.as_default():
+            batch_size = 1
+            stylized_imgs = []
+            for i in range(0, len(frames), batch_size):
+                batch_of_frames = ((np.stack(frames[i:i + batch_size]) / 255) * 2) - 1
+                stylized_batch_of_imgs = comixGAN.model.predict(batch_of_frames)
+                stylized_imgs.append(255 * ((stylized_batch_of_imgs + 1) / 2))
+        # K.clear_session()
+        # gc.collect()
         return list(np.concatenate(stylized_imgs, axis=0))
 
     @classmethod