diff --git a/api/models.py b/api/models.py
index cddf2fe..5578d62 100644
--- a/api/models.py
+++ b/api/models.py
@@ -23,7 +23,7 @@ class Video(models.Model):
         yt_pafy = pafy.new(yt_url)
 
         # Use the biggest possible quality with file size < MAX_FILE_SIZE and resolution <= 480px
-        for stream in yt_pafy.videostreams:
+        for stream in reversed(yt_pafy.videostreams):
             if stream.get_filesize() < settings.MAX_FILE_SIZE and int(stream.quality.split("x")[1]) <= 480:
                 tmp_name = uuid.uuid4().hex + ".mp4"
                 relative_path = jj('raw_videos', tmp_name)
diff --git a/neural_image_assessment/model.py b/neural_image_assessment/model.py
index 44e1b0f..feead33 100644
--- a/neural_image_assessment/model.py
+++ b/neural_image_assessment/model.py
@@ -16,7 +16,7 @@ class NeuralImageAssessment:
             raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), settings.NIMA_MODEL_PATH)
         self.graph = tf.Graph()
         config = tf.ConfigProto()
-        config.gpu_options.per_process_gpu_memory_fraction = 0.2
+        config.gpu_options.per_process_gpu_memory_fraction = 0.8
         config.gpu_options.allow_growth = True
         self.session = tf.Session(graph=self.graph, config=config)
         with self.graph.as_default():
diff --git a/settings/settings.py b/settings/settings.py
index 9ab2cd1..84019b7 100644
--- a/settings/settings.py
+++ b/settings/settings.py
@@ -148,4 +148,6 @@ DEFAULT_IMAGE_ASSESSMENT_MODE = 0
 
 DEFAULT_STYLE_TRANSFER_MODE = 0
 COMIX_GAN_MODEL_PATH = os.path.join(BASE_DIR, 'ComixGAN', 'pretrained_models', 'generator_model.h5')
+MAX_FRAME_SIZE_FOR_STYLE_TRANSFER = 600
+
 NIMA_MODEL_PATH = os.path.join(BASE_DIR, 'neural_image_assessment', 'pretrained_model', 'nima_model.h5')
\ No newline at end of file
diff --git a/style_transfer/style_transfer.py b/style_transfer/style_transfer.py
index 2e68fb5..42ef6fc 100644
--- a/style_transfer/style_transfer.py
+++ b/style_transfer/style_transfer.py
@@ -46,18 +46,18 @@ class StyleTransfer():
 
     @classmethod
     def _comix_gan_stylize(cls, frames):
-        frames = cls._resize_images(frames, size=450)
+        if max(frames[0].shape) > settings.MAX_FRAME_SIZE_FOR_STYLE_TRANSFER:
+            frames = cls._resize_images(frames, size=settings.MAX_FRAME_SIZE_FOR_STYLE_TRANSFER)
 
         with comixGAN.graph.as_default():
             with comixGAN.session.as_default():
-                batch_size = 1
+                batch_size = 5
                 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()
+                    stylized_imgs.append(255 * ((stylized_batch_of_imgs + 1) / 1.25))
+
         return list(np.concatenate(stylized_imgs, axis=0))
 
     @classmethod