diff --git a/api/models.py b/api/models.py
index 12afb59..b39b176 100644
--- a/api/models.py
+++ b/api/models.py
@@ -18,9 +18,9 @@ class Comic(models.Model):
 
     @classmethod
     def create_from_nparray(cls, nparray_file, video):
+        if nparray_file.max() <= 1:
+            nparray_file = (nparray_file * 255).astype(int)
         tmp_name = uuid.uuid4()
-        if not os.path.exists(f"{settings.TMP_DIR}"):
-            os.makedirs(f"{settings.TMP_DIR}")
         cv2.imwrite(f"{settings.TMP_DIR}{tmp_name}.png", nparray_file)
         with open(f"{settings.TMP_DIR}{tmp_name}.png", mode="rb") as tmp_file:
             comic_image = File(tmp_file, name=f"{tmp_name}.png")
diff --git a/comic_layout/comic_layout.py b/comic_layout/comic_layout.py
index 9a9842e..af478a1 100644
--- a/comic_layout/comic_layout.py
+++ b/comic_layout/comic_layout.py
@@ -14,10 +14,10 @@ class LayoutGenerator():
 
         second_row = cv2.resize(second_row,
                                 (first_row.shape[1],
-                                 int(second_row.shape[0] * first_row.shape[1] / second_row.shape[1])))
+                                 (second_row.shape[0] * first_row.shape[1]) // second_row.shape[1]))
         fourth_row = cv2.resize(fourth_row,
                                 (first_row.shape[1],
-                                 int(fourth_row.shape[0] * first_row.shape[1] / fourth_row.shape[1])))
+                                 (fourth_row.shape[0] * first_row.shape[1]) // fourth_row.shape[1]))
 
         return np.vstack([first_row, second_row, third_row, fourth_row])
 
@@ -25,6 +25,6 @@ class LayoutGenerator():
     def _pad_images(frames):
         padded_result_imgs = []
         for img in frames:
-            padded_img = cv2.copyMakeBorder(img, 10, 10, 10, 10, cv2.BORDER_CONSTANT, value=(255, 255, 255))
+            padded_img = cv2.copyMakeBorder(img, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=(1, 1, 1))
             padded_result_imgs.append(padded_img)
         return padded_result_imgs
diff --git a/keyframes/keyframes.py b/keyframes/keyframes.py
index d12695b..99830f9 100644
--- a/keyframes/keyframes.py
+++ b/keyframes/keyframes.py
@@ -39,10 +39,9 @@ class KeyFramesExtractor():
     @staticmethod
     def _get_frames_with_interval(interval, all_keyframes):
         chosen_frames = []
-        chosen_frames_tmp_dir = uuid.uuid4()
-        os.mkdir(jj(f"{settings.TMP_DIR}", f"{chosen_frames_tmp_dir}"))
 
         for i in range(settings.NUMBERS_OF_FRAMES_TO_SHOW):
             frame = cv2.imread(all_keyframes[(i + 1) * interval])
             chosen_frames.append(frame)
+
         return chosen_frames
diff --git a/style_transfer/style_transfer.py b/style_transfer/style_transfer.py
index 6c30aff..c0b2fc9 100644
--- a/style_transfer/style_transfer.py
+++ b/style_transfer/style_transfer.py
@@ -18,7 +18,7 @@ class StyleTransfer():
 
     @staticmethod
     def _cartoon_gan_stylize(frames, gpu=True, **kwargs):
-        style = kwargs.get("style", "Hosoda")
+        style = kwargs.get("style", "Hayao")
         resize = kwargs.get("resize", 450)
 
         # load pretrained model
@@ -38,10 +38,7 @@ class StyleTransfer():
             else:
                 w = resize
                 h = int(w * ratio)
-            input_image = cv2.resize(img, (w, h), interpolation=cv2.INTER_CUBIC)
-
-            # RGB -> BGR
-            input_image = input_image[:, :, [2, 1, 0]]
+            input_image = cv2.resize(img, (w, h))
             input_image = transforms.ToTensor()(input_image).unsqueeze(0)
 
             # preprocess, (-1, 1)
@@ -52,13 +49,13 @@ class StyleTransfer():
             output_image = model(input_image)
             output_image = output_image[0]
 
-            # BGR -> RGB
-            output_image = output_image[[2, 1, 0], :, :]
-
             # deprocess, (0, 1)
-            output_image = output_image.data.cpu().float() * 0.5 + 0.5
+            output_image = (output_image.data.cpu().float() * 0.5 + 0.5).numpy()
 
-            # switch channels and append image to result images
-            stylized_imgs.append(np.rollaxis(output_image.numpy(), 0, 3))
+            # switch channels -> (c, h, w) -> (h, w, c)
+            output_image = np.rollaxis(output_image, 0, 3)
+
+            # append image to result images
+            stylized_imgs.append(output_image)
 
         return stylized_imgs