Change all predicted results as refined RGBA images. Fix a typo in device specification.

app.py

@@ -6,7 +6,7 @@ import gradio as gr
 import spaces
 
 from glob import glob
-from typing import Optional, Tuple
+from typing import Tuple
 
 from PIL import Image
 from gradio_imageslider import ImageSlider
@@ -58,16 +58,10 @@ def FB_blur_fusion_foreground_estimator(image, F, B, alpha, r=90):
     return F, blurred_B
 
 
-def array_to_pil_image(image: np.ndarray, size: Tuple[int, int] = (1024, 1024)) -> Image.Image:
-    image = cv2.resize(image, size, interpolation=cv2.INTER_LINEAR)
-    image = Image.fromarray(image).convert('RGB')
-    return image
-
-
 class ImagePreprocessor():
     def __init__(self, resolution: Tuple[int, int] = (1024, 1024)) -> None:
         self.transform_image = transforms.Compose([
-            # transforms.Resize(resolution),    # 1. keep consistent with the cv2.resize used in training 2. redundant with that in path_to_image()
+            transforms.Resize(resolution),    # 1. keep consistent with the cv2.resize used in training 2. redundant with that in path_to_image()
             transforms.ToTensor(),
             transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
         ])