resize output image

app.py

@@ -10,7 +10,7 @@ pb = 'dmt.pb'
 style_dim = 8
 img_size=256
 
-model_scale = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=3)
+model_scale = EdsrModel.from_pretrained('eugenesiow/edsr-base', scale=2)
 
 def preprocess(img):
   return (img / 255. - 0.5) * 2
@@ -47,7 +47,7 @@ def inference(A,B):
   image = Image.fromarray(output)
   inputs = ImageLoader.load_image(image)
   preds = model_scale(inputs)
-  ImageLoader.save_image(preds, 'output/scaled_3x.png')
+  ImageLoader.save_image(preds, 'output/scaled_2x.png')
 
 
 
@@ -62,12 +62,8 @@ def makeupTransfer(arr1,arr2):
   no_makeup = "input/original.png"
   makeup = "input/ref.png"
   inference(no_makeup, makeup)
-  img = cv2.imread("output/scaled_3x.png")
-  h,w,_ = img.shape
-  h_new = 256
-  w_new = int((256/h)*w)
-  resize_img = cv2.resize(img,(w_new,h_new))
-  return cv2.cvtColor(resize_img, cv2.COLOR_BGR2RGB)
+  img = cv2.imread("output/scaled_2x.png")
+  return cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
 
 
 examples = [['faces/no_makeup/xfsy_0226.png', 'faces/makeup/XMY-136.png'],