update

app.py

@@ -35,7 +35,7 @@ netscale = 4
 model_path = os.path.join('weights', 'realesr-general-x4v3.pth')
 
 # restorer
-upsampler = RealESRGANer(scale=netscale, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=True)
+upsampler = RealESRGANer(scale=netscale, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=False)
 
 # Use GFPGAN for face enhancement
 from gfpgan_utils import GFPGANer

gfpgan_utils.py

@@ -33,7 +33,7 @@ class GFPGANer():
         self.bg_upsampler = bg_upsampler
 
         # initialize model
-        self.device = torch.device('cuda') if device is None else device
+        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
         # initialize the GFP-GAN
         self.gfpgan = GFPGANv1Clean(
             out_size=512,

realesrgan_utils.py

@@ -36,7 +36,7 @@ class RealESRGANer():
         self.half = half
 
         # initialize model
-        self.device = torch.device('cuda')
+        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
         # if the model_path starts with https, it will first download models to the folder: realesrgan/weights
         if model_path.startswith('https://'):
             model_path = load_file_from_url(