Refactor image processing in app.py

app.py

@@ -79,10 +79,9 @@ with gr.Blocks(css=css) as demo:
         # image = torch.from_numpy(image).unsqueeze(0).to(DEVICE)
 
         image = torch.from_numpy(image.transpose((2, 0, 1))).to(DEVICE)
-        image = torch.from_numpy(image.transpose((2, 0, 1)))
         image = Normalize(mean=[0.485, 0.456, 0.406], std=[
             0.229, 0.224, 0.225])(image)
-        image = torch.autograd.Variable(image.unsqueeze(0).cuda())
+        image = torch.autograd.Variable(image.unsqueeze(0).to(DEVICE))
 
         depth = predict_depth(model, image)
         depth = F.interpolate(depth[None], (h, w),