updated requirements

app.py

@@ -7,10 +7,15 @@ diffusers.Zero123Pipeline = Zero123Pipeline
 
 def generate_view(source_img, elevation, azimuth, camera_distance, num_inference_steps):
         
+    if torch.cuda.is_available():
+        device = 'cuda:0'
+    else:
+        device = 'cpu'
+
     # Prepare pipeline
     pipeline = DiffusionPipeline.from_pretrained("ashawkey/stable-zero123-diffusers",
                                                 torch_dtype=torch.float16, trust_remote_code=True)
-    pipeline.to('cuda:0')
+    pipeline.to(device)
 
     # Prepare input data:
     image = source_img.resize((256, 256)).convert("RGB")
@@ -18,9 +23,9 @@ def generate_view(source_img, elevation, azimuth, camera_distance, num_inference
 
     # Generate and save images:
     images = pipeline([image],
-                    torch.tensor([elevation], dtype=torch.float16).to('cuda:0'),
-                    torch.tensor([azimuth], dtype=torch.float16).to('cuda:0'),
-                    torch.tensor([camera_distance], dtype=torch.float16).to('cuda:0'),
+                    torch.tensor([elevation], dtype=torch.float16).to(device),
+                    torch.tensor([azimuth], dtype=torch.float16).to(device),
+                    torch.tensor([camera_distance], dtype=torch.float16).to(device),
                     num_inference_steps=int(num_inference_steps)).images
 
     return images[0]