Update app.py

app.py

@@ -15,6 +15,18 @@ dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 pipeline = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=dtype, device_map="balanced")
 pipeline.load_ip_adapter("h94/IP-Adapter", subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
 
+def prepare_image(image_path_or_url):
+    # Load the image
+    image = load_image(image_path_or_url)
+    
+    # Convert to tensor and move to correct device and dtype
+    transform = transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Resize((1024, 1024), interpolation=transforms.InterpolationMode.LANCZOS)
+    ])
+    image_tensor = transform(image).unsqueeze(0)  # Add batch dimension
+    return image_tensor.to(device=device, dtype=dtype)
+
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, 2000)
@@ -47,7 +59,7 @@ def create_image(image_pil,
             }
         pipeline.set_ip_adapter_scale(scale)
 
-    style_image = load_image(image_pil)
+    style_image = prepare_image(image_pil)
     generator = torch.Generator(device=device).manual_seed(randomize_seed_fn(seed, False))
     
     image = pipeline(