fix torch jit

app.py

@@ -14,7 +14,7 @@ dino_v2_image_processor = AutoImageProcessor.from_pretrained("./dinov2-large")
 
 # Provide a sample input for tracing
 sample_input = dino_v2_image_processor(
-    images=Image.new("RGB", (64, 64)), return_tensors="pt"
+    images=Image.new("RGB", (224, 224)), return_tensors="pt"
 ).to(torch_device)
 traced_dino_v2_model = torch.jit.trace(dino_v2_model, sample_input["pixel_values"])
 
@@ -35,15 +35,15 @@ def process_image(image):
     if image.mode != "RGB":
         image = image.convert("RGB")
 
-    # Resize to 64px while maintaining aspect ratio
+    # Resize to 224px while maintaining aspect ratio
     width, height = image.size
     if width < height:
-        w_percent = 64 / float(width)
-        new_width = 64
+        w_percent = 224 / float(width)
+        new_width = 224
         new_height = int(float(height) * float(w_percent))
     else:
-        h_percent = 64 / float(height)
-        new_height = 64
+        h_percent = 224 / float(height)
+        new_height = 224
         new_width = int(float(width) * float(h_percent))
     image = image.resize((new_width, new_height), Image.LANCZOS)