Update app.py

app.py

@@ -9,13 +9,13 @@ model = torch.jit.load(model_path, map_location=torch.device('cpu'))
 model.eval()
 
 # Define a function to preprocess images to match the expected input shape
+
 def preprocess_image(image):
-    # Resize the image to a fixed size (e.g., 16x16) to match the expected input shape
-    image = image.resize((16, 16))
+    # Resize the image to a fixed size (e.g., 224x224)
+    image = image.resize((1024, 768))
 
-    # Convert to RGB and normalize pixel values
-    image = image.convert("RGB")
-    input_tensor = np.array(image) / 255.0
+    # Convert to RGB (without adding extra dimensions)
+    input_tensor = np.array(image.convert("RGB")) / 255.0
 
     # Add the batch dimension
     input_tensor = input_tensor[np.newaxis, :]