final?

app.py

@@ -32,15 +32,9 @@ model.load_state_dict(torch.hub.load_state_dict_from_url(model_path))
 model.eval()
 
 # Gradio preprocessing and prediction pipeline
-def predict_digit(image_dict):
-    # Extract the image from the 'image' key in the dictionary (if it exists)
-    if isinstance(image_dict, dict) and "image" in image_dict:
-        image = image_dict["image"]  # Access the image data
-    else:
-        raise ValueError("Invalid input format")
-
-    # Convert the image (numpy array) to a PIL Image
-    image = Image.fromarray(np.array(image)).convert('L')  # Convert to grayscale
+def predict_digit(image):
+    # Directly handle the numpy array from gr.Sketchpad
+    image = Image.fromarray(image).convert('L')  # Convert to grayscale
 
     # Preprocess: resize to 28x28 and normalize
     transform = transforms.Compose([