Update app.py

app.py

@@ -4,7 +4,7 @@ import tensorflow as tf
 import cv2
 
 # Load the trained model
-model = tf.keras.models.load_model("Handwritten_model.h5")  # Adjust this if you use the SavedModel format
+model = tf.keras.models.load_model("Handwritten_model.h5")  # Make sure the filename matches your uploaded model
 
 def predict_digit(image):
     # Preprocess the image
@@ -19,10 +19,10 @@ def predict_digit(image):
     predicted_class = np.argmax(prediction)
     return predicted_class
 
-# Define the Gradio interface
+# Define the Gradio interface using the updated API
 gr.Interface(
     fn=predict_digit,
-    inputs=gr.inputs.Image(type="numpy", label="Upload a digit image"),
+    inputs=gr.Image(type="numpy", label="Upload a digit image"),  # Updated to use gr.Image
     outputs="text",
     title="Handwritten Digit Recognition",
     description="Upload an image of a handwritten digit, and the model will predict which digit it is."