Update app.py

app.py

@@ -5,6 +5,7 @@ from tensorflow.keras.models import load_model
 from tensorflow.keras.utils import to_categorical
 from tensorflow.keras.datasets import mnist
 import cv2
+from PIL import Image
 
 # I/O image dimensions for display
 DIMS = (100, 100)
@@ -19,8 +20,10 @@ mnist_examples = [[cv2.resize(x_test[i], DIMS)] for i in range(10)]
 
 # Function to preprocess the image
 def preprocess_image(image):
+    if isinstance(image, Image.Image):
+        image = np.array(image)
     image = cv2.resize(image, (28, 28))  # Resize to 28x28 for model input
-    image = np.array(image) / 255.0
+    image = image / 255.0
     image = image.reshape(1, 28, 28, 1)
     return image