Update app.py

app.py

@@ -6,6 +6,7 @@ from sklearn.preprocessing import MinMaxScaler
 from keras.models import Model
 from keras.layers import Conv2D
 import cv2
+import tensorflow as tf 
 
 model = keras.models.load_model("model.keras")
 
@@ -43,7 +44,9 @@ if uploaded_img is not None:
     #img_norm = img_resized.astype('float32') / 255.0
     input_img = img_resized.reshape(1,28,28,1)
     
-    model.predict(np.zeros((1, 28, 28, 1), dtype=np.float32))
+    #model.predict(np.zeros((1, 28, 28, 1), dtype=np.float32))
+    dummy_input = tf.zeros((1, 28, 28, 1))
+    _ = model(dummy_input)
 
     st.image(img_resized, caption="Uploaded Image (Resized to 28x28)", use_container_width =True, channels="GRAY")