Added numpy

app.py

@@ -1,4 +1,5 @@
 import gradio as gr
+import numpy as np
 import tensorflow as tf
 import urllib.request
 
@@ -14,7 +15,7 @@ labels = labels.decode('utf-8').split("\n")[:-1]
 
 def predict(img):
   img = tf.math.divide(img, 255)
-  preds = cnn_model.predict(img.reshape(-1, 28, 28, 1))[0]
+  preds = cnn_model.predict(img.numpy().reshape(-1, 28, 28, 1))[0]
   return {label: float(pred) for label, pred in zip(labels, preds)}
 
 output = gr.outputs.Label(num_top_classes=3)