Update app.py

app.py

@@ -1,5 +1,13 @@
 import gradio as gr
 
+def predict_image(opened_image):
+    img_array = tf.keras.utils.img_to_array(opened_image)
+    img_array = tf.expand_dims(img_array, 0) #Convert image to one empty batch -> Model was trained on batches
+    prediction = model.predict(img_array)
+    score = tf.nn.softmax(prediction[0])
+    return ("Class of Flower: " + str(class_names[np.argmax(score)]), "Confidence level: " + str(100 * np.max(score)))
+
+
 gr.Interface(fn=predict_image, 
              inputs=gr.Image(shape=(180, 180)),
              outputs=[gr.Label(num_top_classes=5), "text"],