Update app.py

app.py

@@ -1,5 +1,6 @@
 import tensorflow as tf
 import gradio as gr
+import numpy as np
 
 modelo =tf.keras.models.load_model('model_0.h5')
 #modelo.load_weights("model_0_weights.h5")
@@ -8,7 +9,7 @@ classes=['daisy','dandelion','roses','sunflowers','tulips']
 def classifier(image): 
   pred_img = model.predict(tf.expand_dims(image,axis=0))
   pred_img = tf.squeeze(tf.round(pred_img))
-  texto = f'Predicted label: {class_id[(np.argmax(pred_img))]}'
+  texto = str(f'Predicted label: {class_id[(np.argmax(pred_img))]}')
   return texto
 
 interface = gr.Interface(classifier,gr.inputs.Image(shape=(1024,1024)),outputs = "text",