Update app.py

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import torch
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification, pipeline
+#from transformers import AutoFeatureExtractor, AutoModelForImageClassification, pipeline
+from transformers import pipeline
+
 from numpy import exp
 import pandas as  pd
 from PIL import Image
@@ -44,6 +46,7 @@ def softmax(vector):
     
 
 fin_sum=[]   
+
 def aiornot0(image):    
     labels = ["Real", "AI"]
     mod=models[0]
@@ -197,11 +200,11 @@ with gr.Blocks() as app:
                 n_out5=gr.Label(label="Output")
                 outp5 = gr.HTML("""""")    
                 
-    btn.click(fin_clear,None,fin)
+    #btn.click(fin_clear,None,fin)
     load_btn.click(load_url,in_url,[inp,mes])
-    btn.click(aiornot0,[inp],[outp0,n_out0]).then(tot_prob,None,fin)
-    btn.click(aiornot1,[inp],[outp1,n_out1]).then(tot_prob,None,fin)
-    btn.click(aiornot2,[inp],[outp2,n_out2]).then(tot_prob,None,fin)
+    #btn.click(aiornot0,[inp],[outp0,n_out0]).then(tot_prob,None,fin)
+    #btn.click(aiornot1,[inp],[outp1,n_out1]).then(tot_prob,None,fin)
+    #btn.click(aiornot2,[inp],[outp2,n_out2]).then(tot_prob,None,fin)
     
     btn.click(image_classifier0,[inp],[n_out3])
     btn.click(image_classifier1,[inp],[n_out4])