Update app.py

app.py

@@ -23,7 +23,7 @@ pipe2 = pipeline("image-classification", f"{models[2]}")
 
 fin_sum=[] 
 def image_classifier0(image):
-    labels = ["Real","AI"]
+    labels = ["AI","Real"]
     outputs = pipe0(image)
     results = {}
     result_test={}
@@ -36,7 +36,7 @@ def image_classifier0(image):
     fin_sum.append(results)
     return results
 def image_classifier1(image):
-    labels = ["Real","AI"]
+    labels = ["AI","Real"]
     outputs = pipe1(image)
     results = {}
     result_test={}
@@ -49,7 +49,7 @@ def image_classifier1(image):
     fin_sum.append(results)
     return results
 def image_classifier2(image):
-    labels = ["Real","AI"]
+    labels = ["AI","Real"]
     outputs = pipe2(image)
     results = {}
     result_test={}
@@ -119,7 +119,7 @@ def aiornot1(image):
     fin_sum.append(results)
     return gr.HTML.update(html_out),results    
 def aiornot2(image):    
-    labels = ["AI", "Real"]
+    labels = ["Real", "AI"]
     mod=models[2]
     feature_extractor2 = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")
     model2 = AutoModelForImageClassification.from_pretrained(mod)
@@ -160,8 +160,8 @@ def load_url(url):
 
 def tot_prob():
     try:
-        fin_out = fin_sum[0]["Real"]+fin_sum[1]["Real"]+fin_sum[2]["Real"]
-        fin_out = fin_out/3
+        fin_out = fin_sum[0]["Real"]+fin_sum[1]["Real"]+fin_sum[2]["Real"]+fin_sum[3]["Real"]+fin_sum[4]["Real"]+fin_sum[5]["Real"]
+        fin_out = fin_out/6
         fin_sub = 1-fin_out
         out={
             "Real":f"{fin_out}",
@@ -228,7 +228,7 @@ with gr.Blocks() as app:
         return(f"{uid}tmp_src.png")
     inp.change(upd,inp,inp,show_progress=False)
     
-    btn.click(fin_clear,None,fin)
+    btn.click(fin_clear,None,fin,show_progress=False)
     load_btn.click(load_url,in_url,[inp,mes])
     
     btn.click(aiornot0,[inp],[outp0,n_out0]).then(tot_prob,None,fin,show_progress=False)