Update app.py

app.py

@@ -122,8 +122,9 @@ def real_fake_check(list_dir, path, model):
         input_data = torch.tensor(input_data).unsqueeze(0).to('cpu') 
         result = model(input_data.float())
         probabilities = F.softmax(result, dim=1)
-        #prob[i]='%.2f'%probabilities[0][1].item()
-        prob[i]=round(probabilities[0][1].item(),2)
+        prob[i]='%.2f'%probabilities[0][1].item()
+
+        #prob[i]=round(probabilities[0][1].item(),2)
         #porb.append(round(probabilities[0][1].item(),2))
         predicted_class = 0 if probabilities[0][0] >= THRESHOLD else 1  # 확률값이 기준치보다 크다면 real, 아니면 fake
         if predicted_class == 0: