Update app.py

app.py

@@ -2,7 +2,7 @@
 import gradio as gr
 import joblib
 import dill
-import pickle
+# import pickle
 import imblearn
 import sklearn
 import xgboost
@@ -10,36 +10,36 @@ file_name = 'TSPI_model_joblib.sav'
 model = joblib.load(file_name)
 
 
-def STPI(t_1_MaxValue,t_2_MaxValue,t_4_MaxValue,
+def STPI(t_4_MaxValue,t_2_MaxValue,t_1_MaxValue,
 # Acc_0_5__1_0_MaxValue,
-Abs_Diff_t_1_MaxValue,Abs_Diff_t_2_MaxValue,Abs_Diff_t_4_MaxValue):
+Abs_Diff_t_4_MaxValue,Abs_Diff_t_2_MaxValue,Abs_Diff_t_1_MaxValue):
     print('------------------')
     
-    X = [t_1_MaxValue,t_2_MaxValue,t_4_MaxValue,
+    X = [t_4_MaxValue,t_2_MaxValue,t_1_MaxValue,
     # Acc_0_5__1_0_MaxValue,
-    Abs_Diff_t_1_MaxValue,Abs_Diff_t_2_MaxValue,Abs_Diff_t_4_MaxValue]
+    Abs_Diff_t_4_MaxValue,Abs_Diff_t_2_MaxValue,Abs_Diff_t_1_MaxValue]
     print(X)
-    outcome_decoded = ['Normal',,'Suspect','Keratoconic']
+    outcome_decoded = ['Normal','','Suspect','Keratoconic']
     file_object = open('stpi_data.txt', 'a')
-    file_object.write(str(t_1_MaxValue))
+    file_object.write(str(t_4_MaxValue))
     file_object.write(';')
     file_object.write(str(t_2_MaxValue))
     file_object.write(';')
-    file_object.write(str(t_4_MaxValue))
+    file_object.write(str(t_1_MaxValue))
     file_object.write(';')
     # file_object.write(str(Acc_0_5__1_0_MaxValue))
     # file_object.write(';')
-    file_object.write(str(Abs_Diff_t_1_MaxValue))
+    file_object.write(str(Abs_Diff_t_4_MaxValue))
     file_object.write(';')
     file_object.write(str(Abs_Diff_t_2_MaxValue))
     file_object.write(';')
-    file_object.write(str(Abs_Diff_t_4_MaxValue))
+    file_object.write(str(Abs_Diff_t_1_MaxValue))
     file_object.write(';')
     file_object.write('\n')
     file_object.close()
 
     result_3way = model.predict([X])
-    print('The patient is ', outcome_decoded[int(result_3way)], 'through the 3way method')
+    # print('The patient is ', outcome_decoded[int(result_3way)], 'through the 3way method')
     # result = 'The 3-way classification resulted in a ', outcome_decoded[int(result_3way)] + ' patient.'
     # further_analysis = 'Futher analysis using the 2-way classification resulted in a ' + outcome_decoded[int(result_2way)] + ' label.'
     return 'The patient is ' + outcome_decoded[int(result_3way)] + '.'