diff --git a/main.py b/main.py
index 54f2c2858492c768b5aecf714b58782fc963d15c..cc98a857178b0f22f45c9ca4de80b592976130e0 100644
--- a/main.py
+++ b/main.py
@@ -8,15 +8,16 @@ def fasta_like_to_data(path):
     file = open(path, "r")
     content = file.readlines()
     file.close()
-    return content
+    res = []
+    for l in content :
+        if l!='\n':
+            res.append(l)
+    return res
 
 def strip_lines(s):
     s = s.strip('\n')
-    try :
-        s = s.split(' ')[1]
-        return s
-    except:
-        return 'unidentifid seq error'
+    s = s.split(' ')[1]
+    return s
 
 def main(input_data_path):
     print('Reading file')
@@ -80,9 +81,9 @@ def main(input_data_path):
                            'Predicted class':label_multi})
 
     print('Saving output')
-    result.to_csv(input_data_path.strip('.txt')+'_detectability.csv',index=False) #Output du model dans le fichier 'prediction_detectability.csv'
+    result.to_csv(input_data_path.strip('.txt')+'t_detectability.csv',index=False) #Output du model dans le fichier 'prediction_detectability.csv'
 
-    new_file = open(input_data_path.strip('.txt')+'_filtered.txt','w')
+    new_file = open(input_data_path.strip('.txt')+'t_filtered.txt','w')
 
     print('Writting final file')
     i,j=0,1
@@ -96,8 +97,9 @@ def main(input_data_path):
             i+=1
             j+=1
         else :
+            print(l)
             i+=1
     new_file.close()
 
 if __name__ == '__main__':
-    main('250107_FASTA_RP_GroEL_GroES_Tuf_5pct_assemble_peptides_list.txt')
\ No newline at end of file
+    main('250107_FASTA_RP_GroEL_GroES_Tuf_5pct_assemble_peptides_list.txt')