update

utils/methods.py

@@ -50,11 +50,7 @@ def convert_sentence_df(sentJson, pred, true_proba, set_trigram_blocking):
 def extractive_method(sentJson, sentFeat, model, threshold=0.5, TGB=False):
     #預測
     def predict(x):
-        print(x)
         true_proba = model.predict_proba(x)[:, 1]
-        print(threshold)
-        print(type(threshold))
-        print(true_proba)
         # 如果沒有任何句子的預測機率大於閾值，則選取最大機率的句子為摘要句
         if not np.any(true_proba > threshold):
             true_proba[true_proba == np.max(true_proba)] = 1
@@ -72,8 +68,6 @@ def extractive_method(sentJson, sentFeat, model, threshold=0.5, TGB=False):
         pred.append(pred_sec)
         true_proba.append(true_proba_sec)
 
-    
-    pred, true_proba = predict(sentFeat)
     body = convert_sentence_df(sentJson, pred, true_proba, TGB)
     res = body[body['predict'] == True]
     ext = {i: ' '.join(res.groupby('section').get_group(i)['text']) for i in 'IMRD'}