Update src/main.py

src/main.py

@@ -2,22 +2,18 @@ import display_gloss as dg
 import synonyms_preprocess as sp
 from NLP_Spacy_base_translator import NlpSpacyBaseTranslator 
 from flask import Flask,  render_template, Response, request
-import nltk
-
-
 
 
 app = Flask(__name__)
 
-nltk.download('wordnet')
 
 @app.route('/')
 def index():
     global dataset, vocabulary_list, dict_2000_tokens, nlp, dict_docs_spacy
 
     dataset, vocabulary_list = dg.load_data()
-    dict_2000_tokens = dataset["gloss"].unique()
-    nlp, dict_docs_spacy = sp.load_spacy_values()
+    #dict_2000_tokens = dataset["gloss"].unique()
+    #nlp, dict_docs_spacy = sp.load_spacy_values()
 
     return render_template('index.html')
 
@@ -28,9 +24,10 @@ def result():
         eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=sentence)
         generated_gloss = eng_to_asl_translator.translate_to_gloss()
         gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum() ]
-        print('gloss before synonym:', gloss_list_lower)
-        gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, dict_2000_tokens) for gloss in gloss_list_lower]
-        print('synonym list:', gloss_list)
+        gloss_list = gloss_list_lower 
+        #print('gloss before synonym:', gloss_list_lower)
+        #gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, dict_2000_tokens) for gloss in gloss_list_lower]
+        #print('synonym list:', gloss_list)
         gloss_sentence = " ".join(gloss_list)
         return render_template('translate.html', sentence=sentence, gloss_list=gloss_list, gloss_sentence=gloss_sentence)