Suppression des variables globales

src/display_gloss.py

@@ -181,6 +181,7 @@ def load_data(dataset_path='local_dataset'):
     vocabulary_list = data_df['gloss'].tolist()
     return data_df, vocabulary_list
 
+
 def check_gloss_in_vocabulary(gloss, vocabulary_list):
     return gloss in vocabulary_list
 

src/main.py

@@ -1,4 +1,5 @@
 import display_gloss as dg
+import numpy as np
 import synonyms_preprocess as sp
 from NLP_Spacy_base_translator import NlpSpacyBaseTranslator 
 from flask import Flask,  render_template, Response, request
@@ -9,16 +10,13 @@ app = Flask(__name__)
 
 @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()
-
     return render_template('index.html')
 
 @app.route('/translate/', methods=['POST'])
 def result():
+    nlp, dict_docs_spacy = sp.load_spacy_values()
+    _, list_2000_tokens = dg.load_data()
+
     if request.method == 'POST':
         sentence = request.form['inputSentence']
         eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=sentence)
@@ -27,17 +25,17 @@ def result():
         #gloss_list = gloss_list_lower
         #gloss_list = sentence.split()
         #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]
+        gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, list_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_sentence=gloss_sentence)#gloss_list=gloss_list)
 
 @app.route('/video_feed')
 def video_feed():
-    #dataset, vocabulary_list = dg.load_data()
+    dataset, list_2000_tokens = dg.load_data()
     sentence = request.args.get('gloss_sentence_to_display', '')
     gloss_list = sentence.split()
-    return Response(dg.generate_video(gloss_list, dataset, vocabulary_list), mimetype='multipart/x-mixed-replace; boundary=frame')
+    return Response(dg.generate_video(gloss_list, dataset, list_2000_tokens), mimetype='multipart/x-mixed-replace; boundary=frame')
 
 if __name__ == "__main__":
     app.debug = True