Update src/main.py

src/main.py

@@ -1,31 +1,42 @@
 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, jsonify
-import requests
-
-
-
-nlp, dict_docs_spacy = sp.load_spacy_values()
-dataset, list_2000_tokens = dg.load_data()
-
+from flask import Flask, render_template, Response, request
+import googletrans
 from googletrans import Translator
 
 app = Flask(__name__, static_folder='static')
 app.config['TITLE'] = 'Sign Language Translate'
 
-translator = Translator()
+nlp, dict_docs_spacy = sp.load_spacy_values()
+dataset, list_2000_tokens = dg.load_data()
+translator = Translator(service_urls=['translate.google.com'])
 
 def translate_korean_to_english(text):
     try:
         # 한글 감지
         if any('\u3131' <= char <= '\u318F' or '\uAC00' <= char <= '\uD7A3' for char in text):
             translation = translator.translate(text, src='ko', dest='en')
+            print(f"Translation result: {translation.text}")  # 디버깅용
             return translation.text
         return text
     except Exception as e:
         print(f"Translation error: {e}")
-        return text
+        try:
+            # 백업 방식으로 파파고 API 사용
+            headers = {
+                'X-Naver-Client-Id': 'YOUR_CLIENT_ID',
+                'X-Naver-Client-Secret': 'YOUR_CLIENT_SECRET'
+            }
+            data = {
+                'source': 'ko',
+                'target': 'en',
+                'text': text
+            }
+            response = requests.post('https://openapi.naver.com/v1/papago/n2mt', headers=headers, data=data)
+            return response.json()['message']['result']['translatedText']
+        except:
+            return text
 
 @app.route('/')
 def index():
@@ -34,10 +45,13 @@ def index():
 @app.route('/translate/', methods=['POST'])
 def result():
     if request.method == 'POST':
-        korean_sentence = request.form['inputSentence']
+        input_text = request.form['inputSentence']
         try:
-            english_translation = translate_korean_to_english(korean_sentence)
-            eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_translation)
+            english_text = translate_korean_to_english(input_text)
+            if english_text == input_text and any('\u3131' <= char <= '\u318F' or '\uAC00' <= char <= '\uD7A3' for char in input_text):
+                raise Exception("Translation failed")
+                
+            eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_text)
             generated_gloss = eng_to_asl_translator.translate_to_gloss()
             
             gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum()]
@@ -49,11 +63,12 @@ def result():
             
             return render_template('result.html',
                                 title=app.config['TITLE'],
-                                original_sentence=korean_sentence,
-                                english_translation=english_translation,
+                                original_sentence=input_text,
+                                english_translation=english_text,
                                 gloss_sentence_before_synonym=gloss_sentence_before_synonym,
                                 gloss_sentence_after_synonym=gloss_sentence_after_synonym)
         except Exception as e:
+            print(f"Error in translation process: {e}")
             return render_template('error.html', error=str(e))
 
 @app.route('/video_feed')