Update src/main.py

src/main.py

@@ -1,41 +1,26 @@
 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
-from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqTranslation
-import torch
-import os
+from flask import Flask, render_template, Response, request, jsonify
+import requests
 
-app = Flask(__name__)
-app.config['TITLE'] = 'ASL Translator'
-
-# 캐시 디렉토리 설정
-cache_dir = "/tmp/huggingface"
-if not os.path.exists(cache_dir):
-    os.makedirs(cache_dir, exist_ok=True)
-os.environ['TRANSFORMERS_CACHE'] = cache_dir
-os.environ['HF_HOME'] = cache_dir
-
-# CPU 설정
-device = torch.device('cpu')
-os.environ['CUDA_VISIBLE_DEVICES'] = ''
-
-# 번역 모델 초기화
-model_name = "Helsinki-NLP/opus-mt-ko-en"
-tokenizer = AutoTokenizer.from_pretrained(model_name, cache_dir=cache_dir)
-model = AutoModelForSeq2SeqTranslation.from_pretrained(model_name, cache_dir=cache_dir)
-model = model.to(device)
+app = Flask(__name__, static_folder='static')
+app.config['TITLE'] = 'Sign Language Translate'
 
 nlp, dict_docs_spacy = sp.load_spacy_values()
 dataset, list_2000_tokens = dg.load_data()
 
 def translate_korean_to_english(text):
-    if any('\u3131' <= char <= '\u318F' or '\uAC00' <= char <= '\uD7A3' for char in text):
-        inputs = tokenizer(text, return_tensors="pt", padding=True)
-        outputs = model.generate(**inputs)
-        translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
-        return translation
-    return text
+    url = "https://translate.googleapis.com/translate_a/single"
+    params = {
+        "client": "gtx",
+        "sl": "ko",
+        "tl": "en",
+        "dt": "t",
+        "q": text
+    }
+    response = requests.get(url, params=params)
+    return response.json()[0][0][0]
 
 @app.route('/')
 def index():
@@ -44,10 +29,10 @@ def index():
 @app.route('/translate/', methods=['POST'])
 def result():
     if request.method == 'POST':
-        input_text = request.form['inputSentence']
+        korean_sentence = request.form['inputSentence']
         try:
-            english_text = translate_korean_to_english(input_text)
-            eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_text)
+            english_translation = translate_korean_to_english(korean_sentence)
+            eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_translation)
             generated_gloss = eng_to_asl_translator.translate_to_gloss()
             
             gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum()]
@@ -59,8 +44,8 @@ def result():
             
             return render_template('result.html',
                                 title=app.config['TITLE'],
-                                original_sentence=input_text,
-                                english_translation=english_text,
+                                original_sentence=korean_sentence,
+                                english_translation=english_translation,
                                 gloss_sentence_before_synonym=gloss_sentence_before_synonym,
                                 gloss_sentence_after_synonym=gloss_sentence_after_synonym)
         except Exception as e:
@@ -74,4 +59,4 @@ def video_feed():
                    mimetype='multipart/x-mixed-replace; boundary=frame')
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860, debug=True)
+    app.run(host="0.0.0.0", port=5000, debug=True)