Update src/main.py

src/main.py

@@ -1,12 +1,12 @@
 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
+from flask import Flask, render_template, Response, request
 import requests
 
-app = Flask(__name__, static_folder='static')
-app.config['TITLE'] = 'Sign Language Translate'
+app = Flask(__name__)
 
+# Initialize data
 nlp, dict_docs_spacy = sp.load_spacy_values()
 dataset, list_2000_tokens = dg.load_data()
 
@@ -16,40 +16,72 @@ def translate_korean_to_english(text):
         "client": "gtx",
         "sl": "ko",
         "tl": "en",
-        "dt": "t",
+        "dt": ["t", "bd"],  # Added "bd" for better translation
         "q": text
     }
-    response = requests.get(url, params=params)
-    return response.json()[0][0][0]
+    try:
+        response = requests.get(url, params=params)
+        translation = response.json()[0][0][0]
+        # Basic post-processing
+        translation = translation.replace("It is", "").replace("There is", "").strip()
+        return translation
+    except Exception as e:
+        print(f"Translation error: {e}")
+        return text
+
+def process_gloss_conversion(english_text):
+    # Custom mapping for common Korean-specific terms
+    term_mapping = {
+        "Korea": "KOREA",
+        "Seoul": "SEOUL",
+        "four seasons": "FOUR SEASON",
+        "beautiful": "BEAUTIFUL",
+        "country": "COUNTRY"
+    }
+    
+    # Apply mappings before ASL conversion
+    for term, replacement in term_mapping.items():
+        english_text = english_text.replace(term.lower(), replacement)
+    
+    return english_text
 
 @app.route('/')
 def index():
-    return render_template('index.html', title=app.config['TITLE'])
+    return render_template('index.html')
 
 @app.route('/translate/', methods=['POST'])
 def result():
     if request.method == 'POST':
-        korean_sentence = request.form['inputSentence']
-        try:
-            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()]
-            gloss_sentence_before_synonym = " ".join(gloss_list_lower)
-            
-            gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, list_2000_tokens) 
-                         for gloss in gloss_list_lower]
-            gloss_sentence_after_synonym = " ".join(gloss_list)
+        input_text = request.form['inputSentence']
+        
+        # Check if input is Korean (simplified check)
+        is_korean = any(ord('가') <= ord(char) <= ord('힣') for char in input_text)
+        
+        if is_korean:
+            english_translation = translate_korean_to_english(input_text)
+        else:
+            english_translation = input_text
             
-            return render_template('result.html',
-                                title=app.config['TITLE'],
-                                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:
-            return render_template('error.html', error=str(e))
+        # Pre-process for better ASL conversion
+        processed_english = process_gloss_conversion(english_translation)
+        
+        # Convert to ASL
+        eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=processed_english)
+        generated_gloss = eng_to_asl_translator.translate_to_gloss()
+        
+        gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum()]
+        gloss_sentence_before_synonym = " ".join(gloss_list_lower)
+        
+        # Apply custom synonym rules
+        gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, list_2000_tokens) 
+                     for gloss in gloss_list_lower]
+        gloss_sentence_after_synonym = " ".join(gloss_list)
+        
+        return render_template('result.html',
+                            original_sentence=input_text,
+                            english_translation=english_translation,
+                            gloss_sentence_before_synonym=gloss_sentence_before_synonym,
+                            gloss_sentence_after_synonym=gloss_sentence_after_synonym)
 
 @app.route('/video_feed')
 def video_feed():