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, send_file import io import cv2 import numpy as np import os import requests from urllib.parse import quote, unquote import tempfile import re 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 find_quoted_words(text): """작은따옴표로 묶인 단어들을 찾는 함수""" return re.findall(r"'([^']*)'", text) def spell_out_word(word): """단어를 개별 알파벳으로 분리하는 함수""" return ' '.join(list(word.lower())) def translate_korean_to_english(text): try: # 작은따옴표로 묶인 단어들 찾기 quoted_words = find_quoted_words(text) translated_quoted_words = [] # 각 따옴표 단어를 먼저 번역 url = "https://translate.googleapis.com/translate_a/single" for word in quoted_words: params = { "client": "gtx", "sl": "ko", "tl": "en", "dt": "t", "q": word } response = requests.get(url, params=params) if response.status_code == 200: translated_word = response.json()[0][0][0].upper() translated_quoted_words.append(translated_word) else: translated_quoted_words.append(word) # 원본 텍스트에서 따옴표 부분을 임시 마커로 대체 temp_text = text for i, word in enumerate(quoted_words): temp_text = temp_text.replace(f"'{word}'", f"QUOTED_WORD_{i}") # 전체 문장 번역 params = { "client": "gtx", "sl": "ko", "tl": "en", "dt": "t", "q": temp_text.strip() } response = requests.get(url, params=params) if response.status_code == 200: translated_text = ' '.join(item[0] for item in response.json()[0] if item[0]) # 번역된 텍스트에서 마커를 번역된 따옴표 단어로 대체 for i, translated_word in enumerate(translated_quoted_words): translated_text = translated_text.replace(f"QUOTED_WORD_{i}", f"'{translated_word}'") return translated_text else: raise Exception(f"Translation API returned status code: {response.status_code}") except Exception as e: print(f"Translation error: {e}") return text def generate_complete_video(gloss_list, dataset, list_2000_tokens): try: frames = [] is_spelling = False for gloss in gloss_list: if gloss == 'FINGERSPELL-START': is_spelling = True continue elif gloss == 'FINGERSPELL-END': is_spelling = False continue for frame in dg.generate_video([gloss], dataset, list_2000_tokens): frame_data = frame.split(b'\r\n\r\n')[1] nparr = np.frombuffer(frame_data, np.uint8) img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) frames.append(img) if not frames: raise Exception("No frames generated") height, width = frames[0].shape[:2] fourcc = cv2.VideoWriter_fourcc(*'mp4v') with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as temp_file: temp_path = temp_file.name out = cv2.VideoWriter(temp_path, fourcc, 25, (width, height)) for frame in frames: out.write(frame) out.release() with open(temp_path, 'rb') as f: video_bytes = f.read() os.remove(temp_path) return video_bytes except Exception as e: print(f"Error generating video: {str(e)}") raise @app.route('/') def index(): return render_template('index.html', title=app.config['TITLE']) @app.route('/translate/', methods=['POST']) def result(): if request.method == 'POST': input_text = request.form['inputSentence'].strip() if not input_text: return render_template('error.html', error="Please enter text to translate") try: english_text = translate_korean_to_english(input_text) if not english_text: raise Exception("Translation failed") # 작은따옴표로 묶인 단어들 찾기 quoted_words = find_quoted_words(english_text) eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_text.replace("'", "")) generated_gloss = eng_to_asl_translator.translate_to_gloss() # 단어 처리 processed_gloss = [] words = generated_gloss.split() for word in words: word_upper = word.upper() if any(quoted_word.upper() == word_upper for quoted_word in quoted_words): # 고유명사인 경우 철자를 하나씩 분리 spelled_word = spell_out_word(word) processed_gloss.extend(['FINGERSPELL-START'] + spelled_word.split() + ['FINGERSPELL-END']) else: # 일반 단어는 기존 방식대로 처리 word_lower = word.lower() if word_lower.isalnum(): processed_gloss.append(word_lower) gloss_sentence_before_synonym = " ".join(processed_gloss) # 고유명사가 아닌 단어들만 동의어 처리 final_gloss = [] i = 0 while i < len(processed_gloss): if processed_gloss[i] == 'FINGERSPELL-START': # 철자 처리 부분을 그대로 유지 final_gloss.append(processed_gloss[i]) i += 1 while i < len(processed_gloss) and processed_gloss[i] != 'FINGERSPELL-END': final_gloss.append(processed_gloss[i]) i += 1 final_gloss.append('FINGERSPELL-END') i += 1 else: # 일반 단어는 동의어 처리 word = processed_gloss[i] final_gloss.append(sp.find_synonyms(word, nlp, dict_docs_spacy, list_2000_tokens)) i += 1 gloss_sentence_after_synonym = " ".join(final_gloss) return render_template('result.html', title=app.config['TITLE'], 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: return render_template('error.html', error=f"Translation error: {str(e)}") @app.route('/video_feed') def video_feed(): sentence = request.args.get('gloss_sentence_to_display', '') gloss_list = sentence.split() return Response(dg.generate_video(gloss_list, dataset, list_2000_tokens), mimetype='multipart/x-mixed-replace; boundary=frame') @app.route('/download_video/') def download_video(gloss_sentence): try: decoded_sentence = unquote(gloss_sentence) gloss_list = decoded_sentence.split() if not gloss_list: return "No gloss provided", 400 video_bytes = generate_complete_video(gloss_list, dataset, list_2000_tokens) if not video_bytes: return "Failed to generate video", 500 return send_file( io.BytesIO(video_bytes), mimetype='video/mp4', as_attachment=True, download_name='sign_language.mp4' ) except Exception as e: print(f"Download error: {str(e)}") return f"Error downloading video: {str(e)}", 500 if __name__ == "__main__": app.run(host="0.0.0.0", port=7860, debug=True)