import streamlit as st from TTS.api import TTS import torch import subprocess import locale import assemblyai as aai import requests # Load TTS model tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True).to("cuda") # Function to translate video class Translation: def __init__(self, video_path, original_language, target_language): self.video_path = video_path self.original_language = original_language self.target_language = target_language def org_language_parameters(self, original_language): if original_language == 'English': self.lan_code = 'en' elif original_language == 'German': self.lan_code = 'de' elif original_language == 'French': self.lan_code = 'fr' elif original_language == 'Spanish': self.lan_code = 'es' else: self.lan_code = '' def target_language_parameters(self, target_language): if target_language == 'English': self.tran_code = 'en' elif target_language == 'German': self.tran_code = 'de' elif target_language == 'French': self.tran_code = 'fr' elif target_language == 'Spanish': self.tran_code = 'es' else: self.tran_code = '' def extract_audio(self): audio_path = "output_audio.wav" subprocess.run(['ffmpeg', '-i', self.video_path, '-vn', '-acodec', 'pcm_s16le', '-ar', '44100', '-ac', '2', audio_path]) st.success("Audio extracted successfully!") return audio_path def transcribe_audio(self, audio_path): aai.settings.api_key = "c29eb650444a4ae4bea01d82dd861cbb" config = aai.TranscriptionConfig(language_code=self.lan_code) transcriber = aai.Transcriber(config=config) transcript = transcriber.transcribe(audio_path) transcript_text = transcript.text return transcript_text def translate_text(self, transcript_text): base_url = "https://api.cognitive.microsofttranslator.com" endpoint = "/translate" headers = { "Ocp-Apim-Subscription-Key": "cd226bb1f3644276bea01d82dd861cbb", "Content-Type": "application/json", "Ocp-Apim-Subscription-Region": "southeastasia" } params = { "api-version": "3.0", "from": self.lan_code, "to": self.tran_code } body = [{"text": transcript_text}] response = requests.post(base_url + endpoint, headers=headers, params=params, json=body) response.raise_for_status() translation = response.json()[0]["translations"][0]["text"] return translation def generate_audio(self, translated_text): tts.tts_to_file(translated_text, speaker_wav='output_audio.wav', file_path="output_synth.wav", language=self.tran_code ) return "output_synth.wav" def translate_video(self): audio_path = self.extract_audio() self.org_language_parameters(self.original_language) self.target_language_parameters(self.target_language) transcript_text = self.transcribe_audio(audio_path) translated_text = self.translate_text(transcript_text) translated_audio_path = self.generate_audio(translated_text) # Convert translated audio to video subprocess.run(['ffmpeg', '-i', self.video_path, '-i', translated_audio_path, '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', 'output_video.mp4']) st.title("Translate Your Video") st.write("Upload your video and select the original and target languages.") # Upload video video_file = st.file_uploader("Upload Video", type=["mp4"]) if video_file is not None: # Get original and target languages original_language = st.selectbox("Select Original Language", ['English', 'German', 'French', 'Spanish']) target_language = st.selectbox("Select Target Language", ['English', 'German', 'French', 'Spanish']) translation = Translation(video_path=video_file.name, original_language=original_language, target_language=target_language) if st.button("Translate"): translation.translate_video() st.success("Video translation complete! You can download the translated video.")