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from TTS.api import TTS | |
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True).to("cuda") | |
# Dependencies | |
%cd /content/ | |
import locale | |
locale.getpreferredencoding = lambda: "UTF-8" | |
!git clone https://github.com/justinjohn0306/Wav2Lip | |
!cd Wav2Lip && pip install -r requirements_colab.txt | |
%cd /content/Wav2Lip | |
!wget "https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth" -O "face_detection/detection/sfd/s3fd.pth" | |
!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip.pth' -O 'checkpoints/wav2lip.pth' | |
!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/wav2lip_gan.pth' -O 'checkpoints/wav2lip_gan.pth' | |
!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/resnet50.pth' -O 'checkpoints/resnet50.pth' | |
!wget 'https://github.com/justinjohn0306/Wav2Lip/releases/download/models/mobilenet.pth' -O 'checkpoints/mobilenet.pth' | |
import subprocess | |
import assemblyai as aai | |
import requests | |
import moviepy.editor as mp | |
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): | |
video = mp.VideoFileClip(self.video_path) | |
audio = video.audio | |
audio_path = "output_audio.wav" | |
audio.write_audiofile(audio_path) | |
print("Audio extracted successfully!") | |
return audio_path | |
def transcribe_audio(self,audio_path): | |
aai.settings.api_key = "c29eb650444a4ae4be6a787ebb15d5e2" | |
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 | |
if transcript.status == aai.TranscriptStatus.error: | |
print(transcript.error) | |
return None | |
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 | |
#generate audio | |
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) | |
#Generate video | |
%cd /content/Wav2Lip | |
#This is the detection box padding, if you see it doesnt sit quite right, just adjust the values a bit. Usually the bottom one is the biggest issue | |
pad_top = 0 | |
pad_bottom = 15 | |
pad_left = 0 | |
pad_right = 0 | |
rescaleFactor = 1 | |
video_path_fix = f"'../{self.video_path}'" | |
audio_path_fix = f"'../{translated_audio_path}'" | |
!python inference.py --checkpoint_path 'checkpoints/wav2lip_gan.pth' --face $video_path_fix --audio $audio_path_fix --pads $pad_top $pad_bottom $pad_left $pad_right --resize_factor $rescaleFactor --nosmooth --outfile '/content/output_video.mp4' | |
return '/content/output_video.mp4' # Return the path to the translated video file | |
# return '/content/output_video.mp4', open('/content/output_video.mp4', 'rb') # Return the path and file object of the translated video file | |
# from translator import translation # Import the Translator class from translate module | |
import gradio as gr | |
import os | |
from google.colab import files | |
def app(video_path, original_language, target_language): | |
%cd /content/ | |
video_name = os.path.basename(video_path) | |
# Save the uploaded file to the content folder in Colab | |
with open(video_name, "wb") as f: | |
with open(video_path, "rb") as uploaded_file: | |
f.write(uploaded_file.read()) | |
translator = translation(video_name, original_language, target_language) | |
video_file = translator.translate_video() | |
return video_file | |
interface_video_file = gr.Interface( | |
fn=app, | |
inputs=[ | |
gr.Video(label="Video Path"), | |
gr.Dropdown(["English", "German", "French", "Spanish"], label="Original Language"), | |
gr.Dropdown(["English", "German", "French", "Spanish"], label="Targeted Language"), | |
], | |
outputs=gr.Video(label="Translated Video") | |
) | |
interface_video_file.launch(debug=True) | |