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import gradio as gr
import subprocess
import os
from googletrans import Translator
from TTS.api import TTS
from IPython.display import Audio, display
import ffmpeg
import whisper
def process_video(video, high_quality, target_language):
try:
output_filename = "resized_video.mp4"
if high_quality:
ffmpeg.input(video).output(output_filename, vf='scale=-1:720').run()
video_path = output_filename
else:
video_path = video
ffmpeg.input(video_path).output('output_audio.wav', acodec='pcm_s24le', ar=48000, map='a').run()
model = whisper.load_model("base")
result = model.transcribe("output_audio.wav")
whisper_text = result["text"]
whisper_language = result['language']
language_mapping = {
'English': 'en',
'Spanish': 'es',
'French': 'fr',
'German': 'de',
'Italian': 'it',
'Portuguese': 'pt',
'Polish': 'pl',
'Turkish': 'tr',
'Russian': 'ru',
'Dutch': 'nl',
'Czech': 'cs',
'Arabic': 'ar',
'Chinese (Simplified)': 'zh-cn'
}
target_language_code = language_mapping[target_language]
translator = Translator()
translated_text = translator.translate(whisper_text, src=whisper_language, dest=target_language_code).text
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1", gpu=True)
tts.tts_to_file(translated_text, speaker_wav='output_audio.wav', file_path="output_synth.wav", language=target_language_code)
subprocess.run(f"python inference.py --face {video_path} --audio 'output_synth.wav' --outfile 'output_high_qual.mp4'", shell=True)
return "output_high_qual.mp4"
except Exception as e:
return str(e)
iface = gr.Interface(
fn=process_video,
inputs=[
gr.Video(),
gr.inputs.Checkbox(label="High Quality"),
gr.inputs.Dropdown(choices=["English", "Spanish", "French", "German", "Italian", "Portuguese", "Polish", "Turkish", "Russian", "Dutch", "Czech", "Arabic", "Chinese (Simplified)"], label="Target Language for Dubbing")
],
outputs=gr.outputs.File(),
live=False
)
iface.launch(share=True)
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