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