Update app.py
Browse files
app.py
CHANGED
@@ -3,49 +3,56 @@ from pytube import YouTube
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import whisper
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from transformers import pipeline
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from bark import generate_audio, preload_models
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import os
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import moviepy.editor as mp
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# Load models
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asr_model = whisper.load_model("base")
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hi")
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# Preload Bark models
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preload_models()
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def process_video(link):
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try:
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yt = YouTube(link)
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# Step 2: Transcribe
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result = asr_model.transcribe(
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english_text = result["text"]
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# Step 3: Translate to Hindi
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hindi_text = translator(english_text)[0]['translation_text']
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# Step 4: Generate Hindi
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hindi_audio = generate_audio(hindi_text)
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f.write(hindi_audio)
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# Step 5: Merge audio with video
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return hindi_text, output_path
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except Exception as e:
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return str(e), None
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gr.Interface(
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fn=process_video,
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inputs=gr.Textbox(label="
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outputs=[
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gr.Textbox(label="Hindi Translation"),
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gr.Video(label="Dubbed Hindi Video")
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]
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).launch()
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import whisper
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from transformers import pipeline
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from bark import generate_audio, preload_models
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import moviepy.editor as mp
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import os
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import tempfile
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# Load models
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asr_model = whisper.load_model("base")
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translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-hi")
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preload_models()
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def process_video(link):
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try:
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# Download audio from YouTube
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yt = YouTube(link)
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audio_stream = yt.streams.filter(only_audio=True).first()
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temp_dir = tempfile.mkdtemp()
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audio_path = os.path.join(temp_dir, "audio.mp4")
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audio_stream.download(filename=audio_path)
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# Step 2: Transcribe using Whisper
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result = asr_model.transcribe(audio_path)
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english_text = result["text"]
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# Step 3: Translate to Hindi
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hindi_text = translator(english_text)[0]['translation_text']
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# Step 4: Generate Hindi audio using Bark
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hindi_audio = generate_audio(hindi_text)
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hindi_audio_path = os.path.join(temp_dir, "hindi.wav")
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with open(hindi_audio_path, "wb") as f:
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f.write(hindi_audio)
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# Step 5: Merge audio with video
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audio_clip = mp.AudioFileClip(hindi_audio_path)
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video_clip = mp.ColorClip(size=(1280, 720), color=(0, 0, 0), duration=audio_clip.duration)
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final_video = video_clip.set_audio(audio_clip)
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output_path = os.path.join(temp_dir, "final_output.mp4")
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final_video.write_videofile(output_path, fps=24)
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return hindi_text, output_path
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except Exception as e:
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return f"Error: {str(e)}", None
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gr.Interface(
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fn=process_video,
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inputs=gr.Textbox(label="YouTube Video Link"),
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outputs=[
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gr.Textbox(label="Hindi Translation"),
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gr.Video(label="Dubbed Hindi Video")
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],
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title="ποΈ YouTube Hindi Dubber AI",
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description="Paste a YouTube video link. This app transcribes it, translates it to Hindi, and dubs it using Bark AI."
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).launch()
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