Spaces:
Running
Running
Initialize Streamlit transcription app.
Browse files
app.py
ADDED
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import streamlit as st
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForSpeechSeq2Seq
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from pytube import YouTube
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from pydub import AudioSegment
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from audio_extract import extract_audio
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from tqdm import tqdm
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import os
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st.set_page_config(
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page_title="VidText"
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)
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def youtube_video_downloader(url):
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yt_vid = YouTube(url)
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title = yt_vid.title
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vid_dld = (
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yt_vid.streams.filter(progressive=True, file_extension="mp4")
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.order_by("resolution")
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.desc()
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.first()
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)
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# vid_dld = vid_dld.download()
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return vid_dld, title
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def audio_extraction(video_file, output_format):
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# temp_filename = video_file.name
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# video_path = f"{temp_filename}"
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audio = extract_audio(
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input_path=video_file, output_path=f"{video_file[:-4]}.mp3", output_format=f"{output_format}"
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)
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return audio
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def audio_processing(mp3_audio):
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audio = AudioSegment.from_file(mp3_audio, format="mp3")
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wav_file = "audio_file.wav"
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audio = audio.export(wav_file, format="wav")
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return wav_file
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@st.cache_resource
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def transcribe_video(processed_audio):
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transcriber_model = pipeline(task="automatic-speech-recognition", model="openai/whisper-large-v3")
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text_extract = transcriber_model(processed_audio)
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return text_extract['text']
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# Streamlit UI
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url_input_tab, file_select_tab, audio_file_tab = st.tabs(["Youtube url", "Video file", "Audio file"])
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# with url_input_tab:video_path
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# url = st.text_input("Enter the Youtube url")
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# yt_video, title = youtube_video_downloader(url)
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# if yt_video:
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# if st.button("Transcribe"):
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# with st.spinner("Transcribing..."):
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# ytvideo_transcript = transcribe(yt_video)
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# st.success(f"Transcription successful")
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# st.write(ytvideo_transcript)
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# Video file transcription
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with file_select_tab:
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video_file = st.file_uploader("Upload video file", type="mp4")
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if video_file:
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if st.button("Transcribe"):
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with st.spinner("Transcribing..."):
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audio = audio_extraction(video_file, "mp3")
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video_transcript = transcribe_video(audio)
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st.success(f"Transcription successful")
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st.write(video_transcript)
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# Audio transcription
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with audio_file_tab:
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audio_file = st.file_uploader("Upload audio file", type="mp3")
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if audio_file:
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if st.button("Transcribe"):
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with st.spinner("Transcribing..."):
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processed_audio = audio_processing(audio_file)
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audio_transcript = transcribe_video(processed_audio)
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st.success(f"Transcription successful")
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st.write(audio_transcript)
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