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import whisper |
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from pytube import YouTube |
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import gradio as gr |
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import os |
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import re |
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import logging |
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logging.basicConfig(level=logging.INFO) |
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model = whisper.load_model("base") |
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def get_text(url): |
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if url != '': |
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output_text_transcribe = '' |
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yt = YouTube(url) |
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video = yt.streams.filter(only_audio=True).first() |
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out_file=video.download(output_path=".") |
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file_stats = os.stat(out_file) |
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logging.info(f'Size of audio file in Bytes: {file_stats.st_size}') |
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if file_stats.st_size <= 30000000: |
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base, ext = os.path.splitext(out_file) |
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new_file = base+'.mp3' |
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os.rename(out_file, new_file) |
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a = new_file |
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result = model.transcribe(a) |
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return result['text'].strip() |
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else: |
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logging.error('Videos for transcription on this space are limited to about 1.5 hours. Sorry about this limit but some joker thought they could stop this tool from working by transcribing many extremely long videos. Please visit https://steve.digital to contact me about this space.') |
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def get_summary(article): |
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first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5]) |
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b = summarizer(first_sentences, min_length = 20, max_length = 120, do_sample = False) |
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b = b[0]['summary_text'].replace(' .', '.').strip() |
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return b |
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with gr.Blocks() as demo: |
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gr.Markdown("<h1><center>Free Fast YouTube URL Video-to-Text using <a href=https://openai.com/blog/whisper/ target=_blank>OpenAI's Whisper</a> Model</center></h1>") |
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gr.Markdown("<center>Enter the link of any YouTube video to generate a text transcript of the video.</center>") |
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gr.Markdown("<center><b>'Whisper is a neural net that approaches human level robustness and accuracy on English speech recognition.'</b></center>") |
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gr.Markdown("<center>Transcription takes 5-10 seconds per minute of the video (bad audio/hard accents slow it down a bit). #patience<br />If you have time while waiting, drop a ♥️ and check out my <a href=https://www.artificial-intelligence.blog target=_blank>AI blog</a> (opens in new tab).</center>") |
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input_text_url = gr.Textbox(placeholder='Youtube video URL', label='YouTube URL') |
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result_button_transcribe = gr.Button('Transcribe') |
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output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript') |
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result_button_transcribe.click(get_text, inputs = input_text_url, outputs = output_text_transcribe) |
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demo.queue(default_enabled = True).launch(debug = True) |
