Spaces:
Running
Running
| import whisper | |
| from pytube import YouTube | |
| from transformers import pipeline | |
| import gradio as gr | |
| import os | |
| import re | |
| model = whisper.load_model("base") | |
| summarizer = pipeline("summarization") | |
| def get_audio(url): | |
| yt = YouTube(url) | |
| if yt.length < 540: | |
| video = yt.streams.filter(only_audio=True).first() | |
| out_file=video.download(output_path=".") | |
| base, ext = os.path.splitext(out_file) | |
| new_file = base+'.mp3' | |
| os.rename(out_file, new_file) | |
| a = new_file | |
| return a | |
| else: | |
| return "" | |
| def get_text(url): | |
| if url != '' : output_text_transcribe = '' | |
| result = model.transcribe(get_audio(url)) | |
| return result['text'].strip() | |
| def get_summary(article): | |
| first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5]) | |
| b = summarizer(first_sentences, min_length = 20, max_length = 120, do_sample = False) | |
| b = b[0]['summary_text'].replace(' .', '.').strip() | |
| return b | |
| with gr.Blocks() as demo: | |
| 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>") | |
| gr.Markdown("<center>Enter the link of any YouTube video to generate a text transcript of the video and then create a summary of the video transcript.</center>") | |
| gr.Markdown("<center><b>'Whisper is a neural net that approaches human level robustness and accuracy on English speech recognition.'</b></center>") | |
| 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, check out my <a href=https://www.artificial-intelligence.blog target=_blank>AI blog</a> (opens in new tab).</center>") | |
| input_text_url = gr.Textbox(placeholder='Youtube video URL', label='URL') | |
| result_button_transcribe = gr.Button('1. Transcribe') | |
| output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript') | |
| result_button_summary = gr.Button('2. Create Summary') | |
| output_text_summary = gr.Textbox(placeholder='Summary of the YouTube video transcript.', label='Summary') | |
| result_button_transcribe.click(get_text, inputs = input_text_url, outputs = output_text_transcribe) | |
| result_button_summary.click(get_summary, inputs = output_text_transcribe, outputs = output_text_summary) | |
| demo.queue(default_enabled=False).launch(debug = True) |