Duplicate from SteveDigital/free-fast-youtube-url-video-to-text-using-openai-whisper

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README.md

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+---
+title: Free Youtube Url Video To Text Using Openai Whisper
+emoji: 📉
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 3.11.0
+app_file: app.py
+pinned: false
+license: gpl-3.0
+duplicated_from: SteveDigital/free-fast-youtube-url-video-to-text-using-openai-whisper
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+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)
+  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
+
+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>Generating the transcript takes 5-10 seconds per minute of the video (when I am using this space I boost performance for everyone). #patience</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.launch(debug = True)

requirements.txt

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+git+https://github.com/openai/whisper.git
+git+https://github.com/huggingface/transformers
+pytube