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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") | |
# model = pipeline(model="AlexMo/FIFA_WC22_WINNER_LANGUAGE_MODEL") | |
summarizer = pipeline("summarization") | |
def getAudio(url): | |
link = YouTube(url) | |
video = link.streams.filter(only_audio=True).first() | |
file = video.download(output_path=".") | |
base, ext = os.path.splitext(file) | |
file_ext = base + '.mp3' | |
os.rename(file, file_ext) | |
return file_ext | |
def getText(url): | |
if url != '': | |
output_text_transcribe = '' | |
res = model.transcribe(getAudio(url)) | |
return res['text'].strip() | |
def getSummary(article): | |
header = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5]) | |
b = summarizer(header, min_length=15, 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</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(getText, inputs=input_text_url, outputs=output_text_transcribe) | |
result_button_summary.click(getSummary, inputs=output_text_transcribe, outputs=output_text_summary) | |
demo.launch(debug=True) |