| import whisper | |
| from pytube import YouTube | |
| import gradio as gr | |
| import os | |
| import re | |
| import logging | |
| logging.basicConfig(level=logging.INFO) | |
| model = whisper.load_model("base") | |
| def get_text(url): | |
| if url != '': | |
| output_text_transcribe = '' | |
| yt = YouTube(url) | |
| video = yt.streams.filter(only_audio=True).first() | |
| out_file = video.download(output_path=".") | |
| file_stats = os.stat(out_file) | |
| logging.info(f'Size of audio file in Bytes: {file_stats.st_size}') | |
| if file_stats.st_size <= 30000000: | |
| base, ext = os.path.splitext(out_file) | |
| new_file = base + '.mp3' | |
| os.rename(out_file, new_file) | |
| a = new_file | |
| result = model.transcribe(a) | |
| return result['text'].strip() | |
| else: | |
| 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.') | |
| 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>YouTube URL Video-to-Text using <a href=https://openai.com/blog/whisper/ target=_blank>GPTube</a> Model</center></h1>") | |
| input_text_url = gr.Textbox(placeholder='Youtube video URL', label='YouTube URL') | |
| result_button_transcribe = gr.Button('Transcribe') | |
| output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript') | |
| result_button_transcribe.click(get_text, inputs=input_text_url, outputs=output_text_transcribe) | |
| demo.queue(default_enabled=True).launch(show_api=True) |