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import gradio as gr
from pytube import YouTube
from transformers import pipeline
import os
pipe = pipeline(model="GIanlucaRub/whisper-tiny-it-6") # change to "your-username/the-name-you-picked"
def transcribe_yt(link):
yt = YouTube(link)
audio = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp3")
text = pipe(audio)["text"]
os.remove(audio)
return text
def transcribe_audio(audio):
text = pipe(audio)["text"]
return text
def populate_metadata(link):
yt = YouTube(link)
return yt.thumbnail_url, yt.title
title="Youtube Whisperer"
description="Speech to text transcription of Youtube videos using OpenAI's Whisper"
block = gr.Blocks()
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 500px; margin: 0 auto;">
<div>
<h1>Youtube Whisperer</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
Speech to text transcription of Youtube videos using OpenAI's Whisper
</p>
</div>
"""
)
with gr.Group():
with gr.Box():
text = gr.Textbox(
label="Transcription",
placeholder="Transcription Output",
lines=5)
microphone=gr.Audio(source="microphone", type="filepath")
with gr.Row().style(mobile_collapse=False, equal_height=True):
btn_microphone = gr.Button("Transcribe microphone audio")
audio_uploaded=gr.Audio(source="upload", type="filepath")
with gr.Row().style(mobile_collapse=False, equal_height=True):
btn_audio_uploaded = gr.Button("Transcribe audio uploaded")
link = gr.Textbox(label="YouTube Link")
with gr.Row().style(mobile_collapse=False, equal_height=True):
btn_youtube = gr.Button("Transcribe Youtube video")
with gr.Row().style(mobile_collapse=False, equal_height=True):
title = gr.Label(label="Video Title", placeholder="Title")
img = gr.Image(label="Thumbnail")
# Events
btn_youtube.click(transcribe_yt, inputs=[link], outputs=[text])
btn_microphone.click(transcribe_audio, inputs=[microphone], outputs=[text])
btn_audio_uploaded.click(transcribe_audio, inputs=[audio_uploaded], outputs=[text])
link.change(populate_metadata, inputs=[link], outputs=[img, title])
block.launch(debug=True) |