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from transformers import pipeline | |
import gradio as gr | |
import os | |
import subprocess | |
from pytube import YouTube | |
import subprocess | |
pipe = pipeline(model="tilos/whisper-small-zh-HK") # change to "your-username/the-name-you-picked" | |
def video2mp3(video_file, output_ext="mp3"): | |
filename, ext = os.path.splitext(video_file) | |
subprocess.call(["ffmpeg", "-y", "-i", video_file, f"{filename}.{output_ext}"], | |
stdout=subprocess.DEVNULL, | |
stderr=subprocess.STDOUT) | |
return f"{filename}.{output_ext}" | |
def transcribe(audio): | |
text = pipe(audio)["text"] | |
return text | |
def gen_sub(video): | |
result = subprocess.check_output(['auto_subtitle','/example.mp4','--model', 'medium']) | |
return result | |
def get_text(url): | |
result = pipe(get_audio(url)) | |
return result['text'].strip() | |
def get_audio(url): | |
website = YouTube(url) | |
video = website.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) | |
audio = new_file | |
return audio | |
def offline_video(video): | |
audio_file = video2mp3(video) | |
text = transcribe(audio_file) | |
return text | |
with gr.Blocks() as demo: | |
# video file input | |
gr.Interface( | |
title="Whisper: Real Time Cantonese Recognition", | |
description="Realtime demo for Cantonese speech recognition using a fine-tuned Whisper small model. " | |
"Generate zh-HK subtitle from video file, audio file, your microphone, and Youtube URL", | |
fn=offline_video, | |
inputs="video", | |
outputs="text", | |
allow_flagging="never", | |
) | |
# audio file input, generate subtitled video | |
gr.Interface( | |
description= "Generate Cantonese subtitled video from video file", | |
fn=gen_sub, | |
inputs="video", | |
outputs="video", | |
allow_flagging="never", | |
) | |
# audio file input | |
with gr.Row(): | |
with gr.Column(): | |
input_audio = gr.Audio(source="upload", type="filepath") | |
micro_btn = gr.Button('Generate Voice Subtitles') | |
with gr.Column(): | |
output_audio = gr.Textbox(placeholder='Transcript from audio', label='Subtitles') | |
micro_btn.click(transcribe, inputs=input_audio, outputs=output_audio) | |
""" | |
gr.Interface( | |
fn=transcribe, | |
title="Whisper: zh-HK Subtitle Generator", | |
description="Generate zh-HK subtitle from audio file, your microphone and Youtube", | |
inputs = gr.Audio(source="upload", type="filepath", optional=True), | |
outputs = "text", | |
allow_flagging= "never", | |
) | |
""" | |
# microphone input | |
with gr.Row(): | |
with gr.Column(): | |
input_mircro = gr.Audio(source="microphone", type="filepath") | |
micro_btn = gr.Button('Generate Voice Subtitles') | |
with gr.Column(): | |
output_micro = gr.Textbox(placeholder='Transcript from mic', label='Subtitles') | |
micro_btn.click(transcribe, inputs=input_mircro, outputs=output_micro) | |
# Youtube url input | |
with gr.Row(): | |
with gr.Column(): | |
inputs_url = gr.Textbox(placeholder='Youtube URL', label='URL') | |
url_btn = gr.Button('Generate Youtube Video Subtitles') | |
examples = gr.Examples(examples=["https://www.youtube.com/watch?v=Yw4EoGWe0vw"],inputs=[inputs_url]) | |
with gr.Column(): | |
output_url = gr.Textbox(placeholder='Transcript from video.', label='Transcript') | |
url_btn.click(get_text, inputs=inputs_url, outputs=output_url ) | |
demo.launch(debug=True) |