Spaces:
Sleeping
Sleeping
File size: 3,218 Bytes
a943a84 286eb75 79c5bf1 a943a84 286eb75 a943a84 286eb75 c002cde 286eb75 c002cde 286eb75 a943a84 286eb75 a943a84 10a369e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
import torch
import gradio as gr
import pytube as pt
from transformers import pipeline
MODEL_NAME = "BlueRaccoon/whisper-small-kab" # this always needs to stay in line 8 :D sorry for the hackiness
lang = "uz"
device = 0 if torch.cuda.is_available() else "cpu"
pipe = pipeline(
task="automatic-speech-recognition",
model=MODEL_NAME,
chunk_length_s=30,
device=device,
)
pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe")
def transcribe(microphone, file_upload):
warn_output = ""
if (microphone is not None) and (file_upload is not None):
warn_output = (
"WARNING: You've uploaded an audio file and used the microphone. "
"The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
)
elif (microphone is None) and (file_upload is None):
return "ERROR: You have to either use the microphone or upload an audio file"
file = microphone if microphone is not None else file_upload
text = pipe(file)["text"]
return warn_output + text
def _return_yt_html_embed(yt_url):
video_id = yt_url.split("?v=")[-1]
HTML_str = (
f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
" </center>"
)
return HTML_str
def yt_transcribe(yt_url):
yt = pt.YouTube(yt_url)
html_embed_str = _return_yt_html_embed(yt_url)
stream = yt.streams.filter(only_audio=True)[0]
stream.download(filename="audio.mp3")
text = pipe("audio.mp3")["text"]
return html_embed_str, text
with gr.Blocks() as demo:
with gr.Tab("Transcribe Audio"):
gr.Markdown(
f"""
# Whisper Demo: Transcribe Audio
Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned
checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files
of arbitrary length.
"""
)
# Inputs for microphone recording or file upload
microphone_input = gr.Audio(type="filepath", label="Record or Upload Audio")
file_upload_input = gr.Audio(type="filepath", label="Upload Audio File (Optional)")
gr.Interface(
fn=transcribe,
inputs=[microphone_input, file_upload_input],
outputs=gr.Textbox(label="Transcription"),
)
with gr.Tab("Transcribe YouTube"):
gr.Markdown(
f"""
# Whisper Demo: Transcribe YouTube
Transcribe long-form YouTube videos with the click of a button! Demo uses the fine-tuned checkpoint
[{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of
arbitrary length.
"""
)
yt_url_input = gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")
gr.Interface(
fn=yt_transcribe,
inputs=[yt_url_input],
outputs=[gr.HTML(label="YouTube Video"), gr.Textbox(label="Transcription")],
)
demo.launch()
|