Spaces:
Sleeping
Sleeping
File size: 2,633 Bytes
ccfa27a 37fa3c8 ccfa27a 16476dc ccfa27a 16476dc ccfa27a 1728aa5 ccfa27a 44f5653 ccfa27a d74df01 ccfa27a 44f5653 ccfa27a 16476dc ccfa27a d74df01 ccfa27a 44f5653 ccfa27a |
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 95 96 97 98 |
import torch
import gradio as gr
import pytube as pt
from transformers import pipeline
from huggingface_hub import model_info
MODEL_NAME = "openai/whisper-medium"
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipeline(
task="automatic-speech-recognition",
model=MODEL_NAME,
chunk_length_s=30,
device=device,
)
langs = model_info(MODEL_NAME).cardData["language"]
article = f"<details><summary>模型支持 {len(langs)} 语言! (单击展开)</summary>> {langs}</details>"
def transcribe(microphone, file_upload):
warn_output = ""
if (microphone is not None) and (file_upload is not None):
warn_output = (
"WARNING:上传一个音频文件或者使用麦克风录制. "
"使用麦克风录制音频文件丢弃上传的音频文件.\n"
)
elif (microphone is None) and (file_upload is None):
return "ERROR: 你必须使用麦克风录制或上传音频文件"
file = microphone if microphone is not None else file_upload
text = pipe(file,language='zh')["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
demo = gr.Blocks()
mf_transcribe = gr.Interface(
fn=transcribe,
inputs=[
gr.inputs.Audio(source="microphone", type="filepath", optional=True),
gr.inputs.Audio(source="upload", type="filepath", optional=True),
],
outputs="text",
layout="horizontal",
theme="huggingface",
title="口译示例: 音频转录",
description=(
"转录麦克风录制或上传的音频文件!"
),
article=article,
allow_flagging="never",
)
yt_transcribe = gr.Interface(
fn=yt_transcribe,
inputs=[gr.inputs.Textbox(lines=1, placeholder="请粘贴视频地址", label="视频地址URL")],
outputs=["html", "text"],
layout="horizontal",
theme="huggingface",
title="口译示例: 视频转录",
description=(
"转录上传的视频文件!"
),
article=article,
allow_flagging="never",
)
with demo:
gr.TabbedInterface([mf_transcribe, yt_transcribe], ["音频转录", "视频转录"])
demo.launch(enable_queue=True)
|