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import os
os.system("pip install git+https://github.com/openai/whisper.git")
import gradio as gr
import whisper
model = whisper.load_model("base")
def inference(audio):
audio = whisper.load_audio(audio)
audio = whisper.pad_or_trim(audio)
mel = whisper.log_mel_spectrogram(audio).to(model.device)
_, probs = model.detect_language(mel)
options = whisper.DecodingOptions(fp16 = False)
result = whisper.decode(model, mel, options)
return result.text
iface = gr.Interface(
fn=inference,
inputs=gr.Audio(type="filepath", label="格式可為 WAV、MP3、OGG、FLAC、AAC、M4A、WMA，單聲道、多聲道均可。"),
outputs="text"
)
# 启动 Gradio 界面
iface.launch() |