import os import gradio as gr import subprocess os.system("git clone https://github.com/doevent/FullSubNet-plus") os.system("mv FullSubNet-plus/speech_enhance .") os.system("mv FullSubNet-plus/config .") os.system("gdown https://drive.google.com/uc?id=1UJSt1G0P_aXry-u79LLU_l9tCnNa2u7C -O best_model.tar") from speech_enhance.tools.denoise_hf_clone_voice import start # If the file is too duration to inference def duration(input_audio) -> int: command = f"ffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1 -i {input_audio}" result = subprocess.run(command, shell=True, stdout=subprocess.PIPE) data = result.stdout.decode('ascii').rstrip() return int(float(data)) def inference(audio): try: if audio.find("audio") < 0: if duration(audio) >= 150: return "error.wav" result = start(to_list_files=[audio]) return result[0] except Exception as e: gr.Error(f"Maximum duration 150 sec\n{str(e)}") title = """

DeNoise Speech Enhancement

""" description = """ This is an unofficial demo for FullSubNet-plus: DeNoise Speech Enhancement. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below. Link to GitHub: - [FullSubNet +](https://github.com/hit-thusz-RookieCJ/FullSubNet-plus) """ twitter_link = "[![](https://img.shields.io/twitter/follow/DoEvent?label=@DoEvent&style=social)](https://twitter.com/DoEvent)" css = ''' h1#title { text-align: center; } ''' with gr.Blocks(css=css) as demo: gr.Markdown(title) gr.Markdown(description) gr.Markdown(twitter_link) with gr.Tab("Upload audio"): u_audio = gr.Audio(type="filepath", source="upload", label="Input audio") u_output = gr.Audio(type="filepath", label="Output audio") u_button = gr.Button("Submit") with gr.Tab("Record your voice"): m_audio = gr.Audio(ype="filepath", source="microphone", label="Record yourself reading something out loud") m_output = gr.Audio(type="filepath", label="Output audio") m_button = gr.Button("Submit") gr.Examples(examples=["man.wav", "woman.wav"], inputs=u_audio, outputs=u_output, fn=inference, cache_examples=True) u_button.click(inference, inputs=u_audio, outputs=u_output) m_button.click(inference, inputs=m_audio, outputs=m_output) gr.Markdown("
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") demo.queue(concurrency_count=1, api_open=False).launch(show_api=False, show_error=True)