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import time
from pathlib import Path
import gradio as gr
# import onnxruntime as rt
from audio_separator.separator import Separator
from pydub import AudioSegment
from pytube import YouTube
available_model = ["UVR-MDX-NET-Inst_HQ_3", "UVR-MDX-NET-Voc_FT", "UVR_MDXNET_KARA_2", "Kim_Vocal_2", "UVR_MDXNET_Main"]
base_path = Path(__file__).parent
def reduce_audio_size(audio_path):
s1 = AudioSegment.from_file(audio_path)
s1.export(audio_path, format="mp3", bitrate="64k")
def audio_sep(youtube_url, audio_path, separation_model, separation_mode, progress=gr.Progress()):
out_folder = base_path / "audio_filtered"
out_folder.mkdir(exist_ok=True)
temp_folder = base_path / "tmp"
temp_folder.mkdir(exist_ok=True)
print(youtube_url)
print(audio_path)
print(separation_model)
print(separation_mode)
youtube_url = youtube_url.strip()
if youtube_url is not None and youtube_url != "":
try:
print("Downloading YouTube audio...")
yt = YouTube(youtube_url)
video_id = yt.video_id
save_audio_path = temp_folder / f"{video_id}.mp3"
if yt.length > 5 * 60:
raise gr.Error("Video too long. Please use a video shorter than 5 minutes.")
stream = yt.streams.filter(only_audio=True).order_by("abr").desc().first()
stream.download(filename=str(save_audio_path))
audio_path = str(save_audio_path)
print("Downloaded YouTube audio")
except:
gr.Info("Something went wrong. Skipping to second input.")
if audio_path is None:
gr.Info("Please input an audio file or YouTube URL.")
return None, None
if len(separation_mode) == 1:
separation_mode = separation_mode[0]
elif len(separation_mode) == 0:
return None, None
else:
separation_mode = None
progress(0, desc="Starting...")
separator = Separator(
# audio_path,
# model_name=separation_model,
# use_cuda=True if rt.get_device() == "GPU" else False
output_dir=str(out_folder),
output_single_stem=separation_mode,
)
separator.load_model(separation_model)
# for i in progress.tqdm(range(50)):
# time.sleep(0.01)
results = [out_folder / p for p in separator.separate(audio_path)]
print(results)
# for i in progress.tqdm(range(50, 100)):
# time.sleep(0.01)
if separation_mode == "Instrument":
instrument_stem_path = str(results[0])
reduce_audio_size(instrument_stem_path)
vocal_stem_path = None
elif separation_mode == "Vocal":
instrument_stem_path = None
vocal_stem_path = str(results[0])
reduce_audio_size(vocal_stem_path)
else:
if "_(Instrumental)_" in str(results[0]):
instrument_stem_path = str(results[0])
reduce_audio_size(instrument_stem_path)
vocal_stem_path = str(results[1])
reduce_audio_size(vocal_stem_path)
else:
vocal_stem_path = str(results[0])
reduce_audio_size(vocal_stem_path)
instrument_stem_path = str(results[1])
reduce_audio_size(instrument_stem_path)
return instrument_stem_path, vocal_stem_path
gr.Interface(
audio_sep,
[
gr.Textbox(
label="YouTube video URL (No videos more than 5 mins)",
placeholder="https://www.youtube.com/watch?v=XXXXXXXXXXX",
),
gr.Audio(label="Audio Input", type="filepath"),
gr.Dropdown(available_model, label="Separation Model", value="UVR_MDXNET_KARA_2"),
gr.CheckboxGroup(choices=["Instrument", "Vocal"], label="Separation Mode", value=["Instrument", "Vocal"]),
],
[gr.Audio(label="Music/Instrument Output", type="filepath"), gr.Audio(label="Vocal Output", type="filepath")],
title="Audio Separator",
description="<center>Separate the music and vocal from the input audio</center>",
allow_flagging=False,
).queue().launch(share=False) |