Upload Application

app.py

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+import time
+from pathlib import Path
+
+import gradio as gr
+from audio_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"]
+
+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 = Path("/shared_volume/whisper-finetuning/audio_filtered")
+    out_folder.mkdir(exist_ok=True)
+    temp_folder = Path("/shared_volume/whisper-finetuning/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=False,
+        output_dir=str(out_folder),
+        output_single_stem=separation_mode,
+    )
+    for i in progress.tqdm(range(50)):
+        time.sleep(0.01)
+
+    results = [out_folder / p for p in separator.separate()]
+    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:
+        instrument_stem_path = str(results[0])
+        reduce_audio_size(instrument_stem_path)
+        vocal_stem_path = str(results[1])
+        reduce_audio_size(vocal_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=True, favicon_path=Path(__file__).parent / "audiomack.svg")

requirements.txt

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+pathlib
+audio-separator
+pydub
+pytube