audio-separator

Build error

App Files Files Community

_Noxty commited on Jan 19

Commit

292372b

verified ·

1 Parent(s): 24dac05

Update app.py

Browse files

Files changed (1) hide show

app.py +721 -597

app.py CHANGED Viewed

@@ -1,7 +1,188 @@
 import gradio as gr
-from separwator import *
-import os, subprocess
-import gc, re
 def leaderboard(list_filter, list_limit):
     try:
@@ -23,614 +204,557 @@ def leaderboard(list_filter, list_limit):
     except Exception as e:
         return f"Error: {e}"
-with gr.Blocks(theme=gr.themes.Base(), title = "🎵 Audio Separator UI 🎵") as app:
-    with gr.Row():
-        gr.Markdown("<h1><center> 🎵 Audio Separator UI 🎵")
-    with gr.Row():
-        with gr.Tabs():
-            with gr.TabItem("BS/Mel Roformer"):
-                with gr.Row():
-                    roformer_model = gr.Dropdown(
-                        label = "Select the model",
-                        choices = list(roformer_models.keys()),
-                        value = lambda : None,
-                        interactive = True
-                    )
-                    roformer_output_format = gr.Dropdown(
-                        label = "Select the output format",
-                        choices = output_format,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                with gr.Row():
-                    roformer_audio = gr.Audio(
-                        label = "Input audio",
-                        type = "filepath",
-                        interactive = True
-                    )
-                with gr.Column():
-                    with gr.Accordion("Advanced settings", open = False):
-                        with gr.Group():
-                            with gr.Row():
-                                roformer_segment_size = gr.Slider(
-                                    label = "Segment size",
-                                    info = "Larger consumes more resources, but may give better results",
-                                    minimum = 32,
-                                    maximum = 4000,
-                                    step = 32,
-                                    value = 256,
-                                    interactive = True
-                                )
-                            roformer_override_segment_size = gr.Checkbox(
-                                label = "Override segment size",
-                                info = "Override model default segment size instead of using the model default value",
-                                value = False,
-                                interactive = True
-                            )
-                        with gr.Row():
-                            roformer_overlap = gr.Slider(
-                                label = "Overlap",
-                                info = "Amount of overlap between prediction windows",
-                                minimum = 2,
-                                maximum = 10,
-                                step = 1,
-                                value = 8,
-                                interactive = True
-                            )
-                            roformer_batch_size = gr.Slider(
-                                label = "Batch size",
-                                info = "Larger consumes more RAM but may process slightly faster",
-                                minimum = 1,
-                                maximum = 16,
-                                step = 1,
-                                value = 1,
-                                interactive = True
-                            )
-                        with gr.Row():
-                            roformer_normalization_threshold = gr.Slider(
-                                label = "Normalization threshold",
-                                info = "The threshold for audio normalization",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                            roformer_amplification_threshold = gr.Slider(label = "Amplification threshold",info = "The threshold for audio amplification", minimum = 0.1,maximum = 1,step = 0.1,value = 0.1,interactive = True)
-                with gr.Row():
-                    roformer_button = gr.Button("Separate!", variant = "primary")
-                with gr.Row():
-                    roformer_stem1 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 1",
-                        type = "filepath"
-                    )
-                    roformer_stem2 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 2",
-                        type = "filepath"
-                    )
-                roformer_button.click(roformer_separator, [roformer_audio, roformer_model, roformer_output_format, roformer_segment_size, roformer_override_segment_size, roformer_overlap, roformer_batch_size, roformer_normalization_threshold, roformer_amplification_threshold], [roformer_stem1, roformer_stem2])
-            with gr.TabItem("MDX23C"):
-                with gr.Row():
-                    mdx23c_model = gr.Dropdown(
-                        label = "Select the model",
-                        choices = mdx23c_models,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                    mdx23c_output_format = gr.Dropdown(
-                        label = "Select the output format",
-                        choices = output_format,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                with gr.Row():
-                    mdx23c_audio = gr.Audio(
-                        label = "Input audio",
-                        type = "filepath",
-                        interactive = True
-                    )
-                with gr.Accordion("Advanced settings", open = False):
                     with gr.Group():
                         with gr.Row():
-                            mdx23c_segment_size = gr.Slider(
-                                minimum = 32,
-                                maximum = 4000,
-                                step = 32,
-                                label = "Segment size",
-                                info = "Larger consumes more resources, but may give better results",
-                                value = 256,
-                                interactive = True
-                            )
-                            mdx23c_override_segment_size = gr.Checkbox(
-                                label = "Override segment size",
-                                info = "Override model default segment size instead of using the model default value",
-                                value = False,
-                                interactive = True
-                            )
-                        with gr.Row():
-                            mdx23c_overlap = gr.Slider(
-                                minimum = 2,
-                                maximum = 50,
-                                step = 1,
-                                label = "Overlap",
-                                info = "Amount of overlap between prediction windows",
-                                value = 8,
-                                interactive = True
-                            )
-                            mdx23c_batch_size = gr.Slider(
-                                label = "Batch size",
-                                info = "Larger consumes more RAM but may process slightly faster",
-                                minimum = 1,
-                                maximum = 16,
-                                step = 1,
-                                value = 1,
-                                interactive = True
-                            )
-                        with gr.Row():
-                            mdx23c_normalization_threshold = gr.Slider(
-                                label = "Normalization threshold",
-                                info = "The threshold for audio normalization",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                            mdx23c_amplification_threshold = gr.Slider(
-                                label = "Amplification threshold",
-                                info = "The threshold for audio amplification",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                with gr.Row():
-                    mdx23c_button = gr.Button("Separate!", variant = "primary")
-                with gr.Row():
-                    mdx23c_stem1 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 1",
-                        type = "filepath"
-                    )
-                    mdx23c_stem2 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 2",
-                        type = "filepath"
-                    )
-                mdx23c_button.click(mdxc_separator, [mdx23c_audio, mdx23c_model, mdx23c_output_format, mdx23c_segment_size, mdx23c_override_segment_size, mdx23c_overlap, mdx23c_batch_size, mdx23c_normalization_threshold, mdx23c_amplification_threshold], [mdx23c_stem1, mdx23c_stem2])
-            with gr.TabItem("MDX-NET"):
-                with gr.Row():
-                    mdxnet_model = gr.Dropdown(
-                        label = "Select the model",
-                        choices = mdxnet_models,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                    mdxnet_output_format = gr.Dropdown(
-                        label = "Select the output format",
-                        choices = output_format,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                with gr.Row():
-                    mdxnet_audio = gr.Audio(
-                        label = "Input audio",
-                        type = "filepath",
-                        interactive = True
-                    )
-                with gr.Accordion("Advanced settings", open = False):
                     with gr.Group():
                         with gr.Row():
-                            mdxnet_hop_length = gr.Slider(
-                                label = "Hop length",
-                                info = "Usually called stride in neural networks; only change if you know what you're doing",
-                                minimum = 32,
-                                maximum = 2048,
-                                step = 32,
-                                value = 1024,
-                                interactive = True
-                            )
-                            mdxnet_segment_size = gr.Slider(
-                                minimum = 32,
-                                maximum = 4000,
-                                step = 32,
-                                label = "Segment size",
-                                info = "Larger consumes more resources, but may give better results",
-                                value = 256,
-                                interactive = True
-                            )
-                            mdxnet_denoise = gr.Checkbox(
-                                label = "Denoise",
-                                info = "Enable denoising during separation",
-                                value = True,
-                                interactive = True
-                            )
                         with gr.Row():
-                            mdxnet_overlap = gr.Slider(
-                                label = "Overlap",
-                                info = "Amount of overlap between prediction windows",
-                                minimum = 0.001,
-                                maximum = 0.999,
-                                step = 0.001,
-                                value = 0.25,
-                                interactive = True
-                            )
-                            mdxnet_batch_size = gr.Slider(
-                                label = "Batch size",
-                                info = "Larger consumes more RAM but may process slightly faster",
-                                minimum = 1,
-                                maximum = 16,
-                                step = 1,
-                                value = 1,
-                                interactive = True
-                            )
                         with gr.Row():
-                            mdxnet_normalization_threshold = gr.Slider(
-                                label = "Normalization threshold",
-                                info = "The threshold for audio normalization",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                            mdxnet_amplification_threshold = gr.Slider(
-                                label = "Amplification threshold",
-                                info = "The threshold for audio amplification",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                with gr.Row():
-                    mdxnet_button = gr.Button("Separate!", variant = "primary")
-                with gr.Row():
-                    mdxnet_stem1 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 1",
-                        type = "filepath"
-                    )
-                    mdxnet_stem2 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        label = "Stem 2",
-                        type = "filepath"
-                    )
-                mdxnet_button.click(mdxnet_separator, [mdxnet_audio, mdxnet_model, mdxnet_output_format, mdxnet_hop_length, mdxnet_segment_size, mdxnet_denoise, mdxnet_overlap, mdxnet_batch_size, mdxnet_normalization_threshold, mdxnet_amplification_threshold], [mdxnet_stem1, mdxnet_stem2])
-            with gr.TabItem("VR ARCH"):
-                with gr.Row():
-                    vrarch_model = gr.Dropdown(
-                        label = "Select the model",
-                        choices = vrarch_models,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                    vrarch_output_format = gr.Dropdown(
-                        label = "Select the output format",
-                        choices = output_format,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                with gr.Row():
-                    vrarch_audio = gr.Audio(
-                        label = "Input audio",
-                        type = "filepath",
-                        interactive = True
-                    )
-                with gr.Accordion("Advanced settings", open = False):
                     with gr.Group():
                         with gr.Row():
-                            vrarch_window_size = gr.Slider(
-                                label = "Window size",
-                                info = "Balance quality and speed. 1024 = fast but lower, 320 = slower but better quality",
-                                minimum=320,
-                                maximum=1024,
-                                step=32,
-                                value = 512,
-                                interactive = True
-                            )
-                            vrarch_agression = gr.Slider(
-                                minimum = 1,
-                                maximum = 50,
-                                step = 1,
-                                label = "Agression",
-                                info = "Intensity of primary stem extraction",
-                                value = 5,
-                                interactive = True
-                            )
-                            vrarch_tta = gr.Checkbox(
-                                label = "TTA",
-                                info = "Enable Test-Time-Augmentation; slow but improves quality",
-                                value = True,
-                                visible = True,
-                                interactive = True
-                            )
                         with gr.Row():
-                            vrarch_post_process = gr.Checkbox(
-                                label = "Post process",
-                                info = "Identify leftover artifacts within vocal output; may improve separation for some songs",
-                                value = False,
-                                visible = True,
-                                interactive = True
-                            )
-                            vrarch_post_process_threshold = gr.Slider(
-                                label = "Post process threshold",
-                                info = "Threshold for post-processing",
-                                minimum = 0.1,
-                                maximum = 0.3,
-                                step = 0.1,
-                                value = 0.2,
-                                interactive = True
-                            )
                         with gr.Row():
-                            vrarch_high_end_process = gr.Checkbox(
-                                label = "High end process",
-                                info = "Mirror the missing frequency range of the output",
-                                value = False,
-                                visible = True,
-                                interactive = True,
-                            )
-                            vrarch_batch_size = gr.Slider(
-                                label = "Batch size",
-                                info = "Larger consumes more RAM but may process slightly faster",
-                                minimum = 1,
-                                maximum = 16,
-                                step = 1,
-                                value = 1,
-                                interactive = True
-                            )
                         with gr.Row():
-                            vrarch_normalization_threshold = gr.Slider(
-                                label = "Normalization threshold",
-                                info = "The threshold for audio normalization",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                            vrarch_amplification_threshold = gr.Slider(
-                                label = "Amplification threshold",
-                                info = "The threshold for audio amplification",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                with gr.Row():
-                    vrarch_button = gr.Button("Separate!", variant = "primary")
-                with gr.Row():
-                    vrarch_stem1 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 1"
-                    )
-                    vrarch_stem2 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 2"
-                    )
-                vrarch_button.click(vrarch_separator, [vrarch_audio, vrarch_model, vrarch_output_format, vrarch_window_size, vrarch_agression, vrarch_tta, vrarch_post_process, vrarch_post_process_threshold, vrarch_high_end_process, vrarch_batch_size, vrarch_normalization_threshold, vrarch_amplification_threshold], [vrarch_stem1, vrarch_stem2])
-            with gr.TabItem("Demucs"):
-                with gr.Row():
-                    demucs_model = gr.Dropdown(
-                        label = "Select the model",
-                        choices = demucs_models,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                    demucs_output_format = gr.Dropdown(
-                        label = "Select the output format",
-                        choices = output_format,
-                        value = lambda : None,
-                        interactive = True
-                    )
-                with gr.Row():
-                    demucs_audio = gr.Audio(
-                        label = "Input audio",
-                        type = "filepath",
-                        interactive = True
-                    )
-                with gr.Accordion("Advanced settings", open = False):
                     with gr.Group():
                         with gr.Row():
-                            demucs_shifts = gr.Slider(
-                                label = "Shifts",
-                                info = "Number of predictions with random shifts, higher = slower but better quality",
-                                minimum = 1,
-                                maximum = 20,
-                                step = 1,
-                                value = 2,
-                                interactive = True
-                            )
-                            demucs_segment_size = gr.Slider(
-                                label = "Segment size",
-                                info = "Size of segments into which the audio is split. Higher = slower but better quality",
-                                minimum = 1,
-                                maximum = 100,
-                                step = 1,
-                                value = 40,
-                                interactive = True
-                            )
-                            demucs_segments_enabled = gr.Checkbox(
-                                label = "Segment-wise processing",
-                                info = "Enable segment-wise processing",
-                                value = True,
-                                interactive = True
-                            )
                         with gr.Row():
-                            demucs_overlap = gr.Slider(
-                                label = "Overlap",
-                                info = "Overlap between prediction windows. Higher = slower but better quality",
-                                minimum=0.001,
-                                maximum=0.999,
-                                step=0.001,
-                                value = 0.25,
-                                interactive = True
-                            )
-                            demucs_batch_size = gr.Slider(
-                                label = "Batch size",
-                                info = "Larger consumes more RAM but may process slightly faster",
-                                minimum = 1,
-                                maximum = 16,
-                                step = 1,
-                                value = 1,
-                                interactive = True
-                            )
                         with gr.Row():
-                            demucs_normalization_threshold = gr.Slider(
-                                label = "Normalization threshold",
-                                info = "The threshold for audio normalization",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                            demucs_amplification_threshold = gr.Slider(
-                                label = "Amplification threshold",
-                                info = "The threshold for audio amplification",
-                                minimum = 0.1,
-                                maximum = 1,
-                                step = 0.1,
-                                value = 0.1,
-                                interactive = True
-                            )
-                    with gr.Row():
-                        gr.Markdown("You can paste the link to the video/audio from many sites, check the complete list [here](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)")
-                    with gr.Row():
-                        demucs_download_button = gr.Button(
-                            "Download!",
-                            variant = "primary"
-                        )
-                with gr.Row():
-                    demucs_button = gr.Button("Separate!", variant = "primary")
-                with gr.Row():
-                    demucs_stem1 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 1"
-                    )
-                    demucs_stem2 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 2"
-                    )
-                with gr.Row():
-                    demucs_stem3 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 3"
-                    )
-                    demucs_stem4 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 4"
-                    )
-                with gr.Row(visible=False) as stem6:
-                    demucs_stem5 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 5"
-                    )
-                    demucs_stem6 = gr.Audio(
-                        show_download_button = True,
-                        interactive = False,
-                        type = "filepath",
-                        label = "Stem 6"
-                    )
-                demucs_model.change(update_stems, inputs=[demucs_model], outputs=stem6)
-                demucs_button.click(demucs_separator, [demucs_audio, demucs_model, demucs_output_format, demucs_shifts, demucs_segment_size, demucs_segments_enabled, demucs_overlap, demucs_batch_size, demucs_normalization_threshold, demucs_amplification_threshold], [demucs_stem1, demucs_stem2, demucs_stem3, demucs_stem4, demucs_stem5, demucs_stem6])
-            with gr.Tab("Leaderboard"):
-                with gr.Row(equal_height=True):
-                    list_filter = gr.Dropdown(value="vocals", choices=["vocals", "instrumental", "drums", "bass", "guitar", "piano", "other"], label="List filter", info="Filter and sort the model list by 'stem'")
-                    list_limit = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="List limit", info="Limit the number of models shown.")
-                    list_button = gr.Button("Show list", variant="primary")
-                output_list = gr.HTML(label="Leaderboard")
-            list_button.click(leaderboard, inputs=[list_filter, list_limit], outputs=output_list)
-            with gr.TabItem("Credits"):
-                gr.Markdown(
-                    """
-                    audio separator UI created by [Eddycrack 864](https://github.com/Eddycrack864) & [_noxty](https://huggingface.co/theNeofr).
-                    * python-audio-separator by [beveradb](https://github.com/beveradb).
-                    * Thanks to [Mikus](https://github.com/cappuch) for the help with the code.
-                    * Thanks to [Nick088](https://huggingface.co/Nick088) for the help to fix roformers.
-                    * Thanks to [ArisDev](https://github.com/aris-py) for porting UVR5 UI to Kaggle and improvements.
-                    * Thanks to [Bebra777228](https://github.com/Bebra777228)'s code for guiding me to improve my code.
-                    You can donate to the original UVR5 project here:
-                    [!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](https://www.buymeacoffee.com/uvr5)
-                    """
-                )
-                gr.Markdown(
-                    """
-                    <h1> similar of this project\n
-                    [Audio_separator by r3gm](https://huggingface.co/spaces/r3gm/Audio_separator)\n
-                    [Audio-Separator by Politrees](https://huggingface.co/spaces/Politrees/Audio-Separator)\n
-                    [UVR5 UI by Eddycrack 864](https://huggingface.co/spaces/Eddycrack864/UVR5-UI)
-                    """
-                )
-app.queue()
-app.launch(share=True, debug=True)

+import os
+import re
+import torch
+import shutil
+import logging
+import subprocess
 import gradio as gr
+from audio_separator.separator import Separator
+device = "cuda" if torch.cuda.is_available() else "cpu"
+use_autocast = device == "cuda"
+#=========================#
+#     Roformer Models     #
+#=========================#
+ROFORMER_MODELS = {
+    # BS Roformer
+    'BS-Roformer-Viperx-1053': 'model_bs_roformer_ep_937_sdr_10.5309.ckpt',
+    'BS-Roformer-Viperx-1296': 'model_bs_roformer_ep_368_sdr_12.9628.ckpt',
+    'BS-Roformer-Viperx-1297': 'model_bs_roformer_ep_317_sdr_12.9755.ckpt',
+    'BS-Roformer-De-Reverb': 'deverb_bs_roformer_8_384dim_10depth.ckpt',
+    'BS Roformer | Chorus Male-Female by Sucial': 'model_chorus_bs_roformer_ep_267_sdr_24.1275.ckpt',
+    # MelBand Roformer
+    'Mel-Roformer-Crowd-Aufr33-Viperx': 'mel_band_roformer_crowd_aufr33_viperx_sdr_8.7144.ckpt',
+    'Mel-Roformer-Karaoke-Aufr33-Viperx': 'mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt',
+    'Mel-Roformer-Viperx-1143': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt',
+    'MelBand Roformer | De-Reverb-Echo by Sucial': 'dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt',
+    'MelBand Roformer | De-Reverb-Echo V2 by Sucial': 'dereverb-echo_mel_band_roformer_sdr_13.4843_v2.ckpt',
+    'MelBand Roformer | Aspiration Less Aggressive by Sucial': 'aspiration_mel_band_roformer_less_aggr_sdr_18.1201.ckpt',
+    'MelBand Roformer | Aspiration by Sucial': 'aspiration_mel_band_roformer_sdr_18.9845.ckpt',
+    'MelBand Roformer | De-Reverb Less Aggressive by anvuew': 'dereverb_mel_band_roformer_less_aggressive_anvuew_sdr_18.8050.ckpt',
+    'MelBand Roformer | De-Reverb by anvuew': 'dereverb_mel_band_roformer_anvuew_sdr_19.1729.ckpt',
+    'MelBand Roformer | Vocals by Kimberley Jensen': 'vocals_mel_band_roformer.ckpt',
+    'Mel-Roformer-Denoise-Aufr33-Aggr': 'denoise_mel_band_roformer_aufr33_aggr_sdr_27.9768.ckpt',
+    'Mel-Roformer-Denoise-Aufr33': 'denoise_mel_band_roformer_aufr33_sdr_27.9959.ckpt',
+    'MelBand Roformer | Bleed Suppressor V1 by unwa-97chris': 'mel_band_roformer_bleed_suppressor_v1.ckpt',
+    # MelBand Roformer Kim
+    'MelBand Roformer Kim | FT by unwa': 'mel_band_roformer_kim_ft_unwa.ckpt',
+    'MelBand Roformer Kim | Big Beta 4 FT by unwa': 'melband_roformer_big_beta4.ckpt',
+    'MelBand Roformer Kim | Big Beta 5e FT by unwa': 'melband_roformer_big_beta5e.ckpt',
+    'MelBand Roformer Kim | Inst V1 by Unwa': 'melband_roformer_inst_v1.ckpt',
+    'MelBand Roformer Kim | Inst V1 (E) by Unwa': 'melband_roformer_inst_v1e.ckpt',
+    'MelBand Roformer Kim | Inst V2 by Unwa': 'melband_roformer_inst_v2.ckpt',
+    'MelBand Roformer Kim | InstVoc Duality V1 by Unwa': 'melband_roformer_instvoc_duality_v1.ckpt',
+    'MelBand Roformer Kim | InstVoc Duality V2 by Unwa': 'melband_roformer_instvox_duality_v2.ckpt',
+    'MelBand Roformer Kim | SYHFT by SYH99999': 'MelBandRoformerSYHFT.ckpt',
+    'MelBand Roformer Kim | SYHFT V2 by SYH99999': 'MelBandRoformerSYHFTV2.ckpt',
+    'MelBand Roformer Kim | SYHFT V2.5 by SYH99999': 'MelBandRoformerSYHFTV2.5.ckpt',
+    'MelBand Roformer Kim | SYHFT V3 by SYH99999': 'MelBandRoformerSYHFTV3Epsilon.ckpt',
+    'MelBand Roformer Kim | Big SYHFT V1 by SYH99999': 'MelBandRoformerBigSYHFTV1.ckpt',
+}
+#=========================#
+#      MDX23C Models      #
+#=========================#
+MDX23C_MODELS = {
+    'MDX23C DrumSep by aufr33-jarredou': 'MDX23C-DrumSep-aufr33-jarredou.ckpt',
+    'MDX23C De-Reverb by aufr33-jarredou': 'MDX23C-De-Reverb-aufr33-jarredou.ckpt',
+    'MDX23C-InstVoc HQ': 'MDX23C-8KFFT-InstVoc_HQ.ckpt',
+    'VIP | MDX23C-InstVoc HQ 2': 'MDX23C-8KFFT-InstVoc_HQ_2.ckpt',
+    'VIP | MDX23C_D1581': 'MDX23C_D1581.ckpt',
+}
+#=========================#
+#     MDXN-NET Models     #
+#=========================#
+MDXNET_MODELS = {
+    'UVR-MDX-NET 1': 'UVR_MDXNET_1_9703.onnx',
+    'UVR-MDX-NET 2': 'UVR_MDXNET_2_9682.onnx',
+    'UVR-MDX-NET 3': 'UVR_MDXNET_3_9662.onnx',
+    'UVR_MDXNET_9482': 'UVR_MDXNET_9482.onnx',
+    'UVR-MDX-NET Inst 1': 'UVR-MDX-NET-Inst_1.onnx',
+    'UVR-MDX-NET Inst 2': 'UVR-MDX-NET-Inst_2.onnx',
+    'UVR-MDX-NET Inst 3': 'UVR-MDX-NET-Inst_3.onnx',
+    'UVR-MDX-NET Inst HQ 1': 'UVR-MDX-NET-Inst_HQ_1.onnx',
+    'UVR-MDX-NET Inst HQ 2': 'UVR-MDX-NET-Inst_HQ_2.onnx',
+    'UVR-MDX-NET Inst HQ 3': 'UVR-MDX-NET-Inst_HQ_3.onnx',
+    'UVR-MDX-NET Inst HQ 4': 'UVR-MDX-NET-Inst_HQ_4.onnx',
+    'UVR-MDX-NET Inst HQ 5': 'UVR-MDX-NET-Inst_HQ_5.onnx',
+    'UVR-MDX-NET Inst Main': 'UVR-MDX-NET-Inst_Main.onnx',
+    'UVR-MDX-NET Karaoke': 'UVR_MDXNET_KARA.onnx',
+    'UVR-MDX-NET Karaoke 2': 'UVR_MDXNET_KARA_2.onnx',
+    'UVR-MDX-NET Main': 'UVR_MDXNET_Main.onnx',
+    'UVR-MDX-NET Voc FT': 'UVR-MDX-NET-Voc_FT.onnx',
+    'Kim Inst': 'Kim_Inst.onnx',
+    'Kim Vocal 1': 'Kim_Vocal_1.onnx',
+    'Kim Vocal 2': 'Kim_Vocal_2.onnx',
+    'kuielab_a_bass': 'kuielab_a_bass.onnx',
+    'kuielab_a_drums': 'kuielab_a_drums.onnx',
+    'kuielab_a_other': 'kuielab_a_other.onnx',
+    'kuielab_a_vocals': 'kuielab_a_vocals.onnx',
+    'kuielab_b_bass': 'kuielab_b_bass.onnx',
+    'kuielab_b_drums': 'kuielab_b_drums.onnx',
+    'kuielab_b_other': 'kuielab_b_other.onnx',
+    'kuielab_b_vocals': 'kuielab_b_vocals.onnx',
+    'Reverb HQ By FoxJoy': 'Reverb_HQ_By_FoxJoy.onnx',
+    'VIP | UVR-MDX-NET_Inst_82_beta': 'UVR-MDX-NET_Inst_82_beta.onnx',
+    'VIP | UVR-MDX-NET_Inst_90_beta': 'UVR-MDX-NET_Inst_90_beta.onnx',
+    'VIP | UVR-MDX-NET_Inst_187_beta': 'UVR-MDX-NET_Inst_187_beta.onnx',
+    'VIP | UVR-MDX-NET-Inst_full_292': 'UVR-MDX-NET-Inst_full_292.onnx',
+    'VIP | UVR-MDX-NET_Main_340': 'UVR-MDX-NET_Main_340.onnx',
+    'VIP | UVR-MDX-NET_Main_390': 'UVR-MDX-NET_Main_390.onnx',
+    'VIP | UVR-MDX-NET_Main_406': 'UVR-MDX-NET_Main_406.onnx',
+    'VIP | UVR-MDX-NET_Main_427': 'UVR-MDX-NET_Main_427.onnx',
+    'VIP | UVR-MDX-NET_Main_438': 'UVR-MDX-NET_Main_438.onnx',
+}
+#========================#
+#     VR-ARCH Models     #
+#========================#
+VR_ARCH_MODELS = {
+    '1_HP-UVR': '1_HP-UVR.pth',
+    '2_HP-UVR': '2_HP-UVR.pth',
+    '3_HP-Vocal-UVR': '3_HP-Vocal-UVR.pth',
+    '4_HP-Vocal-UVR': '4_HP-Vocal-UVR.pth',
+    '5_HP-Karaoke-UVR': '5_HP-Karaoke-UVR.pth',
+    '6_HP-Karaoke-UVR': '6_HP-Karaoke-UVR.pth',
+    '7_HP2-UVR': '7_HP2-UVR.pth',
+    '8_HP2-UVR': '8_HP2-UVR.pth',
+    '9_HP2-UVR': '9_HP2-UVR.pth',
+    '10_SP-UVR-2B-32000-1': '10_SP-UVR-2B-32000-1.pth',
+    '11_SP-UVR-2B-32000-2': '11_SP-UVR-2B-32000-2.pth',
+    '12_SP-UVR-3B-44100': '12_SP-UVR-3B-44100.pth',
+    '13_SP-UVR-4B-44100-1': '13_SP-UVR-4B-44100-1.pth',
+    '14_SP-UVR-4B-44100-2': '14_SP-UVR-4B-44100-2.pth',
+    '15_SP-UVR-MID-44100-1': '15_SP-UVR-MID-44100-1.pth',
+    '16_SP-UVR-MID-44100-2': '16_SP-UVR-MID-44100-2.pth',
+    '17_HP-Wind_Inst-UVR': '17_HP-Wind_Inst-UVR.pth',
+    'MGM_HIGHEND_v4': 'MGM_HIGHEND_v4.pth',
+    'MGM_LOWEND_A_v4': 'MGM_LOWEND_A_v4.pth',
+    'MGM_LOWEND_B_v4': 'MGM_LOWEND_B_v4.pth',
+    'MGM_MAIN_v4': 'MGM_MAIN_v4.pth',
+    'UVR-BVE-4B_SN-44100-1': 'UVR-BVE-4B_SN-44100-1.pth',
+    'UVR-De-Reverb by aufr33-jarredou': 'UVR-De-Reverb-aufr33-jarredou.pth',
+    'UVR-De-Echo-Aggressive by FoxJoy': 'UVR-De-Echo-Aggressive.pth',
+    'UVR-De-Echo-Normal by FoxJoy': 'UVR-De-Echo-Normal.pth',
+    'UVR-DeEcho-DeReverb by FoxJoy': 'UVR-DeEcho-DeReverb.pth',
+    'UVR-DeNoise-Lite by FoxJoy': 'UVR-DeNoise-Lite.pth',
+    'UVR-DeNoise by FoxJoy': 'UVR-DeNoise.pth',
+}
+#=======================#
+#     DEMUCS Models     #
+#=======================#
+DEMUCS_MODELS = {
+    'htdemucs': 'htdemucs.yaml',
+    'htdemucs_6s': 'htdemucs_6s.yaml',
+    'htdemucs_ft': 'htdemucs_ft.yaml',
+    'hdemucs_mmi': 'hdemucs_mmi.yaml',
+}
+OUTPUT_FORMAT = ["wav", "flac", "mp3", "ogg", "opus", "m4a", "aiff", "ac3"]
+def print_message(input_file, model_name):
+    """Prints information about the audio separation process."""
+    base_name = os.path.splitext(os.path.basename(input_file))[0]
+    print("\n")
+    print("🎵 Audio-Separator 🎵")
+    print("Input audio:", base_name)
+    print("Separation Model:", model_name)
+    print("Audio Separation Process...")
+def prepare_output_dir(input_file, output_dir):
+    """Create a directory for the output files and clean it if it already exists."""
+    base_name = os.path.splitext(os.path.basename(input_file))[0]
+    out_dir = os.path.join(output_dir, base_name)
+    try:
+        if os.path.exists(out_dir):
+            shutil.rmtree(out_dir)
+        os.makedirs(out_dir)
+    except Exception as e:
+        raise RuntimeError(f"Failed to prepare output directory {out_dir}: {e}")
+    return out_dir
+def rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model):
+    base_name = os.path.splitext(os.path.basename(audio))[0]
+    stems = {
+        "Vocals": vocals_stem.replace("NAME", base_name).replace("STEM", "Vocals").replace("MODEL", model),
+        "Instrumental": instrumental_stem.replace("NAME", base_name).replace("STEM", "Instrumental").replace("MODEL", model),
+        "Drums": drums_stem.replace("NAME", base_name).replace("STEM", "Drums").replace("MODEL", model),
+        "Bass": bass_stem.replace("NAME", base_name).replace("STEM", "Bass").replace("MODEL", model),
+        "Other": other_stem.replace("NAME", base_name).replace("STEM", "Other").replace("MODEL", model),
+        "Guitar": guitar_stem.replace("NAME", base_name).replace("STEM", "Guitar").replace("MODEL", model),
+        "Piano": piano_stem.replace("NAME", base_name).replace("STEM", "Piano").replace("MODEL", model),
+    }
+    return stems
 def leaderboard(list_filter, list_limit):
     try:
     except Exception as e:
         return f"Error: {e}"
+def roformer_separator(audio, model_key, seg_size, override_seg_size, overlap, pitch_shift, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, progress=gr.Progress(track_tqdm=True)):
+    """Separate audio using Roformer model."""
+    stemname = rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model_key)
+    print_message(audio, model_key)
+    model = ROFORMER_MODELS[model_key]
+    try:
+        out_dir = prepare_output_dir(audio, out_dir)
+        separator = Separator(
+            log_level=logging.WARNING,
+            model_file_dir=model_dir,
+            output_dir=out_dir,
+            output_format=out_format,
+            normalization_threshold=norm_thresh,
+            amplification_threshold=amp_thresh,
+            use_autocast=use_autocast,
+            mdxc_params={
+                "segment_size": seg_size,
+                "override_model_segment_size": override_seg_size,
+                "batch_size": batch_size,
+                "overlap": overlap,
+                "pitch_shift": pitch_shift,
+            }
+        )
+        progress(0.2, desc="Model loaded...")
+        separator.load_model(model_filename=model)
+        progress(0.7, desc="Audio separated...")
+        separation = separator.separate(audio, stemname)
+        print(f"Separation complete!\nResults: {', '.join(separation)}")
+        stems = [os.path.join(out_dir, file_name) for file_name in separation]
+        return stems[0], stems[1]
+    except Exception as e:
+        raise RuntimeError(f"Roformer separation failed: {e}") from e
+def mdx23c_separator(audio, model_key, seg_size, override_seg_size, overlap, pitch_shift, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, progress=gr.Progress(track_tqdm=True)):
+    """Separate audio using MDX23C model."""
+    stemname = rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model_key)
+    print_message(audio, model_key)
+    model = MDX23C_MODELS[model_key]
+    try:
+        out_dir = prepare_output_dir(audio, out_dir)
+        separator = Separator(
+            log_level=logging.WARNING,
+            model_file_dir=model_dir,
+            output_dir=out_dir,
+            output_format=out_format,
+            normalization_threshold=norm_thresh,
+            amplification_threshold=amp_thresh,
+            use_autocast=use_autocast,
+            mdxc_params={
+                "segment_size": seg_size,
+                "override_model_segment_size": override_seg_size,
+                "batch_size": batch_size,
+                "overlap": overlap,
+                "pitch_shift": pitch_shift,
+            }
+        )
+        progress(0.2, desc="Model loaded...")
+        separator.load_model(model_filename=model)
+        progress(0.7, desc="Audio separated...")
+        separation = separator.separate(audio, stemname)
+        print(f"Separation complete!\nResults: {', '.join(separation)}")
+        stems = [os.path.join(out_dir, file_name) for file_name in separation]
+        return stems[0], stems[1]
+    except Exception as e:
+        raise RuntimeError(f"MDX23C separation failed: {e}") from e
+def mdx_separator(audio, model_key, hop_length, seg_size, overlap, denoise, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, progress=gr.Progress(track_tqdm=True)):
+    """Separate audio using MDX-NET model."""
+    stemname = rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model_key)
+    print_message(audio, model_key)
+    model = MDXNET_MODELS[model_key]
+    try:
+        out_dir = prepare_output_dir(audio, out_dir)
+        separator = Separator(
+            log_level=logging.WARNING,
+            model_file_dir=model_dir,
+            output_dir=out_dir,
+            output_format=out_format,
+            normalization_threshold=norm_thresh,
+            amplification_threshold=amp_thresh,
+            use_autocast=use_autocast,
+            mdx_params={
+                "hop_length": hop_length,
+                "segment_size": seg_size,
+                "overlap": overlap,
+                "batch_size": batch_size,
+                "enable_denoise": denoise,
+            }
+        )
+        progress(0.2, desc="Model loaded...")
+        separator.load_model(model_filename=model)
+        progress(0.7, desc="Audio separated...")
+        separation = separator.separate(audio, stemname)
+        print(f"Separation complete!\nResults: {', '.join(separation)}")
+        stems = [os.path.join(out_dir, file_name) for file_name in separation]
+        return stems[0], stems[1]
+    except Exception as e:
+        raise RuntimeError(f"MDX-NET separation failed: {e}") from e
+def vr_separator(audio, model_key, window_size, aggression, tta, post_process, post_process_threshold, high_end_process, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, progress=gr.Progress(track_tqdm=True)):
+    """Separate audio using VR ARCH model."""
+    stemname = rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model_key)
+    print_message(audio, model_key)
+    model = VR_ARCH_MODELS[model_key]
+    try:
+        out_dir = prepare_output_dir(audio, out_dir)
+        separator = Separator(
+            log_level=logging.WARNING,
+            model_file_dir=model_dir,
+            output_dir=out_dir,
+            output_format=out_format,
+            normalization_threshold=norm_thresh,
+            amplification_threshold=amp_thresh,
+            use_autocast=use_autocast,
+            vr_params={
+                "batch_size": batch_size,
+                "window_size": window_size,
+                "aggression": aggression,
+                "enable_tta": tta,
+                "enable_post_process": post_process,
+                "post_process_threshold": post_process_threshold,
+                "high_end_process": high_end_process,
+            }
+        )
+        progress(0.2, desc="Model loaded...")
+        separator.load_model(model_filename=model)
+        progress(0.7, desc="Audio separated...")
+        separation = separator.separate(audio, stemname)
+        print(f"Separation complete!\nResults: {', '.join(separation)}")
+        stems = [os.path.join(out_dir, file_name) for file_name in separation]
+        return stems[0], stems[1]
+    except Exception as e:
+        raise RuntimeError(f"VR ARCH separation failed: {e}") from e
+def demucs_separator(audio, model_key, seg_size, shifts, overlap, segments_enabled, model_dir, out_dir, out_format, norm_thresh, amp_thresh, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, progress=gr.Progress(track_tqdm=True)):
+    """Separate audio using Demucs model."""
+    stemname = rename_stems(audio, vocals_stem, instrumental_stem, other_stem, drums_stem, bass_stem, guitar_stem, piano_stem, model_key)
+    print_message(audio, model_key)
+    model = DEMUCS_MODELS[model_key]
+    try:
+        out_dir = prepare_output_dir(audio, out_dir)
+        separator = Separator(
+            log_level=logging.WARNING,
+            model_file_dir=model_dir,
+            output_dir=out_dir,
+            output_format=out_format,
+            normalization_threshold=norm_thresh,
+            amplification_threshold=amp_thresh,
+            use_autocast=use_autocast,
+            demucs_params={
+                "segment_size": seg_size,
+                "shifts": shifts,
+                "overlap": overlap,
+                "segments_enabled": segments_enabled,
+            }
+        )
+        progress(0.2, desc="Model loaded...")
+        separator.load_model(model_filename=model)
+        progress(0.7, desc="Audio separated...")
+        separation = separator.separate(audio, stemname)
+        print(f"Separation complete!\nResults: {', '.join(separation)}")
+        stems = [os.path.join(out_dir, file_name) for file_name in separation]
+        if model_key == "htdemucs_6s":
+            return stems[0], stems[1], stems[2], stems[3], stems[4], stems[5]
+        else:
+            return stems[0], stems[1], stems[2], stems[3], None, None
+    except Exception as e:
+        raise RuntimeError(f"Demucs separation failed: {e}") from e
+def update_stems(model):
+    """Update the visibility of stem outputs based on the selected Demucs model."""
+    if model == "htdemucs_6s":
+        return gr.update(visible=True)
+    else:
+        return gr.update(visible=False)
+def show_hide_params(param):
+    """Update the visibility of a parameter based on the checkbox state."""
+    return gr.update(visible=param)
+with gr.Blocks(
+    title="🎵 Audio-Separator by Politrees 🎵",
+    css="footer{display:none !important}",
+) as app:
+    gr.HTML("<h1><center> 🎵 Audio-Separator HF Demo 🎵 </center></h1>")
+    with gr.Tab("Roformer"):
+        with gr.Group():
+            with gr.Row():
+                roformer_model = gr.Dropdown(value="MelBand Roformer Kim | Big Beta 5e FT by unwa", label="Select the Model", choices=list(ROFORMER_MODELS.keys()), scale=3)
+                roformer_output_format = gr.Dropdown(value="wav", choices=OUTPUT_FORMAT, label="Output Format", info="The format of the output audio file.", scale=1)
+            with gr.Accordion("Advanced settings", open=False):
+                with gr.Column(variant='panel'):
                     with gr.Group():
+                        roformer_override_seg_size = gr.Checkbox(value=False, label="Override segment size", info="Override model default segment size instead of using the model default value.")
                         with gr.Row():
+                            roformer_seg_size = gr.Slider(minimum=32, maximum=4000, step=32, value=256, label="Segment Size", info="Larger consumes more resources, but may give better results.", visible=False)
+                            roformer_overlap = gr.Slider(minimum=2, maximum=10, step=1, value=8, label="Overlap", info="Amount of overlap between prediction windows. Lower is better but slower.")
+                            roformer_pitch_shift = gr.Slider(minimum=-24, maximum=24, step=1, value=0, label="Pitch shift", info="Shift audio pitch by a number of semitones while processing. may improve output for deep/high vocals.")
+                with gr.Column(variant='panel'):
                     with gr.Group():
                         with gr.Row():
+                            roformer_batch_size = gr.Slider(minimum=1, maximum=16, step=1, value=1, label="Batch Size", info="Larger consumes more RAM but may process slightly faster.")
+                            roformer_norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.")
+                            roformer_amp_threshold = gr.Slider(minimum=0.0, maximum=1, step=0.1, value=0.0, label="Amplification threshold", info="The threshold for audio amplification.")
+        with gr.Row():
+            roformer_audio = gr.Audio(label="Input Audio", type="filepath")
+        with gr.Row():
+            roformer_button = gr.Button("Separate!", variant="primary")
+        with gr.Row():
+            roformer_stem1 = gr.Audio(label="Stem 1", type="filepath", interactive=False)
+            roformer_stem2 = gr.Audio(label="Stem 2", type="filepath", interactive=False)
+    with gr.Tab("MDX23C"):
+        with gr.Group():
+            with gr.Row():
+                mdx23c_model = gr.Dropdown(value="MDX23C-InstVoc HQ", label="Select the Model", choices=list(MDX23C_MODELS.keys()), scale=3)
+                mdx23c_output_format = gr.Dropdown(value="wav", choices=OUTPUT_FORMAT, label="Output Format", info="The format of the output audio file.", scale=1)
+            with gr.Accordion("Advanced settings", open=False):
+                with gr.Column(variant='panel'):
+                    with gr.Group():
+                        mdx23c_override_seg_size = gr.Checkbox(value=False, label="Override segment size", info="Override model default segment size instead of using the model default value.")
                         with gr.Row():
+                            mdx23c_seg_size = gr.Slider(minimum=32, maximum=4000, step=32, value=256, label="Segment Size", info="Larger consumes more resources, but may give better results.", visible=False)
+                            mdx23c_overlap = gr.Slider(minimum=2, maximum=50, step=1, value=8, label="Overlap", info="Amount of overlap between prediction windows. Higher is better but slower.")
+                            mdx23c_pitch_shift = gr.Slider(minimum=-24, maximum=24, step=1, value=0, label="Pitch shift", info="Shift audio pitch by a number of semitones while processing. may improve output for deep/high vocals.")
+                with gr.Column(variant='panel'):
+                    with gr.Group():
                         with gr.Row():
+                            mdx23c_batch_size = gr.Slider(minimum=1, maximum=16, step=1, value=1, label="Batch Size", info="Larger consumes more RAM but may process slightly faster.")
+                            mdx23c_norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.")
+                            mdx23c_amp_threshold = gr.Slider(minimum=0.0, maximum=1, step=0.1, value=0.0, label="Amplification threshold", info="The threshold for audio amplification.")
+        with gr.Row():
+            mdx23c_audio = gr.Audio(label="Input Audio", type="filepath")
+        with gr.Row():
+            mdx23c_button = gr.Button("Separate!", variant="primary")
+        with gr.Row():
+            mdx23c_stem1 = gr.Audio(label="Stem 1", type="filepath", interactive=False)
+            mdx23c_stem2 = gr.Audio(label="Stem 2", type="filepath", interactive=False)
+    with gr.Tab("MDX-NET"):
+        with gr.Group():
+            with gr.Row():
+                mdx_model = gr.Dropdown(value="UVR-MDX-NET Inst HQ 5", label="Select the Model", choices=list(MDXNET_MODELS.keys()), scale=3)
+                mdx_output_format = gr.Dropdown(value="wav", choices=OUTPUT_FORMAT, label="Output Format", info="The format of the output audio file.", scale=1)
+            with gr.Accordion("Advanced settings", open=False):
+                with gr.Column(variant='panel'):
                     with gr.Group():
+                        mdx_denoise = gr.Checkbox(value=False, label="Denoise", info="Enable denoising after separation.")
                         with gr.Row():
+                            mdx_hop_length = gr.Slider(minimum=32, maximum=2048, step=32, value=1024, label="Hop Length", info="Usually called stride in neural networks; only change if you know what you're doing.")
+                            mdx_seg_size = gr.Slider(minimum=32, maximum=4000, step=32, value=256, label="Segment Size", info="Larger consumes more resources, but may give better results.")
+                            mdx_overlap = gr.Slider(minimum=0.001, maximum=0.999, step=0.001, value=0.25, label="Overlap", info="Amount of overlap between prediction windows. Higher is better but slower.")
+                with gr.Column(variant='panel'):
+                    with gr.Group():
                         with gr.Row():
+                            mdx_batch_size = gr.Slider(minimum=1, maximum=16, step=1, value=1, label="Batch Size", info="Larger consumes more RAM but may process slightly faster.")
+                            mdx_norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.")
+                            mdx_amp_threshold = gr.Slider(minimum=0.0, maximum=1, step=0.1, value=0.0, label="Amplification threshold", info="The threshold for audio amplification.")
+        with gr.Row():
+            mdx_audio = gr.Audio(label="Input Audio", type="filepath")
+        with gr.Row():
+            mdx_button = gr.Button("Separate!", variant="primary")
+        with gr.Row():
+            mdx_stem1 = gr.Audio(label="Stem 1", type="filepath", interactive=False)
+            mdx_stem2 = gr.Audio(label="Stem 2", type="filepath", interactive=False)
+    with gr.Tab("VR ARCH"):
+        with gr.Group():
+            with gr.Row():
+                vr_model = gr.Dropdown(value="1_HP-UVR", label="Select the Model", choices=list(VR_ARCH_MODELS.keys()), scale=3)
+                vr_output_format = gr.Dropdown(value="wav", choices=OUTPUT_FORMAT, label="Output Format", info="The format of the output audio file.", scale=1)
+            with gr.Accordion("Advanced settings", open=False):
+                with gr.Column(variant='panel'):
+                    with gr.Group():
                         with gr.Row():
+                            vr_post_process = gr.Checkbox(value=False, label="Post Process", info="Identify leftover artifacts within vocal output; may improve separation for some songs.")
+                            vr_tta = gr.Checkbox(value=False, label="TTA", info="Enable Test-Time-Augmentation; slow but improves quality.")
+                            vr_high_end_process = gr.Checkbox(value=False, label="High End Process", info="Mirror the missing frequency range of the output.")
                         with gr.Row():
+                            vr_post_process_threshold = gr.Slider(minimum=0.1, maximum=0.3, step=0.1, value=0.2, label="Post Process Threshold", info="Threshold for post-processing.", visible=False)
+                            vr_window_size = gr.Slider(minimum=320, maximum=1024, step=32, value=512, label="Window Size", info="Balance quality and speed. 1024 = fast but lower, 320 = slower but better quality.")
+                            vr_aggression = gr.Slider(minimum=1, maximum=100, step=1, value=5, label="Agression", info="Intensity of primary stem extraction.")
+                with gr.Column(variant='panel'):
                     with gr.Group():
                         with gr.Row():
+                            vr_batch_size = gr.Slider(minimum=1, maximum=16, step=1, value=1, label="Batch Size", info="Larger consumes more RAM but may process slightly faster.")
+                            vr_norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.")
+                            vr_amp_threshold = gr.Slider(minimum=0.0, maximum=1, step=0.1, value=0.0, label="Amplification threshold", info="The threshold for audio amplification.")
+        with gr.Row():
+            vr_audio = gr.Audio(label="Input Audio", type="filepath")
+        with gr.Row():
+            vr_button = gr.Button("Separate!", variant="primary")
+        with gr.Row():
+            vr_stem1 = gr.Audio(label="Stem 1", type="filepath", interactive=False)
+            vr_stem2 = gr.Audio(label="Stem 2", type="filepath", interactive=False)
+    with gr.Tab("Demucs"):
+        with gr.Group():
+            with gr.Row():
+                demucs_model = gr.Dropdown(value="htdemucs_ft", label="Select the Model", choices=list(DEMUCS_MODELS.keys()), scale=3)
+                demucs_output_format = gr.Dropdown(value="wav", choices=OUTPUT_FORMAT, label="Output Format", info="The format of the output audio file.", scale=1)
+            with gr.Accordion("Advanced settings", open=False):
+                with gr.Column(variant='panel'):
+                    with gr.Group():
+                        demucs_segments_enabled = gr.Checkbox(value=True, label="Segment-wise processing", info="Enable segment-wise processing.")
                         with gr.Row():
+                            demucs_seg_size = gr.Slider(minimum=1, maximum=100, step=1, value=40, label="Segment Size", info="Size of segments into which the audio is split. Higher = slower but better quality.")
+                            demucs_overlap = gr.Slider(minimum=0.001, maximum=0.999, step=0.001, value=0.25, label="Overlap", info="Overlap between prediction windows. Higher = slower but better quality.")
+                            demucs_shifts = gr.Slider(minimum=0, maximum=20, step=1, value=2, label="Shifts", info="Number of predictions with random shifts, higher = slower but better quality.")
+                with gr.Column(variant='panel'):
+                    with gr.Group():
                         with gr.Row():
+                            demucs_norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.")
+                            demucs_amp_threshold = gr.Slider(minimum=0.0, maximum=1, step=0.1, value=0.0, label="Amplification threshold", info="The threshold for audio amplification.")
+        with gr.Row():
+            demucs_audio = gr.Audio(label="Input Audio", type="filepath")
+        with gr.Row():
+            demucs_button = gr.Button("Separate!", variant="primary")
+        with gr.Row():
+            demucs_stem1 = gr.Audio(label="Stem 1", type="filepath", interactive=False)
+            demucs_stem2 = gr.Audio(label="Stem 2", type="filepath", interactive=False)
+        with gr.Row():
+            demucs_stem3 = gr.Audio(label="Stem 3", type="filepath", interactive=False)
+            demucs_stem4 = gr.Audio(label="Stem 4", type="filepath", interactive=False)
+        with gr.Row(visible=False) as stem6:
+            demucs_stem5 = gr.Audio(label="Stem 5", type="filepath", interactive=False)
+            demucs_stem6 = gr.Audio(label="Stem 6", type="filepath", interactive=False)
+    with gr.Tab("Settings"):
+        with gr.Group():
+            with gr.Row():
+                model_file_dir = gr.Textbox(value="/tmp/audio-separator-models/", label="Directory to cache model files", info="The directory where model files are stored.", placeholder="/tmp/audio-separator-models/")
+                output_dir = gr.Textbox(value="output", label="File output directory", info="The directory where output files will be saved.", placeholder="output")
+        with gr.Accordion("Rename Stems", open=False):
+            gr.Markdown(
+                """
+                Keys for automatic determination of input file names, stems, and models to simplify the construction of output file names.
+                Keys:
+                * **NAME** - Input File Name
+                * **STEM** - Stem Name (e.g., Vocals, Instrumental)
+                * **MODEL** - Model Name (e.g., BS-Roformer-Viperx-1297)
+                > Example:
+                > * **Usage:** NAME_(STEM)_MODEL
+                > * **Output File Name:** Music_(Vocals)_BS-Roformer-Viperx-1297
+                """
+            )
+            with gr.Row():
+                vocals_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Vocals Stem", info="Output example: Music_(Vocals)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+                instrumental_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Instrumental Stem", info="Output example: Music_(Instrumental)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+            other_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Other Stem", info="Output example: Music_(Other)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+            with gr.Row():
+                drums_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Drums Stem", info="Output example: Music_(Drums)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+                bass_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Bass Stem", info="Output example: Music_(Bass)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+            with gr.Row():
+                guitar_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Guitar Stem", info="Output example: Music_(Guitar)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+                piano_stem = gr.Textbox(value="NAME_(STEM)_MODEL", label="Piano Stem", info="Output example: Music_(Piano)_BS-Roformer-Viperx-1297", placeholder="NAME_(STEM)_MODEL")
+    with gr.Tab("Leaderboard"):
+        with gr.Group():
+            with gr.Row(equal_height=True):
+                list_filter = gr.Dropdown(value="vocals", choices=["vocals", "instrumental", "drums", "bass", "guitar", "piano", "other"], label="List filter", info="Filter and sort the model list by 'stem'")
+                list_limit = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="List limit", info="Limit the number of models shown.")
+                list_button = gr.Button("Show list", variant="primary")
+        output_list = gr.HTML(label="Leaderboard")
+    with gr.Tab("Credits"):
+        gr.Markdown(
+            """
+            This Space created by **[Politrees](https://github.com/Bebra777228) forked by [NeoFr](https://github.com/TheNeodev)**.
+            * python-audio-separator by **[beveradb](https://github.com/beveradb)**.
+            * Thanks to **[Hev832](https://huggingface.co/Hev832)** for the help with the code.
+            """
+        )
+    roformer_override_seg_size.change(show_hide_params, inputs=[roformer_override_seg_size], outputs=[roformer_seg_size])
+    mdx23c_override_seg_size.change(show_hide_params, inputs=[mdx23c_override_seg_size], outputs=[mdx23c_seg_size])
+    vr_post_process.change(show_hide_params, inputs=[vr_post_process], outputs=[vr_post_process_threshold])
+    demucs_model.change(update_stems, inputs=[demucs_model], outputs=stem6)
+    list_button.click(leaderboard, inputs=[list_filter, list_limit], outputs=output_list)
+    roformer_button.click(
+        roformer_separator,
+        inputs=[
+            roformer_audio,
+            roformer_model,
+            roformer_seg_size,
+            roformer_override_seg_size,
+            roformer_overlap,
+            roformer_pitch_shift,
+            model_file_dir,
+            output_dir,
+            roformer_output_format,
+            roformer_norm_threshold,
+            roformer_amp_threshold,
+            roformer_batch_size,
+            vocals_stem,
+            instrumental_stem,
+            other_stem,
+            drums_stem,
+            bass_stem,
+            guitar_stem,
+            piano_stem,
+        ],
+        outputs=[
+            roformer_stem1,
+            roformer_stem2,
+        ], concurrency_limit=1,
+    )
+    mdx23c_button.click(
+        mdx23c_separator,
+        inputs=[
+            mdx23c_audio,
+            mdx23c_model,
+            mdx23c_seg_size,
+            mdx23c_override_seg_size,
+            mdx23c_overlap,
+            mdx23c_pitch_shift,
+            model_file_dir,
+            output_dir,
+            mdx23c_output_format,
+            mdx23c_norm_threshold,
+            mdx23c_amp_threshold,
+            mdx23c_batch_size,
+            vocals_stem,
+            instrumental_stem,
+            other_stem,
+            drums_stem,
+            bass_stem,
+            guitar_stem,
+            piano_stem,
+        ],
+        outputs=[
+            mdx23c_stem1,
+            mdx23c_stem2,
+        ], concurrency_limit=1,
+    )
+    mdx_button.click(
+        mdx_separator,
+        inputs=[
+            mdx_audio,
+            mdx_model,
+            mdx_hop_length,
+            mdx_seg_size,
+            mdx_overlap,
+            mdx_denoise,
+            model_file_dir,
+            output_dir,
+            mdx_output_format,
+            mdx_norm_threshold,
+            mdx_amp_threshold,
+            mdx_batch_size,
+            vocals_stem,
+            instrumental_stem,
+            other_stem,
+            drums_stem,
+            bass_stem,
+            guitar_stem,
+            piano_stem,
+        ],
+        outputs=[
+            mdx_stem1,
+            mdx_stem2,
+        ], concurrency_limit=1,
+    )
+    vr_button.click(
+        vr_separator,
+        inputs=[
+            vr_audio,
+            vr_model,
+            vr_window_size,
+            vr_aggression,
+            vr_tta,
+            vr_post_process,
+            vr_post_process_threshold,
+            vr_high_end_process,
+            model_file_dir,
+            output_dir,
+            vr_output_format,
+            vr_norm_threshold,
+            vr_amp_threshold,
+            vr_batch_size,
+            vocals_stem,
+            instrumental_stem,
+            other_stem,
+            drums_stem,
+            bass_stem,
+            guitar_stem,
+            piano_stem,
+        ],
+        outputs=[
+            vr_stem1,
+            vr_stem2,
+        ], concurrency_limit=1,
+    )
+    demucs_button.click(
+        demucs_separator,
+        inputs=[
+            demucs_audio,
+            demucs_model,
+            demucs_seg_size,
+            demucs_shifts,
+            demucs_overlap,
+            demucs_segments_enabled,
+            model_file_dir,
+            output_dir,
+            demucs_output_format,
+            demucs_norm_threshold,
+            demucs_amp_threshold,
+            vocals_stem,
+            instrumental_stem,
+            other_stem,
+            drums_stem,
+            bass_stem,
+            guitar_stem,
+            piano_stem,
+        ],
+        outputs=[
+            demucs_stem1,
+            demucs_stem2,
+            demucs_stem3,
+            demucs_stem4,
+            demucs_stem5,
+            demucs_stem6,
+        ], concurrency_limit=1,
+    )
+def main():
+    app.queue().launch(share=True, debug=True)
+if __name__ == "__main__":
+    main()