Spaces:
Running
Running
| import os | |
| import torch | |
| import shutil | |
| import logging | |
| 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-De-Reverb': 'deverb_bs_roformer_8_384dim_10depth.ckpt', | |
| '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', | |
| 'Mel-Roformer-Crowd-Aufr33-Viperx': 'mel_band_roformer_crowd_aufr33_viperx_sdr_8.7144.ckpt', | |
| 'Mel-Roformer-Denoise-Aufr33': 'denoise_mel_band_roformer_aufr33_sdr_27.9959.ckpt', | |
| 'Mel-Roformer-Denoise-Aufr33-Aggr': 'denoise_mel_band_roformer_aufr33_aggr_sdr_27.9768.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 Kim | Inst V1 by Unwa': 'melband_roformer_inst_v1.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', | |
| } | |
| #=========================# | |
| # MDX23C Models # | |
| #=========================# | |
| MDX23C_MODELS = [ | |
| 'MDX23C-8KFFT-InstVoc_HQ.ckpt', | |
| 'MDX23C-8KFFT-InstVoc_HQ_2.ckpt', | |
| 'MDX23C_D1581.ckpt', | |
| ] | |
| #=========================# | |
| # MDXN-NET Models # | |
| #=========================# | |
| MDXNET_MODELS = [ | |
| 'UVR-MDX-NET-Crowd_HQ_1.onnx', | |
| 'UVR-MDX-NET-Inst_1.onnx', | |
| 'UVR-MDX-NET-Inst_2.onnx', | |
| 'UVR-MDX-NET-Inst_3.onnx', | |
| 'UVR-MDX-NET-Inst_HQ_1.onnx', | |
| 'UVR-MDX-NET-Inst_HQ_2.onnx', | |
| 'UVR-MDX-NET-Inst_HQ_3.onnx', | |
| 'UVR-MDX-NET-Inst_HQ_4.onnx', | |
| 'UVR-MDX-NET-Inst_HQ_5.onnx', | |
| 'UVR-MDX-NET-Inst_full_292.onnx', | |
| 'UVR-MDX-NET-Voc_FT.onnx', | |
| 'UVR-MDX-NET_Inst_82_beta.onnx', | |
| 'UVR-MDX-NET_Inst_90_beta.onnx', | |
| 'UVR-MDX-NET_Inst_187_beta.onnx', | |
| 'UVR-MDX-NET_Main_340.onnx', | |
| 'UVR-MDX-NET_Main_390.onnx', | |
| 'UVR-MDX-NET_Main_406.onnx', | |
| 'UVR-MDX-NET_Main_427.onnx', | |
| 'UVR-MDX-NET_Main_438.onnx', | |
| 'UVR_MDXNET_1_9703.onnx', | |
| 'UVR_MDXNET_2_9682.onnx', | |
| 'UVR_MDXNET_3_9662.onnx', | |
| 'UVR_MDXNET_9482.onnx', | |
| 'UVR_MDXNET_KARA.onnx', | |
| 'UVR_MDXNET_KARA_2.onnx', | |
| 'UVR_MDXNET_Main.onnx', | |
| 'kuielab_a_bass.onnx', | |
| 'kuielab_a_drums.onnx', | |
| 'kuielab_a_other.onnx', | |
| 'kuielab_a_vocals.onnx', | |
| 'kuielab_b_bass.onnx', | |
| 'kuielab_b_drums.onnx', | |
| 'kuielab_b_other.onnx', | |
| 'kuielab_b_vocals.onnx', | |
| 'Kim_Inst.onnx', | |
| 'Kim_Vocal_1.onnx', | |
| 'Kim_Vocal_2.onnx', | |
| 'Reverb_HQ_By_FoxJoy.onnx', | |
| ] | |
| #========================# | |
| # VR-ARCH Models # | |
| #========================# | |
| VR_ARCH_MODELS = [ | |
| '1_HP-UVR.pth', | |
| '2_HP-UVR.pth', | |
| '3_HP-Vocal-UVR.pth', | |
| '4_HP-Vocal-UVR.pth', | |
| '5_HP-Karaoke-UVR.pth', | |
| '6_HP-Karaoke-UVR.pth', | |
| '7_HP2-UVR.pth', | |
| '8_HP2-UVR.pth', | |
| '9_HP2-UVR.pth', | |
| '10_SP-UVR-2B-32000-1.pth', | |
| '11_SP-UVR-2B-32000-2.pth', | |
| '12_SP-UVR-3B-44100.pth', | |
| '13_SP-UVR-4B-44100-1.pth', | |
| '14_SP-UVR-4B-44100-2.pth', | |
| '15_SP-UVR-MID-44100-1.pth', | |
| '16_SP-UVR-MID-44100-2.pth', | |
| '17_HP-Wind_Inst-UVR.pth', | |
| 'MGM_HIGHEND_v4.pth', | |
| 'MGM_LOWEND_A_v4.pth', | |
| 'MGM_LOWEND_B_v4.pth', | |
| 'MGM_MAIN_v4.pth', | |
| 'UVR-BVE-4B_SN-44100-1.pth', | |
| 'UVR-DeEcho-DeReverb.pth', | |
| 'UVR-De-Echo-Aggressive.pth', | |
| 'UVR-De-Echo-Normal.pth', | |
| 'UVR-DeNoise-Lite.pth', | |
| 'UVR-DeNoise.pth', | |
| ] | |
| #=======================# | |
| # DEMUCS Models # | |
| #=======================# | |
| DEMUCS_MODELS = [ | |
| 'hdemucs_mmi.yaml', | |
| 'htdemucs.yaml', | |
| 'htdemucs_6s.yaml', | |
| 'htdemucs_ft.yaml', | |
| ] | |
| 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 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, progress=gr.Progress()): | |
| """Separate audio using Roformer model.""" | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| 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, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| print(f"Separation complete!\nResults: {', '.join(separation)}") | |
| stems = [os.path.join(out_dir, file_name) for file_name in separation] | |
| return stems[1], stems[0] | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer separation failed: {e}") from e | |
| def mdx23c_separator(audio, model, seg_size, override_seg_size, overlap, pitch_shift, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, progress=gr.Progress(track_tqdm=True)): | |
| """Separate audio using MDX23C model.""" | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| print_message(audio, model) | |
| 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, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| print(f"Separation complete!\nResults: {', '.join(separation)}") | |
| stems = [os.path.join(out_dir, file_name) for file_name in separation] | |
| return stems[1], stems[0] | |
| except Exception as e: | |
| raise RuntimeError(f"MDX23C separation failed: {e}") from e | |
| def mdx_separator(audio, model, hop_length, seg_size, overlap, denoise, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, progress=gr.Progress()): | |
| """Separate audio using MDX-NET model.""" | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| print_message(audio, model) | |
| 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, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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, window_size, aggression, tta, post_process, post_process_threshold, high_end_process, model_dir, out_dir, out_format, norm_thresh, amp_thresh, batch_size, progress=gr.Progress()): | |
| """Separate audio using VR ARCH model.""" | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| print_message(audio, model) | |
| 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, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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, seg_size, shifts, overlap, segments_enabled, model_dir, out_dir, out_format, norm_thresh, amp_thresh, progress=gr.Progress()): | |
| """Separate audio using Demucs model.""" | |
| print_message(audio, model) | |
| 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) | |
| print(f"Separation complete!\nResults: {', '.join(separation)}") | |
| stems = [os.path.join(out_dir, file_name) for file_name in separation] | |
| if model == "htdemucs_6s.yaml": | |
| 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): | |
| if model == "htdemucs_6s.yaml": | |
| return gr.update(visible=True) | |
| else: | |
| return gr.update(visible=False) | |
| with gr.Blocks( | |
| title="🎵 Audio-Separator 🎵", | |
| #css="footer{display:none !important}", | |
| theme="theNeofr/Syne" | |
| ) as app: | |
| gr.HTML("<h1> 🎵 Audio-Separator 🎵 </h1>") | |
| with gr.Tab("Roformer"): | |
| with gr.Group(): | |
| with gr.Row(): | |
| roformer_model = gr.Dropdown(label="Select the Model", choices=list(ROFORMER_MODELS.keys())) | |
| 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.") | |
| 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.") | |
| 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=-12, maximum=12, 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.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(label="Select the Model", choices=MDX23C_MODELS) | |
| 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.") | |
| 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.") | |
| 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=-12, maximum=12, 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.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(label="Select the Model", choices=MDXNET_MODELS) | |
| 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.") | |
| mdx_denoise = gr.Checkbox(value=False, label="Denoise", info="Enable denoising after separation.") | |
| 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(label="Select the Model", choices=VR_ARCH_MODELS) | |
| with gr.Row(): | |
| 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=50, step=1, value=5, label="Agression", info="Intensity of primary stem extraction.") | |
| vr_tta = gr.Checkbox(value=False, label="TTA", info="Enable Test-Time-Augmentation; slow but improves quality.") | |
| vr_post_process = gr.Checkbox(value=False, label="Post Process", info="Identify leftover artifacts within vocal output; may improve separation for some songs.") | |
| 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.") | |
| 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_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(label="Select the Model", choices=DEMUCS_MODELS) | |
| 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_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.") | |
| 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_segments_enabled = gr.Checkbox(value=True, label="Segment-wise processing", info="Enable segment-wise processing.") | |
| 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("General settings"): | |
| with gr.Group(): | |
| 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/") | |
| with gr.Row(): | |
| output_dir = gr.Textbox(value="output", label="File output directory", info="The directory where output files will be saved.", placeholder="output") | |
| output_format = gr.Dropdown(value="wav", choices=["wav", "flac", "mp3"], label="Output Format", info="The format of the output audio file.") | |
| with gr.Row(): | |
| norm_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.9, label="Normalization threshold", info="The threshold for audio normalization.") | |
| amp_threshold = gr.Slider(minimum=0.1, maximum=1, step=0.1, value=0.6, label="Amplification threshold", info="The threshold for audio amplification.") | |
| with gr.Row(): | |
| 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.") | |
| with gr.Tab("Credits"): | |
| gr.Markdown(""" | |
| Politrees - gradio webui\n | |
| theNeodev - mod the ui\n | |
| nomadkaraoke - original project | |
| """) | |
| demucs_model.change(update_stems, inputs=[demucs_model], outputs=stem6) | |
| 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, | |
| output_format, | |
| norm_threshold, | |
| amp_threshold, | |
| batch_size, | |
| ], | |
| outputs=[roformer_stem1, roformer_stem2], | |
| ) | |
| 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, | |
| output_format, | |
| norm_threshold, | |
| amp_threshold, | |
| batch_size, | |
| ], | |
| outputs=[mdx23c_stem1, mdx23c_stem2], | |
| ) | |
| 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, | |
| output_format, | |
| norm_threshold, | |
| amp_threshold, | |
| batch_size, | |
| ], | |
| outputs=[mdx_stem1, mdx_stem2], | |
| ) | |
| 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, | |
| output_format, | |
| norm_threshold, | |
| amp_threshold, | |
| batch_size, | |
| ], | |
| outputs=[vr_stem1, vr_stem2], | |
| ) | |
| 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, | |
| output_format, | |
| norm_threshold, | |
| amp_threshold, | |
| ], | |
| outputs=[demucs_stem1, demucs_stem2, demucs_stem3, demucs_stem4, demucs_stem5, demucs_stem6], | |
| ) | |
| def main(): | |
| app.launch(share=True, debug=True) | |
| if __name__ == "__main__": | |
| main() | |