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| import os | |
| import torch | |
| import logging | |
| import yt_dlp | |
| import spaces | |
| 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-Viperx-1297': 'model_bs_roformer_ep_317_sdr_12.9755.ckpt', | |
| 'BS-Roformer-Viperx-1296': 'model_bs_roformer_ep_368_sdr_12.9628.ckpt', | |
| 'BS-Roformer-Viperx-1053': 'model_bs_roformer_ep_937_sdr_10.5309.ckpt', | |
| 'Mel-Roformer-Viperx-1143': 'model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt', | |
| 'BS-Roformer-De-Reverb': 'deverb_bs_roformer_8_384dim_10depth.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', | |
| '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_D1581.ckpt', | |
| 'MDX23C-8KFFT-InstVoc_HQ.ckpt', | |
| 'MDX23C-8KFFT-InstVoc_HQ_2.ckpt', | |
| ] | |
| #=========================# | |
| # MDXN-NET Models # | |
| #=========================# | |
| mdxnet_models = [ | |
| 'UVR-MDX-NET-Inst_full_292.onnx', | |
| 'UVR-MDX-NET_Inst_187_beta.onnx', | |
| 'UVR-MDX-NET_Inst_82_beta.onnx', | |
| 'UVR-MDX-NET_Inst_90_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-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_MDXNET_Main.onnx', | |
| 'UVR-MDX-NET-Inst_Main.onnx', | |
| 'UVR_MDXNET_1_9703.onnx', | |
| 'UVR_MDXNET_2_9682.onnx', | |
| 'UVR_MDXNET_3_9662.onnx', | |
| 'UVR-MDX-NET-Inst_1.onnx', | |
| 'UVR-MDX-NET-Inst_2.onnx', | |
| 'UVR-MDX-NET-Inst_3.onnx', | |
| 'UVR_MDXNET_KARA.onnx', | |
| 'UVR_MDXNET_KARA_2.onnx', | |
| 'UVR_MDXNET_9482.onnx', | |
| 'UVR-MDX-NET-Voc_FT.onnx', | |
| 'Kim_Vocal_1.onnx', | |
| 'Kim_Vocal_2.onnx', | |
| 'Kim_Inst.onnx', | |
| 'Reverb_HQ_By_FoxJoy.onnx', | |
| 'UVR-MDX-NET_Crowd_HQ_1.onnx', | |
| 'kuielab_a_vocals.onnx', | |
| 'kuielab_a_other.onnx', | |
| 'kuielab_a_bass.onnx', | |
| 'kuielab_a_drums.onnx', | |
| 'kuielab_b_vocals.onnx', | |
| 'kuielab_b_other.onnx', | |
| 'kuielab_b_bass.onnx', | |
| 'kuielab_b_drums.onnx', | |
| ] | |
| #========================# | |
| # VR-ARCH Models # | |
| #========================# | |
| vrarch_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', | |
| 'UVR-De-Echo-Aggressive.pth', | |
| 'UVR-De-Echo-Normal.pth', | |
| 'UVR-DeEcho-DeReverb.pth', | |
| 'UVR-DeNoise-Lite.pth', | |
| 'UVR-DeNoise.pth', | |
| 'UVR-BVE-4B_SN-44100-1.pth', | |
| 'MGM_HIGHEND_v4.pth', | |
| 'MGM_LOWEND_A_v4.pth', | |
| 'MGM_LOWEND_B_v4.pth', | |
| 'MGM_MAIN_v4.pth', | |
| ] | |
| #=======================# | |
| # DEMUCS Models # | |
| #=======================# | |
| demucs_models = [ | |
| 'htdemucs_ft.yaml', | |
| 'htdemucs_6s.yaml', | |
| 'htdemucs.yaml', | |
| 'hdemucs_mmi.yaml', | |
| ] | |
| output_format = [ | |
| 'wav', | |
| 'flac', | |
| 'mp3', | |
| 'ogg', | |
| 'opus', | |
| 'm4a', | |
| 'aiff', | |
| 'ac3' | |
| ] | |
| found_files = [] | |
| logs = [] | |
| out_dir = "./outputs" | |
| models_dir = "./models" | |
| extensions = (".wav", ".flac", ".mp3", ".ogg", ".opus", ".m4a", ".aiff", ".ac3") | |
| def download_audio(url, output_dir="ytdl"): | |
| os.makedirs(output_dir, exist_ok=True) | |
| ydl_opts = { | |
| 'format': 'bestaudio/best', | |
| 'postprocessors': [{ | |
| 'key': 'FFmpegExtractAudio', | |
| 'preferredcodec': 'wav', | |
| 'preferredquality': '32', | |
| }], | |
| 'outtmpl': os.path.join(output_dir, '%(title)s.%(ext)s'), | |
| 'postprocessor_args': [ | |
| '-acodec', 'pcm_f32le' | |
| ], | |
| } | |
| try: | |
| with yt_dlp.YoutubeDL(ydl_opts) as ydl: | |
| info = ydl.extract_info(url, download=False) | |
| video_title = info['title'] | |
| ydl.download([url]) | |
| file_path = os.path.join(output_dir, f"{video_title}.wav") | |
| if os.path.exists(file_path): | |
| return os.path.abspath(file_path) | |
| else: | |
| raise Exception("Something went wrong") | |
| except Exception as e: | |
| raise Exception(f"Error extracting audio with yt-dlp: {str(e)}") | |
| def roformer_separator(audio, model_key, out_format, segment_size, override_seg_size, overlap, batch_size, norm_thresh, amp_thresh, progress=gr.Progress(track_tqdm=True)): | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| roformer_model = roformer_models[model_key] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=out_dir, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdxc_params={ | |
| "segment_size": segment_size, | |
| "override_model_segment_size": override_seg_size, | |
| "batch_size": batch_size, | |
| "overlap": overlap, | |
| } | |
| ) | |
| progress(0.2, desc="Loading model...") | |
| separator.load_model(model_filename=roformer_model) | |
| progress(0.7, desc="Separating audio...") | |
| separation = separator.separate(audio, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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 mdxc_separator(audio, model, out_format, segment_size, override_seg_size, overlap, batch_size, norm_thresh, amp_thresh, progress=gr.Progress(track_tqdm=True)): | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=out_dir, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdxc_params={ | |
| "segment_size": segment_size, | |
| "override_model_segment_size": override_seg_size, | |
| "batch_size": batch_size, | |
| "overlap": overlap, | |
| } | |
| ) | |
| progress(0.2, desc="Loading model...") | |
| separator.load_model(model_filename=model) | |
| progress(0.7, desc="Separating audio...") | |
| separation = separator.separate(audio, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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 mdxnet_separator(audio, model, out_format, hop_length, segment_size, denoise, overlap, batch_size, norm_thresh, amp_thresh, progress=gr.Progress(track_tqdm=True)): | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=out_dir, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdx_params={ | |
| "hop_length": hop_length, | |
| "segment_size": segment_size, | |
| "overlap": overlap, | |
| "batch_size": batch_size, | |
| "enable_denoise": denoise, | |
| } | |
| ) | |
| progress(0.2, desc="Loading model...") | |
| separator.load_model(model_filename=model) | |
| progress(0.7, desc="Separating audio...") | |
| separation = separator.separate(audio, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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 vrarch_separator(audio, model, out_format, window_size, aggression, tta, post_process, post_process_threshold, high_end_process, batch_size, norm_thresh, amp_thresh, progress=gr.Progress(track_tqdm=True)): | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=out_dir, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| 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="Loading model...") | |
| separator.load_model(model_filename=model) | |
| progress(0.7, desc="Separating audio...") | |
| separation = separator.separate(audio, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| 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, out_format, shifts, segment_size, segments_enabled, overlap, batch_size, norm_thresh, amp_thresh, progress=gr.Progress(track_tqdm=True)): | |
| base_name = os.path.splitext(os.path.basename(audio))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=out_dir, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| demucs_params={ | |
| "batch_size": batch_size, | |
| "segment_size": segment_size, | |
| "shifts": shifts, | |
| "overlap": overlap, | |
| "segments_enabled": segments_enabled, | |
| } | |
| ) | |
| progress(0.2, desc="Loading model...") | |
| separator.load_model(model_filename=model) | |
| progress(0.7, desc="Separating audio...") | |
| separation = separator.separate(audio) | |
| 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) | |
| def roformer_batch(path_input, path_output, model_key, out_format, segment_size, override_seg_size, overlap, batch_size, norm_thresh, amp_thresh): | |
| found_files.clear() | |
| logs.clear() | |
| roformer_model = roformer_models[model_key] | |
| for audio_files in os.listdir(path_input): | |
| if audio_files.endswith(extensions): | |
| found_files.append(audio_files) | |
| total_files = len(found_files) | |
| if total_files == 0: | |
| logs.append("No valid audio files.") | |
| yield "\n".join(logs) | |
| else: | |
| logs.append(f"{total_files} audio files found") | |
| found_files.sort() | |
| for audio_files in found_files: | |
| file_path = os.path.join(path_input, audio_files) | |
| base_name = os.path.splitext(os.path.basename(file_path))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=path_output, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdxc_params={ | |
| "segment_size": segment_size, | |
| "override_model_segment_size": override_seg_size, | |
| "batch_size": batch_size, | |
| "overlap": overlap, | |
| } | |
| ) | |
| logs.append("Loading model...") | |
| yield "\n".join(logs) | |
| separator.load_model(model_filename=roformer_model) | |
| logs.append(f"Separating file: {audio_files}") | |
| yield "\n".join(logs) | |
| separator.separate(file_path, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| logs.append(f"File: {audio_files} separated!") | |
| yield "\n".join(logs) | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer batch separation failed: {e}") from e | |
| def mdx23c_batch(path_input, path_output, model, out_format, segment_size, override_seg_size, overlap, batch_size, norm_thresh, amp_thresh): | |
| found_files.clear() | |
| logs.clear() | |
| for audio_files in os.listdir(path_input): | |
| if audio_files.endswith(extensions): | |
| found_files.append(audio_files) | |
| total_files = len(found_files) | |
| if total_files == 0: | |
| logs.append("No valid audio files.") | |
| yield "\n".join(logs) | |
| else: | |
| logs.append(f"{total_files} audio files found") | |
| found_files.sort() | |
| for audio_files in found_files: | |
| file_path = os.path.join(path_input, audio_files) | |
| base_name = os.path.splitext(os.path.basename(file_path))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=path_output, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdxc_params={ | |
| "segment_size": segment_size, | |
| "override_model_segment_size": override_seg_size, | |
| "batch_size": batch_size, | |
| "overlap": overlap, | |
| } | |
| ) | |
| logs.append("Loading model...") | |
| yield "\n".join(logs) | |
| separator.load_model(model_filename=model) | |
| logs.append(f"Separating file: {audio_files}") | |
| yield "\n".join(logs) | |
| separator.separate(file_path, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| logs.append(f"File: {audio_files} separated!") | |
| yield "\n".join(logs) | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer batch separation failed: {e}") from e | |
| def mdxnet_batch(path_input, path_output, model, out_format, hop_length, segment_size, denoise, overlap, batch_size, norm_thresh, amp_thresh): | |
| found_files.clear() | |
| logs.clear() | |
| for audio_files in os.listdir(path_input): | |
| if audio_files.endswith(extensions): | |
| found_files.append(audio_files) | |
| total_files = len(found_files) | |
| if total_files == 0: | |
| logs.append("No valid audio files.") | |
| yield "\n".join(logs) | |
| else: | |
| logs.append(f"{total_files} audio files found") | |
| found_files.sort() | |
| for audio_files in found_files: | |
| file_path = os.path.join(path_input, audio_files) | |
| base_name = os.path.splitext(os.path.basename(file_path))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=path_output, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| mdx_params={ | |
| "hop_length": hop_length, | |
| "segment_size": segment_size, | |
| "overlap": overlap, | |
| "batch_size": batch_size, | |
| "enable_denoise": denoise, | |
| } | |
| ) | |
| logs.append("Loading model...") | |
| yield "\n".join(logs) | |
| separator.load_model(model_filename=model) | |
| logs.append(f"Separating file: {audio_files}") | |
| yield "\n".join(logs) | |
| separator.separate(file_path, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| logs.append(f"File: {audio_files} separated!") | |
| yield "\n".join(logs) | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer batch separation failed: {e}") from e | |
| def vrarch_batch(path_input, path_output, model, out_format, window_size, aggression, tta, post_process, post_process_threshold, high_end_process, batch_size, norm_thresh, amp_thresh): | |
| found_files.clear() | |
| logs.clear() | |
| for audio_files in os.listdir(path_input): | |
| if audio_files.endswith(extensions): | |
| found_files.append(audio_files) | |
| total_files = len(found_files) | |
| if total_files == 0: | |
| logs.append("No valid audio files.") | |
| yield "\n".join(logs) | |
| else: | |
| logs.append(f"{total_files} audio files found") | |
| found_files.sort() | |
| for audio_files in found_files: | |
| file_path = os.path.join(path_input, audio_files) | |
| base_name = os.path.splitext(os.path.basename(file_path))[0] | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=path_output, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| 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, | |
| } | |
| ) | |
| logs.append("Loading model...") | |
| yield "\n".join(logs) | |
| separator.load_model(model_filename=model) | |
| logs.append(f"Separating file: {audio_files}") | |
| yield "\n".join(logs) | |
| separator.separate(file_path, f"{base_name}_(Stem1)", f"{base_name}_(Stem2)") | |
| logs.append(f"File: {audio_files} separated!") | |
| yield "\n".join(logs) | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer batch separation failed: {e}") from e | |
| def demucs_batch(path_input, path_output, model, out_format, shifts, segment_size, segments_enabled, overlap, batch_size, norm_thresh, amp_thresh): | |
| found_files.clear() | |
| logs.clear() | |
| for audio_files in os.listdir(path_input): | |
| if audio_files.endswith(extensions): | |
| found_files.append(audio_files) | |
| total_files = len(found_files) | |
| if total_files == 0: | |
| logs.append("No valid audio files.") | |
| yield "\n".join(logs) | |
| else: | |
| logs.append(f"{total_files} audio files found") | |
| found_files.sort() | |
| for audio_files in found_files: | |
| file_path = os.path.join(path_input, audio_files) | |
| try: | |
| separator = Separator( | |
| log_level=logging.WARNING, | |
| model_file_dir=models_dir, | |
| output_dir=path_output, | |
| output_format=out_format, | |
| use_autocast=use_autocast, | |
| normalization_threshold=norm_thresh, | |
| amplification_threshold=amp_thresh, | |
| demucs_params={ | |
| "batch_size": batch_size, | |
| "segment_size": segment_size, | |
| "shifts": shifts, | |
| "overlap": overlap, | |
| "segments_enabled": segments_enabled, | |
| } | |
| ) | |
| logs.append("Loading model...") | |
| yield "\n".join(logs) | |
| separator.load_model(model_filename=model) | |
| logs.append(f"Separating file: {audio_files}") | |
| yield "\n".join(logs) | |
| separator.separate(file_path) | |
| logs.append(f"File: {audio_files} separated!") | |
| yield "\n".join(logs) | |
| except Exception as e: | |
| raise RuntimeError(f"Roformer batch separation failed: {e}") from e | |