Update app.py

app.py

@@ -6,597 +6,7 @@ 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)}")
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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)
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-
-@spaces.GPU(duration=60)
-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
-            
 with gr.Blocks(theme ="hev832/applio", title = "🎵 Audio Separator UI 🎵") as app:
     with gr.Row():
         gr.Markdown("<h1> 🎵 Audio Separator UI 🎵 </h1>")