feat: update infer

app.py

@@ -27,14 +27,23 @@ from vc_infer_pipeline import VC
 from config import Config
 config = Config()
 logging.getLogger("numba").setLevel(logging.WARNING)
-limitation = os.getenv("SYSTEM") == "spaces"
+spaces = os.getenv("SYSTEM") == "spaces"
+force_support = None
+if config.unsupported is False:
+    if config.device == "mps" or config.device == "cpu":
+        force_support = False
+else:
+    force_support = True
 
 audio_mode = []
 f0method_mode = []
 f0method_info = ""
 
-if limitation is True:
-    audio_mode = ["Upload audio", "TTS Audio"]
+if force_support is False or spaces is True:
+    if spaces is True:
+        audio_mode = ["Upload audio", "TTS Audio"]
+    else:
+        audio_mode = ["Input path", "Upload audio", "TTS Audio"]
     f0method_mode = ["pm", "harvest"]
     f0method_info = "PM is fast, Harvest is good but extremely slow, Rvmpe is alternative to harvest (might be better). (Default: PM)"
 else:
@@ -61,7 +70,10 @@ def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index):
         protect,
     ):
         try:
+            logs = []
             print(f"Converting using {model_name}...")
+            logs.append(f"Converting using {model_name}...")
+            yield "\n".join(logs), None
             if vc_audio_mode == "Input path" or "Youtube" and vc_input != "":
                 audio, sr = librosa.load(vc_input, sr=16000, mono=True)
             elif vc_audio_mode == "Upload audio":
@@ -69,7 +81,7 @@ def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index):
                     return "You need to upload an audio", None
                 sampling_rate, audio = vc_upload
                 duration = audio.shape[0] / sampling_rate
-                if duration > 20 and limitation:
+                if duration > 20 and spaces:
                     return "Please upload an audio file that is less than 20 seconds. If you need to generate a longer audio file, please use Colab.", None
                 audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32)
                 if len(audio.shape) > 1:
@@ -77,7 +89,7 @@ def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index):
                 if sampling_rate != 16000:
                     audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
             elif vc_audio_mode == "TTS Audio":
-                if len(tts_text) > 100 and limitation:
+                if len(tts_text) > 100 and spaces:
                     return "Text is too long", None
                 if tts_text is None or tts_voice is None:
                     return "You need to enter text and select a voice", None
@@ -109,110 +121,120 @@ def create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, file_index):
             )
             info = f"[{datetime.now().strftime('%Y-%m-%d %H:%M')}]: npy: {times[0]}, f0: {times[1]}s, infer: {times[2]}s"
             print(f"{model_name} | {info}")
-            return info, (tgt_sr, audio_opt)
+            logs.append(f"Successfully Convert {model_name}\n{info}")
+            yield "\n".join(logs), (tgt_sr, audio_opt)
         except:
             info = traceback.format_exc()
             print(info)
-            return info, None
+            yield info, None
     return vc_fn
 
 def load_model():
     categories = []
-    with open("weights/folder_info.json", "r", encoding="utf-8") as f:
-        folder_info = json.load(f)
-    for category_name, category_info in folder_info.items():
-        if not category_info['enable']:
-            continue
-        category_title = category_info['title']
-        category_folder = category_info['folder_path']
-        description = category_info['description']
-        models = []
-        with open(f"weights/{category_folder}/model_info.json", "r", encoding="utf-8") as f:
-            models_info = json.load(f)
-        for character_name, info in models_info.items():
-            if not info['enable']:
+    if os.path.isfile("weights/folder_info.json"):
+        with open("weights/folder_info.json", "r", encoding="utf-8") as f:
+            folder_info = json.load(f)
+        for category_name, category_info in folder_info.items():
+            if not category_info['enable']:
                 continue
-            model_title = info['title']
-            model_name = info['model_path']
-            model_author = info.get("author", None)
-            model_cover = f"weights/{category_folder}/{character_name}/{info['cover']}"
-            model_index = f"weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"
-            cpt = torch.load(f"weights/{category_folder}/{character_name}/{model_name}", map_location="cpu")
-            tgt_sr = cpt["config"][-1]
-            cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
-            if_f0 = cpt.get("f0", 1)
-            version = cpt.get("version", "v1")
-            if version == "v1":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
-                else:
-                    net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
-                model_version = "V1"
-            elif version == "v2":
-                if if_f0 == 1:
-                    net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+            category_title = category_info['title']
+            category_folder = category_info['folder_path']
+            description = category_info['description']
+            models = []
+            with open(f"weights/{category_folder}/model_info.json", "r", encoding="utf-8") as f:
+                models_info = json.load(f)
+            for character_name, info in models_info.items():
+                if not info['enable']:
+                    continue
+                model_title = info['title']
+                model_name = info['model_path']
+                model_author = info.get("author", None)
+                model_cover = f"weights/{category_folder}/{character_name}/{info['cover']}"
+                model_index = f"weights/{category_folder}/{character_name}/{info['feature_retrieval_library']}"
+                cpt = torch.load(f"weights/{category_folder}/{character_name}/{model_name}", map_location="cpu")
+                tgt_sr = cpt["config"][-1]
+                cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0]  # n_spk
+                if_f0 = cpt.get("f0", 1)
+                version = cpt.get("version", "v1")
+                if version == "v1":
+                    if if_f0 == 1:
+                        net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=config.is_half)
+                    else:
+                        net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"])
+                    model_version = "V1"
+                elif version == "v2":
+                    if if_f0 == 1:
+                        net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=config.is_half)
+                    else:
+                        net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
+                    model_version = "V2"
+                del net_g.enc_q
+                print(net_g.load_state_dict(cpt["weight"], strict=False))
+                net_g.eval().to(config.device)
+                if config.is_half:
+                    net_g = net_g.half()
                 else:
-                    net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
-                model_version = "V2"
-            del net_g.enc_q
-            print(net_g.load_state_dict(cpt["weight"], strict=False))
-            net_g.eval().to(config.device)
-            if config.is_half:
-                net_g = net_g.half()
-            else:
-                net_g = net_g.float()
-            vc = VC(tgt_sr, config)
-            print(f"Model loaded: {character_name} / {info['feature_retrieval_library']} | ({model_version})")
-            models.append((character_name, model_title, model_author, model_cover, model_version, create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, model_index)))
-        categories.append([category_title, category_folder, description, models])
+                    net_g = net_g.float()
+                vc = VC(tgt_sr, config)
+                print(f"Model loaded: {character_name} / {info['feature_retrieval_library']} | ({model_version})")
+                models.append((character_name, model_title, model_author, model_cover, model_version, create_vc_fn(model_name, tgt_sr, net_g, vc, if_f0, version, model_index)))
+            categories.append([category_title, category_folder, description, models])
+    else:
+        categories = []
     return categories
 
-def cut_vocal_and_inst(url, audio_provider, split_model):
-    if url != "":
-        if not os.path.exists("dl_audio"):
-            os.mkdir("dl_audio")
-        if audio_provider == "Youtube":
-            ydl_opts = {
-                'noplaylist': True,
-                'format': 'bestaudio/best',
-                'postprocessors': [{
-                    'key': 'FFmpegExtractAudio',
-                    'preferredcodec': 'wav',
-                }],
-                "outtmpl": 'dl_audio/youtube_audio',
-            }
-            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-                ydl.download([url])
-            audio_path = "dl_audio/youtube_audio.wav"
-        if split_model == "htdemucs":
-            command = f"demucs --two-stems=vocals {audio_path} -o output"
-            result = subprocess.run(command.split(), stdout=subprocess.PIPE)
-            print(result.stdout.decode())
-            return "output/htdemucs/youtube_audio/vocals.wav", "output/htdemucs/youtube_audio/no_vocals.wav", audio_path, "output/htdemucs/youtube_audio/vocals.wav"
-        else:
-            command = f"demucs --two-stems=vocals -n mdx_extra_q {audio_path} -o output"
-            result = subprocess.run(command.split(), stdout=subprocess.PIPE)
-            print(result.stdout.decode())
-            return "output/mdx_extra_q/youtube_audio/vocals.wav", "output/mdx_extra_q/youtube_audio/no_vocals.wav", audio_path, "output/mdx_extra_q/youtube_audio/vocals.wav"
-    else:
+def download_audio(url, audio_provider):
+    logs = []
+    if url == "":
         raise gr.Error("URL Required!")
-        return None, None, None, None
+        return "URL Required"
+    if not os.path.exists("dl_audio"):
+        os.mkdir("dl_audio")
+    if audio_provider == "Youtube":
+        logs.append("Downloading the audio...")
+        yield None, "\n".join(logs)
+        ydl_opts = {
+            'noplaylist': True,
+            'format': 'bestaudio/best',
+            'postprocessors': [{
+                'key': 'FFmpegExtractAudio',
+                'preferredcodec': 'wav',
+            }],
+            "outtmpl": 'dl_audio/audio',
+        }
+        audio_path = "dl_audio/audio.wav"
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            ydl.download([url])
+        logs.append("Download Complete.")
+        yield audio_path, "\n".join(logs)
+
+def cut_vocal_and_inst(split_model):
+    logs = []
+    logs.append("Starting the audio splitting process...")
+    yield "\n".join(logs), None, None, None, None
+    command = f"demucs --two-stems=vocals -n {split_model} dl_audio/audio.wav -o output"
+    result = subprocess.Popen(command.split(), stdout=subprocess.PIPE, text=True)
+    for line in result.stdout:
+        logs.append(line)
+        yield "\n".join(logs), None, None, None, None
+    print(result.stdout)
+    vocal = f"output/{split_model}/audio/vocals.wav"
+    inst = f"output/{split_model}/audio/no_vocals.wav"
+    logs.append("Audio splitting complete.")
+    yield "\n".join(logs), vocal, inst, vocal
 
-def combine_vocal_and_inst(audio_data, audio_volume, split_model):
+def combine_vocal_and_inst(audio_data, vocal_volume, inst_volume, split_model):
     if not os.path.exists("output/result"):
         os.mkdir("output/result")
     vocal_path = "output/result/output.wav"
     output_path = "output/result/combine.mp3"
-    if split_model == "htdemucs":
-        inst_path = "output/htdemucs/youtube_audio/no_vocals.wav"
-    else:
-        inst_path = "output/mdx_extra_q/youtube_audio/no_vocals.wav"
+    inst_path = f"output/{split_model}/audio/no_vocals.wav"
     with wave.open(vocal_path, "w") as wave_file:
         wave_file.setnchannels(1) 
         wave_file.setsampwidth(2)
         wave_file.setframerate(audio_data[0])
         wave_file.writeframes(audio_data[1].tobytes())
-    command =  f'ffmpeg -y -i {inst_path} -i {vocal_path} -filter_complex [1:a]volume={audio_volume}dB[v];[0:a][v]amix=inputs=2:duration=longest -b:a 320k -c:a libmp3lame {output_path}'
+    command =  f'ffmpeg -y -i {inst_path} -i {vocal_path} -filter_complex [0:a]volume={inst_volume}[i];[1:a]volume={vocal_volume}[v];[i][v]amix=inputs=2:duration=longest[a] -map [a] -b:a 320k -c:a libmp3lame {output_path}'
     result = subprocess.run(command.split(), stdout=subprocess.PIPE)
     print(result.stdout.decode())
     return output_path
@@ -241,12 +263,17 @@ def change_audio_mode(vc_audio_mode):
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
+            gr.Textbox.update(visible=False),
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
+            gr.Textbox.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
@@ -262,12 +289,17 @@ def change_audio_mode(vc_audio_mode):
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
+            gr.Textbox.update(visible=False),
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
+            gr.Textbox.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
@@ -283,12 +315,17 @@ def change_audio_mode(vc_audio_mode):
             # Youtube
             gr.Dropdown.update(visible=True),
             gr.Textbox.update(visible=True),
+            gr.Textbox.update(visible=True),
+            gr.Button.update(visible=True),
+            # Splitter
             gr.Dropdown.update(visible=True),
+            gr.Textbox.update(visible=True),
             gr.Button.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Slider.update(visible=True),
+            gr.Slider.update(visible=True),
             gr.Audio.update(visible=True),
             gr.Button.update(visible=True),
             # TTS
@@ -304,38 +341,22 @@ def change_audio_mode(vc_audio_mode):
             # Youtube
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
-            gr.Dropdown.update(visible=False),
-            gr.Button.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Slider.update(visible=False),
-            gr.Audio.update(visible=False),
-            gr.Button.update(visible=False),
-            # TTS
-            gr.Textbox.update(visible=True),
-            gr.Dropdown.update(visible=True)
-        )
-    else:
-        return (
-            # Input & Upload
             gr.Textbox.update(visible=False),
-            gr.Checkbox.update(visible=True),
-            gr.Audio.update(visible=True),
-            # Youtube
+            gr.Button.update(visible=False),
+            # Splitter
             gr.Dropdown.update(visible=False),
             gr.Textbox.update(visible=False),
-            gr.Dropdown.update(visible=False),
             gr.Button.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Slider.update(visible=False),
+            gr.Slider.update(visible=False),
             gr.Audio.update(visible=False),
             gr.Button.update(visible=False),
             # TTS
-            gr.Textbox.update(visible=False),
-            gr.Dropdown.update(visible=False)
+            gr.Textbox.update(visible=True),
+            gr.Dropdown.update(visible=True)
         )
 
 def use_microphone(microphone):
@@ -358,6 +379,12 @@ if __name__ == '__main__':
             "</div>\n\n"+
             "[![Repository](https://img.shields.io/badge/Github-Multi%20Model%20RVC%20Inference-blue?style=for-the-badge&logo=github)](https://github.com/ArkanDash/Multi-Model-RVC-Inference)"
         )
+        if categories == []:
+            gr.Markdown(
+                "<div align='center'>\n\n"+
+                "## No model found, please add the model into weights folder\n\n"+
+                "</div>"
+            )
         for (folder_title, folder, description, models) in categories:
             with gr.TabItem(folder_title):
                 if description:
@@ -365,7 +392,7 @@ if __name__ == '__main__':
                 with gr.Tabs():
                     if not models:
                         gr.Markdown("# <center> No Model Loaded.")
-                        gr.Markdown("## <center> Please add model or fix your model path.")
+                        gr.Markdown("## <center> Please add the model or fix your model path.")
                         continue
                     for (name, title, author, cover, model_version, vc_fn) in models:
                         with gr.TabItem(name):
@@ -379,92 +406,212 @@ if __name__ == '__main__':
                                     '</div>'
                                 )
                             with gr.Row():
-                                with gr.Column():
-                                    vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
-                                    # Input
-                                    vc_input = gr.Textbox(label="Input audio path", visible=False)
-                                    # Upload
-                                    vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
-                                    vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
-                                    # Youtube
-                                    vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
-                                    vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
-                                    vc_split_model = gr.Dropdown(label="Splitter Model", choices=["htdemucs", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
-                                    vc_split = gr.Button("Split Audio", variant="primary", visible=False)
-                                    vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
-                                    vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
-                                    vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
-                                    # TTS
-                                    tts_text = gr.Textbox(visible=False, label="TTS text", info="Text to speech input")
-                                    tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
-                                with gr.Column():
-                                    vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
-                                    f0method0 = gr.Radio(
-                                        label="Pitch extraction algorithm",
-                                        info=f0method_info,
-                                        choices=f0method_mode,
-                                        value="pm",
-                                        interactive=True
-                                    )
-                                    index_rate1 = gr.Slider(
-                                        minimum=0,
-                                        maximum=1,
-                                        label="Retrieval feature ratio",
-                                        info="(Default: 0.7)",
-                                        value=0.7,
-                                        interactive=True,
-                                    )
-                                    filter_radius0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=7,
-                                        label="Apply Median Filtering",
-                                        info="The value represents the filter radius and can reduce breathiness.",
-                                        value=3,
-                                        step=1,
-                                        interactive=True,
-                                    )
-                                    resample_sr0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=48000,
-                                        label="Resample the output audio",
-                                        info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
-                                        value=0,
-                                        step=1,
-                                        interactive=True,
-                                    )
-                                    rms_mix_rate0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=1,
-                                        label="Volume Envelope",
-                                        info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
-                                        value=1,
-                                        interactive=True,
-                                    )
-                                    protect0 = gr.Slider(
-                                        minimum=0,
-                                        maximum=0.5,
-                                        label="Voice Protection",
-                                        info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
-                                        value=0.5,
-                                        step=0.01,
-                                        interactive=True,
-                                    )
-                                with gr.Column():
-                                    vc_log = gr.Textbox(label="Output Information", interactive=False)
-                                    vc_output = gr.Audio(label="Output Audio", interactive=False)
-                                    vc_convert = gr.Button("Convert", variant="primary")
-                                    vc_volume = gr.Slider(
-                                        minimum=0,
-                                        maximum=10,
-                                        label="Vocal volume",
-                                        value=4,
-                                        interactive=True,
-                                        step=1,
-                                        info="Adjust vocal volume (Default: 4}",
-                                        visible=False
-                                    )
-                                    vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
-                                    vc_combine =  gr.Button("Combine",variant="primary", visible=False)
+                                if spaces is False:
+                                    with gr.TabItem("Input"):
+                                        with gr.Row():
+                                            with gr.Column():
+                                                vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+                                                # Input
+                                                vc_input = gr.Textbox(label="Input audio path", visible=False)
+                                                # Upload
+                                                vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+                                                vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+                                                # Youtube
+                                                vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+                                                vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+                                                vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                                vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+                                                vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+                                                # TTS
+                                                tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+                                                tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+                                            with gr.Column():
+                                                vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+                                                vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                                vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+                                                vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+                                                vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+                                    with gr.TabItem("Convert"):
+                                        with gr.Row():
+                                            with gr.Column():
+                                                vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+                                                f0method0 = gr.Radio(
+                                                    label="Pitch extraction algorithm",
+                                                    info=f0method_info,
+                                                    choices=f0method_mode,
+                                                    value="pm",
+                                                    interactive=True
+                                                )
+                                                index_rate1 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=1,
+                                                    label="Retrieval feature ratio",
+                                                    info="(Default: 0.7)",
+                                                    value=0.7,
+                                                    interactive=True,
+                                                )
+                                                filter_radius0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=7,
+                                                    label="Apply Median Filtering",
+                                                    info="The value represents the filter radius and can reduce breathiness.",
+                                                    value=3,
+                                                    step=1,
+                                                    interactive=True,
+                                                )
+                                                resample_sr0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=48000,
+                                                    label="Resample the output audio",
+                                                    info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+                                                    value=0,
+                                                    step=1,
+                                                    interactive=True,
+                                                )
+                                                rms_mix_rate0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=1,
+                                                    label="Volume Envelope",
+                                                    info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+                                                    value=1,
+                                                    interactive=True,
+                                                )
+                                                protect0 = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=0.5,
+                                                    label="Voice Protection",
+                                                    info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+                                                    value=0.5,
+                                                    step=0.01,
+                                                    interactive=True,
+                                                )
+                                            with gr.Column():
+                                                vc_log = gr.Textbox(label="Output Information", interactive=False)
+                                                vc_output = gr.Audio(label="Output Audio", interactive=False)
+                                                vc_convert = gr.Button("Convert", variant="primary")
+                                                vc_vocal_volume = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=10,
+                                                    label="Vocal volume",
+                                                    value=1,
+                                                    interactive=True,
+                                                    step=1,
+                                                    info="Adjust vocal volume (Default: 1}",
+                                                    visible=False
+                                                )
+                                                vc_inst_volume = gr.Slider(
+                                                    minimum=0,
+                                                    maximum=10,
+                                                    label="Instrument volume",
+                                                    value=1,
+                                                    interactive=True,
+                                                    step=1,
+                                                    info="Adjust instrument volume (Default: 1}",
+                                                    visible=False
+                                                )
+                                                vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+                                                vc_combine =  gr.Button("Combine",variant="primary", visible=False)
+                                else:
+                                    with gr.Column():
+                                        vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+                                        # Input
+                                        vc_input = gr.Textbox(label="Input audio path", visible=False)
+                                        # Upload
+                                        vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+                                        vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+                                        # Youtube
+                                        vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+                                        vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+                                        vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                        vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+                                        vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+                                        # Splitter
+                                        vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+                                        vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+                                        vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+                                        vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+                                        vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+                                        # TTS
+                                        tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+                                        tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+                                    with gr.Column():
+                                        vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+                                        f0method0 = gr.Radio(
+                                            label="Pitch extraction algorithm",
+                                            info=f0method_info,
+                                            choices=f0method_mode,
+                                            value="pm",
+                                            interactive=True
+                                        )
+                                        index_rate1 = gr.Slider(
+                                            minimum=0,
+                                            maximum=1,
+                                            label="Retrieval feature ratio",
+                                            info="(Default: 0.7)",
+                                            value=0.7,
+                                            interactive=True,
+                                        )
+                                        filter_radius0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=7,
+                                            label="Apply Median Filtering",
+                                            info="The value represents the filter radius and can reduce breathiness.",
+                                            value=3,
+                                            step=1,
+                                            interactive=True,
+                                        )
+                                        resample_sr0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=48000,
+                                            label="Resample the output audio",
+                                            info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+                                            value=0,
+                                            step=1,
+                                            interactive=True,
+                                        )
+                                        rms_mix_rate0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=1,
+                                            label="Volume Envelope",
+                                            info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+                                            value=1,
+                                            interactive=True,
+                                        )
+                                        protect0 = gr.Slider(
+                                            minimum=0,
+                                            maximum=0.5,
+                                            label="Voice Protection",
+                                            info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+                                            value=0.5,
+                                            step=0.01,
+                                            interactive=True,
+                                        )
+                                    with gr.Column():
+                                        vc_log = gr.Textbox(label="Output Information", interactive=False)
+                                        vc_output = gr.Audio(label="Output Audio", interactive=False)
+                                        vc_convert = gr.Button("Convert", variant="primary")
+                                        vc_vocal_volume = gr.Slider(
+                                            minimum=0,
+                                            maximum=10,
+                                            label="Vocal volume",
+                                            value=1,
+                                            interactive=True,
+                                            step=1,
+                                            info="Adjust vocal volume (Default: 1}",
+                                            visible=False
+                                        )
+                                        vc_inst_volume = gr.Slider(
+                                            minimum=0,
+                                            maximum=10,
+                                            label="Instrument volume",
+                                            value=1,
+                                            interactive=True,
+                                            step=1,
+                                            info="Adjust instrument volume (Default: 1}",
+                                            visible=False
+                                        )
+                                        vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+                                        vc_combine =  gr.Button("Combine",variant="primary", visible=False)
                         vc_convert.click(
                             fn=vc_fn, 
                             inputs=[
@@ -483,14 +630,19 @@ if __name__ == '__main__':
                             ], 
                             outputs=[vc_log ,vc_output]
                         )
+                        vc_download_button.click(
+                            fn=download_audio, 
+                            inputs=[vc_link, vc_download_audio], 
+                            outputs=[vc_audio_preview, vc_log_yt]
+                        )
                         vc_split.click(
                             fn=cut_vocal_and_inst, 
-                            inputs=[vc_link, vc_download_audio, vc_split_model], 
-                            outputs=[vc_vocal_preview, vc_inst_preview, vc_audio_preview, vc_input]
+                            inputs=[vc_split_model], 
+                            outputs=[vc_split_log, vc_vocal_preview, vc_inst_preview, vc_input]
                         )
                         vc_combine.click(
                             fn=combine_vocal_and_inst,
-                            inputs=[vc_output, vc_volume, vc_split_model],
+                            inputs=[vc_output, vc_vocal_volume, vc_inst_volume, vc_split_model],
                             outputs=[vc_combined_output]
                         )
                         vc_microphone_mode.change(
@@ -507,12 +659,16 @@ if __name__ == '__main__':
                                 vc_upload,
                                 vc_download_audio,
                                 vc_link,
+                                vc_log_yt,
+                                vc_download_button,
                                 vc_split_model,
+                                vc_split_log,
                                 vc_split,
+                                vc_audio_preview,
                                 vc_vocal_preview,
                                 vc_inst_preview,
-                                vc_audio_preview,
-                                vc_volume,
+                                vc_vocal_volume,
+                                vc_inst_volume,
                                 vc_combined_output,
                                 vc_combine,
                                 tts_text,

config.py

@@ -11,42 +11,24 @@ class Config:
         self.gpu_name = None
         self.gpu_mem = None
         (
-            self.python_cmd,
-            self.listen_port,
             self.colab,
-            self.noparallel,
-            self.noautoopen,
-            self.api
+            self.api,
+            self.unsupported
         ) = self.arg_parse()
         self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
 
     @staticmethod
     def arg_parse() -> tuple:
-        exe = sys.executable or "python"
         parser = argparse.ArgumentParser()
-        parser.add_argument("--port", type=int, default=7865, help="Listen port")
-        parser.add_argument("--pycmd", type=str, default=exe, help="Python command")
         parser.add_argument("--colab", action="store_true", help="Launch in colab")
-        parser.add_argument(
-            "--noparallel", action="store_true", help="Disable parallel processing"
-        )
-        parser.add_argument(
-            "--noautoopen",
-            action="store_true",
-            help="Do not open in browser automatically",
-        )
         parser.add_argument("--api", action="store_true", help="Launch with api")
+        parser.add_argument("--unsupported", action="store_true", help="Enable unsupported feature")
         cmd_opts = parser.parse_args()
 
-        cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
-
         return (
-            cmd_opts.pycmd,
-            cmd_opts.port,
             cmd_opts.colab,
-            cmd_opts.noparallel,
-            cmd_opts.noautoopen,
-            cmd_opts.api
+            cmd_opts.api,
+            cmd_opts.unsupported
         )
 
     # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
@@ -72,10 +54,10 @@ class Config:
                 or "1070" in self.gpu_name
                 or "1080" in self.gpu_name
             ):
-                print("Found GPU", self.gpu_name, ", force to fp32")
+                print("INFO: Found GPU", self.gpu_name, ", force to fp32")
                 self.is_half = False
             else:
-                print("Found GPU", self.gpu_name)
+                print("INFO: Found GPU", self.gpu_name)
             self.gpu_mem = int(
                 torch.cuda.get_device_properties(i_device).total_memory
                 / 1024
@@ -84,11 +66,11 @@ class Config:
                 + 0.4
             )
         elif self.has_mps():
-            print("No supported Nvidia GPU found, use MPS instead")
+            print("INFO: No supported Nvidia GPU found, use MPS instead")
             self.device = "mps"
             self.is_half = False
         else:
-            print("No supported Nvidia GPU found, use CPU instead")
+            print("INFO: No supported Nvidia GPU found, use CPU instead")
             self.device = "cpu"
             self.is_half = False