Upload 5 files

README.md

@@ -1,14 +1,14 @@
----
-title: RVC⚡ZERO
-emoji: ⚡
-colorFrom: gray
-colorTo: indigo
-sdk: gradio
-sdk_version: 4.28.3
-app_file: app.py
-license: mit
-pinned: true
-short_description: Voice conversion framework based on VITS
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: RVC⚡ZERO
+emoji: ⚡
+colorFrom: gray
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.34.2
+app_file: app.py
+license: mit
+pinned: true
+short_description: Voice conversion framework based on VITS
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,741 +1,742 @@
-import os
-import gradio as gr
-import spaces
-from infer_rvc_python import BaseLoader
-import random
-import logging
-import time
-import soundfile as sf
-from infer_rvc_python.main import download_manager
-import zipfile
-import edge_tts
-import asyncio
-import librosa
-import traceback
-import soundfile as sf
-from pedalboard import Pedalboard, Reverb, Compressor, HighpassFilter
-from pedalboard.io import AudioFile
-from pydub import AudioSegment
-import noisereduce as nr
-import numpy as np
-import urllib.request
-import shutil
-import threading
-
-logging.getLogger("infer_rvc_python").setLevel(logging.ERROR)
-
-converter = BaseLoader(only_cpu=False, hubert_path=None, rmvpe_path=None)
-
-title = "<center><strong><font size='7'>RVC⚡ZERO</font></strong></center>"
-description = "This demo is provided for educational and research purposes only. The authors and contributors of this project do not endorse or encourage any misuse or unethical use of this software. Any use of this software for purposes other than those intended is solely at the user's own risk. The authors and contributors shall not be held responsible for any damages or liabilities arising from the use of this demo inappropriately."
-theme = "aliabid94/new-theme"
-
-PITCH_ALGO_OPT = [
-    "pm",
-    "harvest",
-    "crepe",
-    "rmvpe",
-    "rmvpe+",
-]
-
-
-def find_files(directory):
-    file_paths = []
-    for filename in os.listdir(directory):
-        # Check if the file has the desired extension
-        if filename.endswith('.pth') or filename.endswith('.zip') or filename.endswith('.index'):
-            # If yes, add the file path to the list
-            file_paths.append(os.path.join(directory, filename))
-
-    return file_paths
-
-
-def unzip_in_folder(my_zip, my_dir):
-    with zipfile.ZipFile(my_zip) as zip:
-        for zip_info in zip.infolist():
-            if zip_info.is_dir():
-                continue
-            zip_info.filename = os.path.basename(zip_info.filename)
-            zip.extract(zip_info, my_dir)
-
-
-def find_my_model(a_, b_):
-
-    if a_ is None or a_.endswith(".pth"):
-        return a_, b_
-
-    txt_files = []
-    for base_file in [a_, b_]:
-        if base_file is not None and base_file.endswith(".txt"):
-            txt_files.append(base_file)
-
-    directory = os.path.dirname(a_)
-
-    for txt in txt_files:
-        with open(txt, 'r') as file:
-            first_line = file.readline()
-
-        download_manager(
-            url=first_line.strip(),
-            path=directory,
-            extension="",
-        )
-
-    for f in find_files(directory):
-        if f.endswith(".zip"):
-            unzip_in_folder(f, directory)
-
-    model = None
-    index = None
-    end_files = find_files(directory)
-
-    for ff in end_files:
-        if ff.endswith(".pth"):
-            model = os.path.join(directory, ff)
-            gr.Info(f"Model found: {ff}")
-        if ff.endswith(".index"):
-            index = os.path.join(directory, ff)
-            gr.Info(f"Index found: {ff}")
-
-    if not model:
-        gr.Error(f"Model not found in: {end_files}")
-
-    if not index:
-        gr.Warning("Index not found")
-
-    return model, index
-
-
-def get_file_size(url):
-
-    if "huggingface" not in url:
-        raise ValueError("Only downloads from Hugging Face are allowed")
-
-    try:
-        with urllib.request.urlopen(url) as response:
-            info = response.info()
-            content_length = info.get("Content-Length")
-
-        file_size = int(content_length)
-        if file_size > 500000000:
-            raise ValueError("The file is too large. You can only download files up to 500 MB in size.")
-
-    except Exception as e:
-        raise e
-
-
-def clear_files(directory):
-    time.sleep(15)
-    print(f"Clearing files: {directory}.")
-    shutil.rmtree(directory)
-
-
-def get_my_model(url_data):
-
-    if not url_data:
-        return None, None
-
-    if "," in url_data:
-        a_, b_ = url_data.split()
-        a_, b_ = a_.strip().replace("/blob/", "/resolve/"), b_.strip().replace("/blob/", "/resolve/")
-    else:
-        a_, b_ = url_data.strip().replace("/blob/", "/resolve/"), None
-
-    out_dir = "downloads"
-    folder_download = str(random.randint(1000, 9999))
-    directory = os.path.join(out_dir, folder_download)
-    os.makedirs(directory, exist_ok=True)
-
-    try:
-        get_file_size(a_)
-        if b_:
-            get_file_size(b_)
-
-        valid_url = [a_] if not b_ else [a_, b_]
-        for link in valid_url:
-            download_manager(
-                url=link,
-                path=directory,
-                extension="",
-            )
-
-        for f in find_files(directory):
-            if f.endswith(".zip"):
-                unzip_in_folder(f, directory)
-
-        model = None
-        index = None
-        end_files = find_files(directory)
-
-        for ff in end_files:
-            if ff.endswith(".pth"):
-                model = ff
-                gr.Info(f"Model found: {ff}")
-            if ff.endswith(".index"):
-                index = ff
-                gr.Info(f"Index found: {ff}")
-
-        if not model:
-            raise ValueError(f"Model not found in: {end_files}")
-
-        if not index:
-            gr.Warning("Index not found")
-        else:
-            index = os.path.abspath(index)
-
-        return os.path.abspath(model), index
-
-    except Exception as e:
-        raise e
-    finally:
-        # time.sleep(10)
-        # shutil.rmtree(directory)
-        t = threading.Thread(target=clear_files, args=(directory,))
-        t.start()
-
-
-def add_audio_effects(audio_list):
-    print("Audio effects")
-
-    result = []
-    for audio_path in audio_list:
-        try:
-            output_path = f'{os.path.splitext(audio_path)[0]}_effects.wav'
-
-            # Initialize audio effects plugins
-            board = Pedalboard(
-                [
-                    HighpassFilter(),
-                    Compressor(ratio=4, threshold_db=-15),
-                    Reverb(room_size=0.10, dry_level=0.8, wet_level=0.2, damping=0.7)
-                 ]
-            )
-
-            with AudioFile(audio_path) as f:
-                with AudioFile(output_path, 'w', f.samplerate, f.num_channels) as o:
-                    # Read one second of audio at a time, until the file is empty:
-                    while f.tell() < f.frames:
-                        chunk = f.read(int(f.samplerate))
-                        effected = board(chunk, f.samplerate, reset=False)
-                        o.write(effected)
-            result.append(output_path)
-        except Exception as e:
-            traceback.print_exc()
-            print(f"Error noisereduce: {str(e)}")
-            result.append(audio_path)
-
-    return result
-
-
-def apply_noisereduce(audio_list):
-    # https://github.com/sa-if/Audio-Denoiser
-    print("Noice reduce")
-
-    result = []
-    for audio_path in audio_list:
-        out_path = f'{os.path.splitext(audio_path)[0]}_noisereduce.wav'
-
-        try:
-            # Load audio file
-            audio = AudioSegment.from_file(audio_path)
-
-            # Convert audio to numpy array
-            samples = np.array(audio.get_array_of_samples())
-
-            # Reduce noise
-            reduced_noise = nr.reduce_noise(samples, sr=audio.frame_rate, prop_decrease=0.6)
-
-            # Convert reduced noise signal back to audio
-            reduced_audio = AudioSegment(
-                reduced_noise.tobytes(), 
-                frame_rate=audio.frame_rate, 
-                sample_width=audio.sample_width,
-                channels=audio.channels
-            )
-
-            # Save reduced audio to file
-            reduced_audio.export(out_path, format="wav")
-            result.append(out_path)
-
-        except Exception as e:
-            traceback.print_exc()
-            print(f"Error noisereduce: {str(e)}")
-            result.append(audio_path)
-
-    return result
-
-
-@spaces.GPU()
-def convert_now(audio_files, random_tag, converter):
-    return converter(
-        audio_files,
-        random_tag,
-        overwrite=False,
-        parallel_workers=8
-    )
-
-
-def run(
-    audio_files,
-    file_m,
-    pitch_alg,
-    pitch_lvl,
-    file_index,
-    index_inf,
-    r_m_f,
-    e_r,
-    c_b_p,
-    active_noise_reduce,
-    audio_effects,
-):
-    if not audio_files:
-        raise ValueError("The audio pls")
-
-    if isinstance(audio_files, str):
-        audio_files = [audio_files]
-
-    try:
-        duration_base = librosa.get_duration(filename=audio_files[0])
-        print("Duration:", duration_base)
-    except Exception as e:
-        print(e)
-
-    if file_m is not None and file_m.endswith(".txt"):
-        file_m, file_index = find_my_model(file_m, file_index)
-        print(file_m, file_index)
-
-    random_tag = "USER_"+str(random.randint(10000000, 99999999))
-
-    converter.apply_conf(
-        tag=random_tag,
-        file_model=file_m,
-        pitch_algo=pitch_alg,
-        pitch_lvl=pitch_lvl,
-        file_index=file_index,
-        index_influence=index_inf,
-        respiration_median_filtering=r_m_f,
-        envelope_ratio=e_r,
-        consonant_breath_protection=c_b_p,
-        resample_sr=44100 if audio_files[0].endswith('.mp3') else 0, 
-    )
-    time.sleep(0.1)
-
-    result = convert_now(audio_files, random_tag, converter)
-
-    if active_noise_reduce:
-        result = apply_noisereduce(result)
-
-    if audio_effects:
-        result = add_audio_effects(result)
-
-    return result
-
-
-def audio_conf():
-    return gr.File(
-        label="Audio files",
-        file_count="multiple",
-        type="filepath",
-        container=True,
-    )
-
-
-def model_conf():
-    return gr.File(
-        label="Model file",
-        type="filepath",
-        height=130,
-    )
-
-
-def pitch_algo_conf():
-    return gr.Dropdown(
-        PITCH_ALGO_OPT,
-        value=PITCH_ALGO_OPT[4],
-        label="Pitch algorithm",
-        visible=True,
-        interactive=True,
-    )
-
-
-def pitch_lvl_conf():
-    return gr.Slider(
-        label="Pitch level",
-        minimum=-24,
-        maximum=24,
-        step=1,
-        value=0,
-        visible=True,
-        interactive=True,
-    )
-
-
-def index_conf():
-    return gr.File(
-        label="Index file",
-        type="filepath",
-        height=130,
-    )
-
-
-def index_inf_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=1,
-        label="Index influence",
-        value=0.75,
-    )
-
-
-def respiration_filter_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=7,
-        label="Respiration median filtering",
-        value=3,
-        step=1,
-        interactive=True,
-    )
-
-
-def envelope_ratio_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=1,
-        label="Envelope ratio",
-        value=0.25,
-        interactive=True,
-    )
-
-
-def consonant_protec_conf():
-    return gr.Slider(
-        minimum=0,
-        maximum=0.5,
-        label="Consonant breath protection",
-        value=0.5,
-        interactive=True,
-    )
-
-
-def button_conf():
-    return gr.Button(
-        "Inference",
-        variant="primary",
-    )
-
-
-def output_conf():
-    return gr.File(
-        label="Result",
-        file_count="multiple",
-        interactive=False,
-    )
-
-
-def active_tts_conf():
-    return gr.Checkbox(
-        False,
-        label="TTS",
-        # info="",
-        container=False,
-    )
-
-
-def tts_voice_conf():
-    return gr.Dropdown(
-        label="tts voice",
-        choices=voices,
-        visible=False,
-        value="en-US-EmmaMultilingualNeural-Female",
-    )
-
-
-def tts_text_conf():
-    return gr.Textbox(
-        value="",
-        placeholder="Write the text here...",
-        label="Text",
-        visible=False,
-        lines=3,
-    )
-
-
-def tts_button_conf():
-    return gr.Button(
-        "Process TTS",
-        variant="secondary",
-        visible=False,
-    )
-
-
-def tts_play_conf():
-    return gr.Checkbox(
-        False,
-        label="Play",
-        # info="",
-        container=False,
-        visible=False,
-    )
-
-
-def sound_gui():
-    return gr.Audio(
-        value=None,
-        type="filepath",
-        # format="mp3",
-        autoplay=True,
-        visible=False,
-    )
-
-
-def denoise_conf():
-    return gr.Checkbox(
-        False,
-        label="Denoise",
-        # info="",
-        container=False,
-        visible=True,
-    )
-
-
-def effects_conf():
-    return gr.Checkbox(
-        False,
-        label="Reverb",
-        # info="",
-        container=False,
-        visible=True,
-    )
-
-
-def infer_tts_audio(tts_voice, tts_text, play_tts):
-    out_dir = "output"
-    folder_tts = "USER_"+str(random.randint(10000, 99999))
-
-    os.makedirs(out_dir, exist_ok=True)
-    os.makedirs(os.path.join(out_dir, folder_tts), exist_ok=True)
-    out_path = os.path.join(out_dir, folder_tts, "tts.mp3")
-
-    asyncio.run(edge_tts.Communicate(tts_text, "-".join(tts_voice.split('-')[:-1])).save(out_path))
-    if play_tts:
-        return [out_path], out_path
-    return [out_path], None
-
-
-def show_components_tts(value_active):
-    return gr.update(
-        visible=value_active
-    ), gr.update(
-        visible=value_active
-    ), gr.update(
-        visible=value_active
-    ), gr.update(
-        visible=value_active
-    )
-
-
-def down_active_conf():
-    return gr.Checkbox(
-        False,
-        label="URL-to-Model",
-        # info="",
-        container=False,
-    )
-
-
-def down_url_conf():
-    return gr.Textbox(
-        value="",
-        placeholder="Write the url here...",
-        label="Enter URL",
-        visible=False,
-        lines=1,
-    )
-
-
-def down_button_conf():
-    return gr.Button(
-        "Process",
-        variant="secondary",
-        visible=False,
-    )
-
-
-def show_components_down(value_active):
-    return gr.update(
-        visible=value_active
-    ), gr.update(
-        visible=value_active
-    ), gr.update(
-        visible=value_active
-    )
-
-
-def get_gui(theme):
-    with gr.Blocks(theme=theme, delete_cache=(3200, 3200)) as app:
-        gr.Markdown(title)
-        gr.Markdown(description)
-
-        active_tts = active_tts_conf()
-        with gr.Row():
-            with gr.Column(scale=1):
-                tts_text = tts_text_conf()
-            with gr.Column(scale=2):
-                with gr.Row():
-                    with gr.Column():
-                        with gr.Row():
-                            tts_voice = tts_voice_conf()
-                            tts_active_play = tts_play_conf()
-
-                tts_button = tts_button_conf()
-                tts_play = sound_gui()
-
-        active_tts.change(
-            fn=show_components_tts,
-            inputs=[active_tts],
-            outputs=[tts_voice, tts_text, tts_button, tts_active_play],
-        )
-
-        aud = audio_conf()
-        # gr.HTML("<hr>")
-
-        tts_button.click(
-            fn=infer_tts_audio,
-            inputs=[tts_voice, tts_text, tts_active_play],
-            outputs=[aud, tts_play],
-        )
-
-        down_active_gui = down_active_conf()
-        down_info = gr.Markdown(
-            "Provide a link to a zip file, like this one: `https://huggingface.co/mrmocciai/Models/resolve/main/Genshin%20Impact/ayaka-v2.zip?download=true`, or separate links with a comma for the .pth and .index files, like this: `https://huggingface.co/sail-rvc/ayaka-jp/resolve/main/model.pth?download=true, https://huggingface.co/sail-rvc/ayaka-jp/resolve/main/model.index?download=true`",
-            visible=False
-        )
-        with gr.Row():
-            with gr.Column(scale=3):
-                down_url_gui = down_url_conf()
-            with gr.Column(scale=1):
-                down_button_gui = down_button_conf()
-
-        with gr.Column():
-            with gr.Row():
-                model = model_conf()
-                indx = index_conf()
-
-        down_active_gui.change(
-            show_components_down,
-            [down_active_gui],
-            [down_info, down_url_gui, down_button_gui]
-        )
-
-        down_button_gui.click(
-            get_my_model,
-            [down_url_gui],
-            [model, indx]
-        )
-
-        algo = pitch_algo_conf()
-        algo_lvl = pitch_lvl_conf()
-        indx_inf = index_inf_conf()
-        res_fc = respiration_filter_conf()
-        envel_r = envelope_ratio_conf()
-        const = consonant_protec_conf()
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    denoise_gui = denoise_conf()
-                    effects_gui = effects_conf()
-        button_base = button_conf()
-        output_base = output_conf()
-
-        button_base.click(
-            run,
-            inputs=[
-                aud,
-                model,
-                algo,
-                algo_lvl,
-                indx,
-                indx_inf,
-                res_fc,
-                envel_r,
-                const,
-                denoise_gui,
-                effects_gui,
-            ],
-            outputs=[output_base],
-        )
-
-        gr.Examples(
-            examples=[
-                [
-                    ["./test.ogg"],
-                    "./model.pth",
-                    "rmvpe+",
-                    0,
-                    "./model.index",
-                    0.75,
-                    3,
-                    0.25,
-                    0.50,
-                ],
-                [
-                    ["./example2/test2.ogg"],
-                    "./example2/model_link.txt",
-                    "rmvpe+",
-                    0,
-                    "./example2/index_link.txt",
-                    0.75,
-                    3,
-                    0.25,
-                    0.50,
-                ],
-                [
-                    ["./example3/test3.wav"],
-                    "./example3/zip_link.txt",
-                    "rmvpe+",
-                    0,
-                    None,
-                    0.75,
-                    3,
-                    0.25,
-                    0.50,
-                ],
-
-            ],
-            fn=run,
-            inputs=[
-                aud,
-                model,
-                algo,
-                algo_lvl,
-                indx,
-                indx_inf,
-                res_fc,
-                envel_r,
-                const,
-            ],
-            outputs=[output_base],
-            cache_examples=False,
-        )
-
-    return app
-
-
-if __name__ == "__main__":
-
-    tts_voice_list = asyncio.new_event_loop().run_until_complete(edge_tts.list_voices())
-    voices = sorted([f"{v['ShortName']}-{v['Gender']}" for v in tts_voice_list])
-
-    app = get_gui(theme)
-
-    app.queue(default_concurrency_limit=40)
-
-    app.launch(
-        max_threads=40,
-        share=False,
-        show_error=True,
-        quiet=False,
-        debug=False,
-        allowed_paths=["./downloads/"],
-    )
+import os
+import gradio as gr
+import spaces
+from infer_rvc_python import BaseLoader
+import random
+import logging
+import time
+import soundfile as sf
+from infer_rvc_python.main import download_manager
+import zipfile
+import edge_tts
+import asyncio
+import librosa
+import traceback
+import soundfile as sf
+from pedalboard import Pedalboard, Reverb, Compressor, HighpassFilter
+from pedalboard.io import AudioFile
+from pydub import AudioSegment
+import noisereduce as nr
+import numpy as np
+import urllib.request
+import shutil
+import threading
+
+logging.getLogger("infer_rvc_python").setLevel(logging.ERROR)
+
+converter = BaseLoader(only_cpu=False, hubert_path=None, rmvpe_path=None)
+
+title = "<center><strong><font size='7'>RVC⚡ZERO</font></strong></center>"
+description = "This demo is provided for educational and research purposes only. The authors and contributors of this project do not endorse or encourage any misuse or unethical use of this software. Any use of this software for purposes other than those intended is solely at the user's own risk. The authors and contributors shall not be held responsible for any damages or liabilities arising from the use of this demo inappropriately."
+theme = "aliabid94/new-theme"
+
+PITCH_ALGO_OPT = [
+    "pm",
+    "harvest",
+    "crepe",
+    "rmvpe",
+    "rmvpe+",
+]
+
+
+def find_files(directory):
+    file_paths = []
+    for filename in os.listdir(directory):
+        # Check if the file has the desired extension
+        if filename.endswith('.pth') or filename.endswith('.zip') or filename.endswith('.index'):
+            # If yes, add the file path to the list
+            file_paths.append(os.path.join(directory, filename))
+
+    return file_paths
+
+
+def unzip_in_folder(my_zip, my_dir):
+    with zipfile.ZipFile(my_zip) as zip:
+        for zip_info in zip.infolist():
+            if zip_info.is_dir():
+                continue
+            zip_info.filename = os.path.basename(zip_info.filename)
+            zip.extract(zip_info, my_dir)
+
+
+def find_my_model(a_, b_):
+
+    if a_ is None or a_.endswith(".pth"):
+        return a_, b_
+
+    txt_files = []
+    for base_file in [a_, b_]:
+        if base_file is not None and base_file.endswith(".txt"):
+            txt_files.append(base_file)
+
+    directory = os.path.dirname(a_)
+
+    for txt in txt_files:
+        with open(txt, 'r') as file:
+            first_line = file.readline()
+
+        download_manager(
+            url=first_line.strip(),
+            path=directory,
+            extension="",
+        )
+
+    for f in find_files(directory):
+        if f.endswith(".zip"):
+            unzip_in_folder(f, directory)
+
+    model = None
+    index = None
+    end_files = find_files(directory)
+
+    for ff in end_files:
+        if ff.endswith(".pth"):
+            model = os.path.join(directory, ff)
+            gr.Info(f"Model found: {ff}")
+        if ff.endswith(".index"):
+            index = os.path.join(directory, ff)
+            gr.Info(f"Index found: {ff}")
+
+    if not model:
+        gr.Error(f"Model not found in: {end_files}")
+
+    if not index:
+        gr.Warning("Index not found")
+
+    return model, index
+
+
+def get_file_size(url):
+
+    if "huggingface" not in url:
+        raise ValueError("Only downloads from Hugging Face are allowed")
+
+    try:
+        with urllib.request.urlopen(url) as response:
+            info = response.info()
+            content_length = info.get("Content-Length")
+
+        file_size = int(content_length)
+        if file_size > 500000000:
+            raise ValueError("The file is too large. You can only download files up to 500 MB in size.")
+
+    except Exception as e:
+        raise e
+
+
+def clear_files(directory):
+    time.sleep(15)
+    print(f"Clearing files: {directory}.")
+    shutil.rmtree(directory)
+
+
+def get_my_model(url_data):
+
+    if not url_data:
+        return None, None
+
+    if "," in url_data:
+        a_, b_ = url_data.split()
+        a_, b_ = a_.strip().replace("/blob/", "/resolve/"), b_.strip().replace("/blob/", "/resolve/")
+    else:
+        a_, b_ = url_data.strip().replace("/blob/", "/resolve/"), None
+
+    out_dir = "downloads"
+    folder_download = str(random.randint(1000, 9999))
+    directory = os.path.join(out_dir, folder_download)
+    os.makedirs(directory, exist_ok=True)
+
+    try:
+        get_file_size(a_)
+        if b_:
+            get_file_size(b_)
+
+        valid_url = [a_] if not b_ else [a_, b_]
+        for link in valid_url:
+            download_manager(
+                url=link,
+                path=directory,
+                extension="",
+            )
+
+        for f in find_files(directory):
+            if f.endswith(".zip"):
+                unzip_in_folder(f, directory)
+
+        model = None
+        index = None
+        end_files = find_files(directory)
+
+        for ff in end_files:
+            if ff.endswith(".pth"):
+                model = ff
+                gr.Info(f"Model found: {ff}")
+            if ff.endswith(".index"):
+                index = ff
+                gr.Info(f"Index found: {ff}")
+
+        if not model:
+            raise ValueError(f"Model not found in: {end_files}")
+
+        if not index:
+            gr.Warning("Index not found")
+        else:
+            index = os.path.abspath(index)
+
+        return os.path.abspath(model), index
+
+    except Exception as e:
+        raise e
+    finally:
+        # time.sleep(10)
+        # shutil.rmtree(directory)
+        t = threading.Thread(target=clear_files, args=(directory,))
+        t.start()
+
+
+def add_audio_effects(audio_list):
+    print("Audio effects")
+
+    result = []
+    for audio_path in audio_list:
+        try:
+            output_path = f'{os.path.splitext(audio_path)[0]}_effects.wav'
+
+            # Initialize audio effects plugins
+            board = Pedalboard(
+                [
+                    HighpassFilter(),
+                    Compressor(ratio=4, threshold_db=-15),
+                    Reverb(room_size=0.10, dry_level=0.8, wet_level=0.2, damping=0.7)
+                 ]
+            )
+
+            with AudioFile(audio_path) as f:
+                with AudioFile(output_path, 'w', f.samplerate, f.num_channels) as o:
+                    # Read one second of audio at a time, until the file is empty:
+                    while f.tell() < f.frames:
+                        chunk = f.read(int(f.samplerate))
+                        effected = board(chunk, f.samplerate, reset=False)
+                        o.write(effected)
+            result.append(output_path)
+        except Exception as e:
+            traceback.print_exc()
+            print(f"Error noisereduce: {str(e)}")
+            result.append(audio_path)
+
+    return result
+
+
+def apply_noisereduce(audio_list):
+    # https://github.com/sa-if/Audio-Denoiser
+    print("Noice reduce")
+
+    result = []
+    for audio_path in audio_list:
+        out_path = f'{os.path.splitext(audio_path)[0]}_noisereduce.wav'
+
+        try:
+            # Load audio file
+            audio = AudioSegment.from_file(audio_path)
+
+            # Convert audio to numpy array
+            samples = np.array(audio.get_array_of_samples())
+
+            # Reduce noise
+            reduced_noise = nr.reduce_noise(samples, sr=audio.frame_rate, prop_decrease=0.6)
+
+            # Convert reduced noise signal back to audio
+            reduced_audio = AudioSegment(
+                reduced_noise.tobytes(), 
+                frame_rate=audio.frame_rate, 
+                sample_width=audio.sample_width,
+                channels=audio.channels
+            )
+
+            # Save reduced audio to file
+            reduced_audio.export(out_path, format="wav")
+            result.append(out_path)
+
+        except Exception as e:
+            traceback.print_exc()
+            print(f"Error noisereduce: {str(e)}")
+            result.append(audio_path)
+
+    return result
+
+
+@spaces.GPU()
+def convert_now(audio_files, random_tag, converter):
+    return converter(
+        audio_files,
+        random_tag,
+        overwrite=False,
+        parallel_workers=8
+    )
+
+
+def run(
+    audio_files,
+    file_m,
+    pitch_alg,
+    pitch_lvl,
+    file_index,
+    index_inf,
+    r_m_f,
+    e_r,
+    c_b_p,
+    active_noise_reduce,
+    audio_effects,
+):
+    if not audio_files:
+        raise ValueError("The audio pls")
+
+    if isinstance(audio_files, str):
+        audio_files = [audio_files]
+
+    try:
+        duration_base = librosa.get_duration(filename=audio_files[0])
+        print("Duration:", duration_base)
+    except Exception as e:
+        print(e)
+
+    if file_m is not None and file_m.endswith(".txt"):
+        file_m, file_index = find_my_model(file_m, file_index)
+        print(file_m, file_index)
+
+    random_tag = "USER_"+str(random.randint(10000000, 99999999))
+
+    converter.apply_conf(
+        tag=random_tag,
+        file_model=file_m,
+        pitch_algo=pitch_alg,
+        pitch_lvl=pitch_lvl,
+        file_index=file_index,
+        index_influence=index_inf,
+        respiration_median_filtering=r_m_f,
+        envelope_ratio=e_r,
+        consonant_breath_protection=c_b_p,
+        resample_sr=44100 if audio_files[0].endswith('.mp3') else 0, 
+    )
+    time.sleep(0.1)
+
+    result = convert_now(audio_files, random_tag, converter)
+
+    if active_noise_reduce:
+        result = apply_noisereduce(result)
+
+    if audio_effects:
+        result = add_audio_effects(result)
+
+    return result
+
+
+def audio_conf():
+    return gr.File(
+        label="Audio files",
+        file_count="multiple",
+        type="filepath",
+        container=True,
+    )
+
+
+def model_conf():
+    return gr.File(
+        label="Model file",
+        type="filepath",
+        height=130,
+    )
+
+
+def pitch_algo_conf():
+    return gr.Dropdown(
+        PITCH_ALGO_OPT,
+        value=PITCH_ALGO_OPT[4],
+        label="Pitch algorithm",
+        visible=True,
+        interactive=True,
+    )
+
+
+def pitch_lvl_conf():
+    return gr.Slider(
+        label="Pitch level",
+        minimum=-24,
+        maximum=24,
+        step=1,
+        value=0,
+        visible=True,
+        interactive=True,
+    )
+
+
+def index_conf():
+    return gr.File(
+        label="Index file",
+        type="filepath",
+        height=130,
+    )
+
+
+def index_inf_conf():
+    return gr.Slider(
+        minimum=0,
+        maximum=1,
+        label="Index influence",
+        value=0.75,
+    )
+
+
+def respiration_filter_conf():
+    return gr.Slider(
+        minimum=0,
+        maximum=7,
+        label="Respiration median filtering",
+        value=3,
+        step=1,
+        interactive=True,
+    )
+
+
+def envelope_ratio_conf():
+    return gr.Slider(
+        minimum=0,
+        maximum=1,
+        label="Envelope ratio",
+        value=0.25,
+        interactive=True,
+    )
+
+
+def consonant_protec_conf():
+    return gr.Slider(
+        minimum=0,
+        maximum=0.5,
+        label="Consonant breath protection",
+        value=0.5,
+        interactive=True,
+    )
+
+
+def button_conf():
+    return gr.Button(
+        "Inference",
+        variant="primary",
+    )
+
+
+def output_conf():
+    return gr.File(
+        label="Result",
+        file_count="multiple",
+        interactive=False,
+    )
+
+
+def active_tts_conf():
+    return gr.Checkbox(
+        False,
+        label="TTS",
+        # info="",
+        container=False,
+    )
+
+
+def tts_voice_conf():
+    return gr.Dropdown(
+        label="tts voice",
+        choices=voices,
+        visible=False,
+        value="en-US-EmmaMultilingualNeural-Female",
+    )
+
+
+def tts_text_conf():
+    return gr.Textbox(
+        value="",
+        placeholder="Write the text here...",
+        label="Text",
+        visible=False,
+        lines=3,
+    )
+
+
+def tts_button_conf():
+    return gr.Button(
+        "Process TTS",
+        variant="secondary",
+        visible=False,
+    )
+
+
+def tts_play_conf():
+    return gr.Checkbox(
+        False,
+        label="Play",
+        # info="",
+        container=False,
+        visible=False,
+    )
+
+
+def sound_gui():
+    return gr.Audio(
+        value=None,
+        type="filepath",
+        # format="mp3",
+        autoplay=True,
+        visible=False,
+    )
+
+
+def denoise_conf():
+    return gr.Checkbox(
+        False,
+        label="Denoise",
+        # info="",
+        container=False,
+        visible=True,
+    )
+
+
+def effects_conf():
+    return gr.Checkbox(
+        False,
+        label="Reverb",
+        # info="",
+        container=False,
+        visible=True,
+    )
+
+
+def infer_tts_audio(tts_voice, tts_text, play_tts):
+    out_dir = "output"
+    folder_tts = "USER_"+str(random.randint(10000, 99999))
+
+    os.makedirs(out_dir, exist_ok=True)
+    os.makedirs(os.path.join(out_dir, folder_tts), exist_ok=True)
+    out_path = os.path.join(out_dir, folder_tts, "tts.mp3")
+
+    asyncio.run(edge_tts.Communicate(tts_text, "-".join(tts_voice.split('-')[:-1])).save(out_path))
+    if play_tts:
+        return [out_path], out_path
+    return [out_path], None
+
+
+def show_components_tts(value_active):
+    return gr.update(
+        visible=value_active
+    ), gr.update(
+        visible=value_active
+    ), gr.update(
+        visible=value_active
+    ), gr.update(
+        visible=value_active
+    )
+
+
+def down_active_conf():
+    return gr.Checkbox(
+        False,
+        label="URL-to-Model",
+        # info="",
+        container=False,
+    )
+
+
+def down_url_conf():
+    return gr.Textbox(
+        value="",
+        placeholder="Write the url here...",
+        label="Enter URL",
+        visible=False,
+        lines=1,
+    )
+
+
+def down_button_conf():
+    return gr.Button(
+        "Process",
+        variant="secondary",
+        visible=False,
+    )
+
+
+def show_components_down(value_active):
+    return gr.update(
+        visible=value_active
+    ), gr.update(
+        visible=value_active
+    ), gr.update(
+        visible=value_active
+    )
+
+
+def get_gui(theme):
+    with gr.Blocks(theme=theme, fill_width=True, fill_height=True, delete_cache=(3200, 3200)) as app:
+        gr.Markdown(title)
+        gr.Markdown(description)
+
+        active_tts = active_tts_conf()
+        with gr.Row():
+            with gr.Column(scale=1):
+                tts_text = tts_text_conf()
+            with gr.Column(scale=2):
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Row():
+                            tts_voice = tts_voice_conf()
+                            tts_active_play = tts_play_conf()
+
+                tts_button = tts_button_conf()
+                tts_play = sound_gui()
+
+        active_tts.change(
+            fn=show_components_tts,
+            inputs=[active_tts],
+            outputs=[tts_voice, tts_text, tts_button, tts_active_play],
+        )
+
+        aud = audio_conf()
+        # gr.HTML("<hr>")
+
+        tts_button.click(
+            fn=infer_tts_audio,
+            inputs=[tts_voice, tts_text, tts_active_play],
+            outputs=[aud, tts_play],
+        )
+
+        down_active_gui = down_active_conf()
+        down_info = gr.Markdown(
+            "Provide a link to a zip file, like this one: `https://huggingface.co/mrmocciai/Models/resolve/main/Genshin%20Impact/ayaka-v2.zip?download=true`, or separate links with a comma for the .pth and .index files, like this: `https://huggingface.co/sail-rvc/ayaka-jp/resolve/main/model.pth?download=true, https://huggingface.co/sail-rvc/ayaka-jp/resolve/main/model.index?download=true`",
+            visible=False
+        )
+        with gr.Row():
+            with gr.Column(scale=3):
+                down_url_gui = down_url_conf()
+            with gr.Column(scale=1):
+                down_button_gui = down_button_conf()
+
+        with gr.Column():
+            with gr.Row():
+                model = model_conf()
+                indx = index_conf()
+
+        down_active_gui.change(
+            show_components_down,
+            [down_active_gui],
+            [down_info, down_url_gui, down_button_gui]
+        )
+
+        down_button_gui.click(
+            get_my_model,
+            [down_url_gui],
+            [model, indx]
+        )
+
+        algo = pitch_algo_conf()
+        algo_lvl = pitch_lvl_conf()
+        indx_inf = index_inf_conf()
+        res_fc = respiration_filter_conf()
+        envel_r = envelope_ratio_conf()
+        const = consonant_protec_conf()
+        with gr.Row():
+            with gr.Column():
+                with gr.Row():
+                    denoise_gui = denoise_conf()
+                    effects_gui = effects_conf()
+        button_base = button_conf()
+        output_base = output_conf()
+
+        button_base.click(
+            run,
+            inputs=[
+                aud,
+                model,
+                algo,
+                algo_lvl,
+                indx,
+                indx_inf,
+                res_fc,
+                envel_r,
+                const,
+                denoise_gui,
+                effects_gui,
+            ],
+            outputs=[output_base],
+        )
+
+        gr.Examples(
+            examples=[
+                [
+                    ["./test.ogg"],
+                    "./model.pth",
+                    "rmvpe+",
+                    0,
+                    "./model.index",
+                    0.75,
+                    3,
+                    0.25,
+                    0.50,
+                ],
+                [
+                    ["./example2/test2.ogg"],
+                    "./example2/model_link.txt",
+                    "rmvpe+",
+                    0,
+                    "./example2/index_link.txt",
+                    0.75,
+                    3,
+                    0.25,
+                    0.50,
+                ],
+                [
+                    ["./example3/test3.wav"],
+                    "./example3/zip_link.txt",
+                    "rmvpe+",
+                    0,
+                    None,
+                    0.75,
+                    3,
+                    0.25,
+                    0.50,
+                ],
+
+            ],
+            fn=run,
+            inputs=[
+                aud,
+                model,
+                algo,
+                algo_lvl,
+                indx,
+                indx_inf,
+                res_fc,
+                envel_r,
+                const,
+            ],
+            outputs=[output_base],
+            cache_examples=False,
+        )
+
+    return app
+
+
+if __name__ == "__main__":
+
+    tts_voice_list = asyncio.new_event_loop().run_until_complete(edge_tts.list_voices())
+    voices = sorted([f"{v['ShortName']}-{v['Gender']}" for v in tts_voice_list])
+
+    app = get_gui(theme)
+
+    app.queue(default_concurrency_limit=40)
+
+    app.launch(
+        max_threads=40,
+        share=False,
+        show_error=True,
+        quiet=False,
+        debug=False,
+        ssr_mode=False,
+        allowed_paths=["./downloads/"],
+    )

pre-requirements.txt

@@ -0,0 +1 @@
+pip==24.0

requirements.txt

@@ -1,6 +1,8 @@
-torch==2.2.0
-infer-rvc-python==1.1.0
-edge-tts
-pedalboard
-noisereduce
-numpy==1.23.5
+torch==2.2.0
+infer-rvc-python==1.1.0
+edge-tts
+pedalboard
+noisereduce
+numpy==1.23.5
+transformers<=4.48.3
+pydantic==2.10.6