import os import json import librosa import soundfile import numpy as np import gradio as gr from UVR_interface import root, UVRInterface, VR_MODELS_DIR, MDX_MODELS_DIR from gui_data.constants import * from typing import List, Dict, Callable, Union class UVRWebUI: def __init__(self, uvr: UVRInterface, online_data_path: str) -> None: self.uvr = uvr self.models_url = self.get_models_url(online_data_path) self.define_layout() self.input_temp_dir = "__temp" self.export_path = "out" if not os.path.exists(self.input_temp_dir): os.mkdir(self.input_temp_dir) def get_models_url(self, models_info_path: str) -> Dict[str, Dict]: with open(models_info_path, "r") as f: online_data = json.loads(f.read()) models_url = {} for arch, download_list_key in zip([VR_ARCH_TYPE, MDX_ARCH_TYPE], ["vr_download_list", "mdx_download_list"]): models_url[arch] = {model: NORMAL_REPO+model_path for model, model_path in online_data[download_list_key].items()} return models_url def get_local_models(self, arch: str) -> List[str]: model_config = { VR_ARCH_TYPE: (VR_MODELS_DIR, ".pth"), MDX_ARCH_TYPE: (MDX_MODELS_DIR, ".onnx"), } try: model_dir, suffix = model_config[arch] except KeyError: raise ValueError(f"Unkown arch type: {arch}") return [os.path.splitext(f)[0] for f in os.listdir(model_dir) if f.endswith(suffix)] def set_arch_setting_value(self, arch: str, setting1, setting2): if arch == VR_ARCH_TYPE: root.window_size_var.set(setting1) root.aggression_setting_var.set(setting2) elif arch == MDX_ARCH_TYPE: root.mdx_batch_size_var.set(setting1) root.compensate_var.set(setting2) def arch_select_update(self, arch: str) -> List[Dict]: choices = self.get_local_models(arch) if arch == VR_ARCH_TYPE: model_update = self.model_choice.update(choices=choices, value=CHOOSE_MODEL, label=SELECT_VR_MODEL_MAIN_LABEL) setting1_update = self.arch_setting1.update(choices=VR_WINDOW, label=WINDOW_SIZE_MAIN_LABEL, value=root.window_size_var.get()) setting2_update = self.arch_setting2.update(choices=VR_AGGRESSION, label=AGGRESSION_SETTING_MAIN_LABEL, value=root.aggression_setting_var.get()) elif arch == MDX_ARCH_TYPE: model_update = self.model_choice.update(choices=choices, value=CHOOSE_MODEL, label=CHOOSE_MDX_MODEL_MAIN_LABEL) setting1_update = self.arch_setting1.update(choices=BATCH_SIZE, label=BATCHES_MDX_MAIN_LABEL, value=root.mdx_batch_size_var.get()) setting2_update = self.arch_setting2.update(choices=VOL_COMPENSATION, label=VOL_COMP_MDX_MAIN_LABEL, value=root.compensate_var.get()) else: raise gr.Error(f"Unkown arch type: {arch}") return [model_update, setting1_update, setting2_update] def model_select_update(self, arch: str, model_name: str) -> List[Union[str, Dict, None]]: if model_name == CHOOSE_MODEL: return [None for _ in range(4)] model, = self.uvr.assemble_model_data(model_name, arch) if not model.model_status: raise gr.Error(f"Cannot get model data, model hash = {model.model_hash}") stem1_check_update = self.primary_stem_only.update(label=f"{model.primary_stem} Only") stem2_check_update = self.secondary_stem_only.update(label=f"{model.secondary_stem} Only") stem1_out_update = self.primary_stem_out.update(label=f"Output {model.primary_stem}") stem2_out_update = self.secondary_stem_out.update(label=f"Output {model.secondary_stem}") return [stem1_check_update, stem2_check_update, stem1_out_update, stem2_out_update] def checkbox_set_root_value(self, checkbox: gr.Checkbox, root_attr: str): checkbox.change(lambda value: root.__getattribute__(root_attr).set(value), inputs=checkbox) def set_checkboxes_exclusive(self, checkboxes: List[gr.Checkbox], pure_callbacks: List[Callable], exclusive_value=True): def exclusive_onchange(i, callback_i): def new_onchange(*check_values): if check_values[i] == exclusive_value: return_values = [] for j, value_j in enumerate(check_values): if j != i and value_j == exclusive_value: return_values.append(not exclusive_value) else: return_values.append(value_j) else: return_values = check_values callback_i(check_values[i]) return return_values return new_onchange for i, (checkbox, callback) in enumerate(zip(checkboxes, pure_callbacks)): checkbox.change(exclusive_onchange(i, callback), inputs=checkboxes, outputs=checkboxes) def process(self, input_audio, input_filename, model_name, arch, setting1, setting2, progress=gr.Progress()): def set_progress_func(step, inference_iterations=0): progress_curr = step + inference_iterations progress(progress_curr) sampling_rate, audio = input_audio audio = (audio / np.iinfo(audio.dtype).max).astype(np.float32) if len(audio.shape) > 1: audio = librosa.to_mono(audio.transpose(1, 0)) input_path = os.path.join(self.input_temp_dir, input_filename) soundfile.write(input_path, audio, sampling_rate, format="wav") self.set_arch_setting_value(arch, setting1, setting2) seperator = uvr.process( model_name=model_name, arch_type=arch, audio_file=input_path, export_path=self.export_path, is_model_sample_mode=root.model_sample_mode_var.get(), set_progress_func=set_progress_func, ) primary_audio = None secondary_audio = None msg = "" if not seperator.is_secondary_stem_only: primary_stem_path = os.path.join(seperator.export_path, f"{seperator.audio_file_base}_({seperator.primary_stem}).wav") audio, rate = soundfile.read(primary_stem_path) primary_audio = (rate, audio) msg += f"{seperator.primary_stem} saved at {primary_stem_path}\n" if not seperator.is_primary_stem_only: secondary_stem_path = os.path.join(seperator.export_path, f"{seperator.audio_file_base}_({seperator.secondary_stem}).wav") audio, rate = soundfile.read(secondary_stem_path) secondary_audio = (rate, audio) msg += f"{seperator.secondary_stem} saved at {secondary_stem_path}\n" os.remove(input_path) return primary_audio, secondary_audio, msg def define_layout(self): with gr.Blocks() as app: self.app = app gr.HTML("

🎵 Ultimate Vocal Remover 5.6 for Hugging Face 🎵

") gr.Markdown("## Space created by [Not Eddy (Spanish Mod)](http://discord.com/users/274566299349155851) in [AI HUB](https://discord.gg/aihub) server.") gr.Markdown("## You can use a GPU version in this [Colab](https://colab.research.google.com/github/Eddycrack864/Ultimate-Vocal-Remover-5.6-for-Google-Colab/blob/main/Ultimate_Vocal_Remover_5_6_for_Google_Colab.ipynb). If you liked the space and colab you can give it a 💖 and star my repo on [GitHub](https://github.com/Eddycrack864/UVR5-5.6-for-Colab).") gr.Markdown("### Thanks to: [Hina](https://github.com/hinabl), [r3gm](https://github.com/R3gm) and [Anjok07](https://github.com/Anjok07)") gr.Markdown("### You can donate to the original UVR5 project [here](https://www.buymeacoffee.com/uvr5):") gr.Markdown("### This is an experimental demo with CPU. Duplicate the space for use in private.") gr.Markdown( "[![Duplicate this Space](https://huggingface.co./datasets/huggingface/badges/raw/main/duplicate-this-space-sm-dark.svg)](https://huggingface.co./spaces/Eddycrack864/UVR5?duplicate=true)\n\n" ) with gr.Tabs(): with gr.TabItem("Process"): with gr.Row(): self.arch_choice = gr.Dropdown( choices=[VR_ARCH_TYPE, MDX_ARCH_TYPE], value=VR_ARCH_TYPE, # choices=[VR_ARCH_TYPE, MDX_ARCH_TYPE, DEMUCS_ARCH_TYPE], value=VR_ARCH_TYPE, label=CHOOSE_PROC_METHOD_MAIN_LABEL, interactive=True) self.model_choice = gr.Dropdown( choices=self.get_local_models(VR_ARCH_TYPE), value=CHOOSE_MODEL, label=SELECT_VR_MODEL_MAIN_LABEL+' 👋Select a model', interactive=True) with gr.Row(): self.arch_setting1 = gr.Dropdown( choices=VR_WINDOW, value=root.window_size_var.get(), label=WINDOW_SIZE_MAIN_LABEL+' 👋Select one', interactive=True) self.arch_setting2 = gr.Dropdown( choices=VR_AGGRESSION, value=root.aggression_setting_var.get(), label=AGGRESSION_SETTING_MAIN_LABEL, interactive=True) with gr.Row(): self.use_gpu = gr.Checkbox( label=GPU_CONVERSION_MAIN_LABEL, value=root.is_gpu_conversion_var.get(), interactive=True) #label='Rhythmic Transmutation Device', value=True, interactive=True) self.primary_stem_only = gr.Checkbox( label=f"{PRIMARY_STEM} only", value=root.is_primary_stem_only_var.get(), interactive=True) self.secondary_stem_only = gr.Checkbox( label=f"{SECONDARY_STEM} only", value=root.is_secondary_stem_only_var.get(), interactive=True) self.sample_mode = gr.Checkbox( label=SAMPLE_MODE_CHECKBOX(root.model_sample_mode_duration_var.get()), value=root.model_sample_mode_var.get(), interactive=True) with gr.Row(): self.input_filename = gr.Textbox(label="Input filename", value="temp.wav", interactive=True) with gr.Row(): self.audio_in = gr.Audio(label="Input audio", interactive=True) with gr.Row(): self.process_submit = gr.Button(START_PROCESSING, variant="primary") with gr.Row(): self.primary_stem_out = gr.Audio(label=f"Output {PRIMARY_STEM}", interactive=False) self.secondary_stem_out = gr.Audio(label=f"Output {SECONDARY_STEM}", interactive=False) with gr.Row(): self.out_message = gr.Textbox(label="Output Message", interactive=False, show_progress=False) with gr.TabItem("Settings"): with gr.Tabs(): with gr.TabItem("Additional Settigns"): self.wav_type = gr.Dropdown(choices=WAV_TYPE, label="Wav Type", value="PCM_16", interactive=True) self.mp3_rate = gr.Dropdown(choices=MP3_BIT_RATES, label="MP3 Bitrate", value="320k",interactive=True) self.arch_choice.change( self.arch_select_update, inputs=self.arch_choice, outputs=[self.model_choice, self.arch_setting1, self.arch_setting2]) self.model_choice.change( self.model_select_update, inputs=[self.arch_choice, self.model_choice], outputs=[self.primary_stem_only, self.secondary_stem_only, self.primary_stem_out, self.secondary_stem_out]) self.checkbox_set_root_value(self.use_gpu, 'is_gpu_conversion_var') self.checkbox_set_root_value(self.sample_mode, 'model_sample_mode_var') self.set_checkboxes_exclusive( [self.primary_stem_only, self.secondary_stem_only], [lambda value: root.is_primary_stem_only_var.set(value), lambda value: root.is_secondary_stem_only_var.set(value)]) self.process_submit.click( self.process, inputs=[self.audio_in, self.input_filename, self.model_choice, self.arch_choice, self.arch_setting1, self.arch_setting2], outputs=[self.primary_stem_out, self.secondary_stem_out, self.out_message]) def launch(self, **kwargs): self.app.queue().launch(**kwargs) uvr = UVRInterface() uvr.cached_sources_clear() webui = UVRWebUI(uvr, online_data_path='models/download_checks.json') print(webui.models_url) model_dict = webui.models_url import os import wget for category, models in model_dict.items(): if category in ['VR Arc', 'MDX-Net']: if category == 'VR Arc': model_path = 'models/VR_Models' elif category == 'MDX-Net': model_path = 'models/MDX_Net_Models' for model_name, model_url in models.items(): cmd = f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -j5 -x16 -s16 -k1M -c -d {model_path} -Z {model_url}" os.system(cmd) print("Models downloaded successfully.") webui = UVRWebUI(uvr, online_data_path='models/download_checks.json') webui.launch()