File size: 15,416 Bytes
c2dad70
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8c5624f
2d261dd
8c5624f
 
 
c2dad70
 
 
 
2d261dd
c2dad70
 
 
2d261dd
c2dad70
 
 
2d261dd
c2dad70
 
 
 
 
d524d37
c2dad70
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c52395e
c2dad70
4e4c3fe
 
c52395e
4e4c3fe
 
 
 
 
 
8c5624f
 
 
 
 
4e4c3fe
 
8c5624f
 
4e4c3fe
8c5624f
4e4c3fe
 
 
 
 
 
be23d15
c2dad70
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
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, DEMUCS_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()}
        models_url[DEMUCS_ARCH_TYPE] = online_data["demucs_download_list"]
        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"),
            DEMUCS_ARCH_TYPE: (DEMUCS_MODELS_DIR, ".yaml"),
        }
        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)
        elif arch == DEMUCS_ARCH_TYPE:
            pass

    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())
        elif arch == DEMUCS_ARCH_TYPE:
            model_update = self.model_choice.update(choices=choices, value=CHOOSE_MODEL, label=CHOOSE_DEMUCS_MODEL_MAIN_LABEL)
            raise gr.Error(f"{DEMUCS_ARCH_TYPE} not implempted")
        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("<h1> 🎵 Ultimate Vocal Remover WebUI 🎵 </h1>")
            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/r3gm/Ultimate-Vocal-Remover-WebUI?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='Rhythmic Transmutation Device', value=True, interactive=True) #label=GPU_CONVERSION_MAIN_LABEL, value=root.is_gpu_conversion_var.get(), 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("Settings Guide"):
                            pass
                        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)
                        with gr.TabItem("Download models"):

                            def md_url(url, text=None):
                                if text is None:
                                    text = url
                                return f"[{url}]({url})"

                            with gr.Row():
                                vr_models = self.models_url[VR_ARCH_TYPE]
                                self.vr_download_choice = gr.Dropdown(choices=list(vr_models.keys()), label=f"Select {VR_ARCH_TYPE} Model", interactive=True)
                                self.vr_download_url = gr.Markdown()
                                self.vr_download_choice.change(lambda model: md_url(vr_models[model]), inputs=self.vr_download_choice, outputs=self.vr_download_url)
                            with gr.Row(variant="panel"):
                                mdx_models = self.models_url[MDX_ARCH_TYPE]
                                self.mdx_download_choice = gr.Dropdown(choices=list(mdx_models.keys()), label=f"Select {MDX_ARCH_TYPE} Model", interactive=True)
                                self.mdx_download_url = gr.Markdown()
                                self.mdx_download_choice.change(lambda model: md_url(mdx_models[model]), inputs=self.mdx_download_choice, outputs=self.mdx_download_url)
                            with gr.Row(variant="panel"):
                                demucs_models: Dict[str, Dict] = self.models_url[DEMUCS_ARCH_TYPE]
                                self.demucs_download_choice = gr.Dropdown(choices=list(demucs_models.keys()), label=f"Select {DEMUCS_ARCH_TYPE} Model", interactive=True)
                                self.demucs_download_url = gr.Markdown()

                                self.demucs_download_choice.change(
                                    lambda model: "\n".join([
                                        "- " + md_url(url, text=filename) for filename, url in demucs_models[model].items()]),
                                    inputs=self.demucs_download_choice,
                                    outputs=self.demucs_download_url)

            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.")
    else:
        print(f"Ignoring category: {category}")




webui = UVRWebUI(uvr, online_data_path='models/download_checks.json')
webui.launch()