File size: 15,110 Bytes
16de183
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7ad983b
 
 
 
 
16de183
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7ad983b
16de183
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7ad983b
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
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
import os, sys
import gradio as gr
import regex as re
import shutil
import datetime
import random

from core import (
    run_infer_script,
    run_batch_infer_script,
)

from assets.i18n.i18n import I18nAuto

from rvc.lib.utils import format_title

i18n = I18nAuto()

now_dir = os.getcwd()
sys.path.append(now_dir)

model_root = os.path.join(now_dir, "logs")
audio_root = os.path.join(now_dir, "assets", "audios")

model_root_relative = os.path.relpath(model_root, now_dir)
audio_root_relative = os.path.relpath(audio_root, now_dir)

sup_audioext = {
    "wav",
    "mp3",
    "flac",
    "ogg",
    "opus",
    "m4a",
    "mp4",
    "aac",
    "alac",
    "wma",
    "aiff",
    "webm",
    "ac3",
}

names = [
    os.path.join(root, file)
    for root, _, files in os.walk(model_root_relative, topdown=False)
    for file in files
    if (
        file.endswith((".pth", ".onnx"))
        and not (file.startswith("G_") or file.startswith("D_"))
    )
]

indexes_list = [
    os.path.join(root, name)
    for root, _, files in os.walk(model_root_relative, topdown=False)
    for name in files
    if name.endswith(".index") and "trained" not in name
]

audio_paths = [
    os.path.join(root, name)
    for root, _, files in os.walk(audio_root_relative, topdown=False)
    for name in files
    if name.endswith(tuple(sup_audioext))
    and root == audio_root_relative
    and "_output" not in name
]


def output_path_fn(input_audio_path):
    original_name_without_extension = os.path.basename(input_audio_path).rsplit(".", 1)[
        0
    ]
    new_name = original_name_without_extension + "_output.wav"
    output_path = os.path.join(os.path.dirname(input_audio_path), new_name)
    return output_path


def change_choices():
    names = [
        os.path.join(root, file)
        for root, _, files in os.walk(model_root_relative, topdown=False)
        for file in files
        if (
            file.endswith((".pth", ".onnx"))
            and not (file.startswith("G_") or file.startswith("D_"))
        )
    ]

    indexes_list = [
        os.path.join(root, name)
        for root, _, files in os.walk(model_root_relative, topdown=False)
        for name in files
        if name.endswith(".index") and "trained" not in name
    ]

    audio_paths = [
        os.path.join(root, name)
        for root, _, files in os.walk(audio_root_relative, topdown=False)
        for name in files
        if name.endswith(tuple(sup_audioext))
        and root == audio_root_relative
        and "_output" not in name
    ]

    return (
        {"choices": sorted(names), "__type__": "update"},
        {"choices": sorted(indexes_list), "__type__": "update"},
        {"choices": sorted(audio_paths), "__type__": "update"},
    )


def get_indexes():
    indexes_list = [
        os.path.join(dirpath, filename)
        for dirpath, _, filenames in os.walk(model_root_relative)
        for filename in filenames
        if filename.endswith(".index") and "trained" not in filename
    ]

    return indexes_list if indexes_list else ""


def match_index(model_file: str) -> tuple:
    model_files_trip = re.sub(r"\.pth|\.onnx$", "", model_file)
    model_file_name = os.path.split(model_files_trip)[
        -1
    ]  # Extract only the name, not the directory

    # Check if the sid0strip has the specific ending format _eXXX_sXXX
    if re.match(r".+_e\d+_s\d+$", model_file_name):
        base_model_name = model_file_name.rsplit("_", 2)[0]
    else:
        base_model_name = model_file_name

    sid_directory = os.path.join(model_root_relative, base_model_name)
    double_sid_directory = os.path.join(sid_directory, base_model_name)
    directories_to_search = [sid_directory] if os.path.exists(sid_directory) else []
    directories_to_search += (
        [double_sid_directory] if os.path.exists(double_sid_directory) else []
    )
    directories_to_search.append(model_root_relative)
    matching_index_files = []

    for directory in directories_to_search:
        for filename in os.listdir(directory):
            if filename.endswith(".index") and "trained" not in filename:
                # Condition to match the name
                name_match = any(
                    name.lower() in filename.lower()
                    for name in [model_file_name, base_model_name]
                )

                # If in the specific directory, it's automatically a match
                folder_match = directory == sid_directory

                if name_match or folder_match:
                    index_path = os.path.join(directory, filename)
                    if index_path in indexes_list:
                        matching_index_files.append(
                            (
                                index_path,
                                os.path.getsize(index_path),
                                " " not in filename,
                            )
                        )
    if matching_index_files:
        # Sort by favoring files without spaces and by size (largest size first)
        matching_index_files.sort(key=lambda x: (-x[2], -x[1]))
        best_match_index_path = matching_index_files[0][0]
        return best_match_index_path

    return ""


def save_to_wav(record_button):
    if record_button is None:
        pass
    else:
        path_to_file = record_button
        new_name = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + ".wav"
        target_path = os.path.join(audio_root_relative, os.path.basename(new_name))

        shutil.move(path_to_file, target_path)
        return target_path, output_path_fn(target_path)


def save_to_wav2(upload_audio):
    file_path = upload_audio
    formated_name = format_title(os.path.basename(file_path))
    target_path = os.path.join(audio_root_relative, formated_name)

    if os.path.exists(target_path):
        os.remove(target_path)

    shutil.copy(file_path, target_path)
    return target_path, output_path_fn(target_path)


def delete_outputs():
    for root, _, files in os.walk(audio_root_relative, topdown=False):
        for name in files:
            if name.endswith(tuple(sup_audioext)) and name.__contains__("_output"):
                os.remove(os.path.join(root, name))
    gr.Info(f"Outputs cleared!")


# Inference tab
def inference_tab():
    default_weight = random.choice(names) if names else None
    with gr.Row():
        with gr.Row():
            model_file = gr.Dropdown(
                label=i18n("Voice Model"),
                choices=sorted(names, key=lambda path: os.path.getsize(path)),
                interactive=True,
                value=default_weight,
                allow_custom_value=True,
            )

            index_file = gr.Dropdown(
                label=i18n("Index File"),
                choices=get_indexes(),
                value=match_index(default_weight) if default_weight else "",
                interactive=True,
                allow_custom_value=True,
            )
        with gr.Column():
            refresh_button = gr.Button(i18n("Refresh"))
            unload_button = gr.Button(i18n("Unload Voice"))

            unload_button.click(
                fn=lambda: ({"value": "", "__type__": "update"}),
                inputs=[],
                outputs=[model_file],
            )

            model_file.select(
                fn=match_index,
                inputs=[model_file],
                outputs=[index_file],
            )

    # Single inference tab
    with gr.Tab(i18n("Single")):
        with gr.Row():
            with gr.Column():
                upload_audio = gr.Audio(
                    label=i18n("Upload Audio"), type="filepath", editable=False
                )
                with gr.Row():
                    audio = gr.Dropdown(
                        label=i18n("Select Audio"),
                        choices=sorted(audio_paths),
                        value=audio_paths[0] if audio_paths else "",
                        interactive=True,
                        allow_custom_value=True,
                    )

        with gr.Accordion(i18n("Advanced Settings"), open=False):
            with gr.Column():
                clear_outputs = gr.Button(
                    i18n("Clear Outputs (Deletes all audios in assets/audios)")
                )
                output_path = gr.Textbox(
                    label=i18n("Output Path"),
                    placeholder=i18n("Enter output path"),
                    value=(
                        output_path_fn(audio_paths[0])
                        if audio_paths
                        else os.path.join(now_dir, "assets", "audios", "output.wav")
                    ),
                    interactive=True,
                )
                split_audio = gr.Checkbox(
                    label=i18n("Split Audio"),
                    visible=True,
                    value=False,
                    interactive=True,
                )
                pitch = gr.Slider(
                    minimum=-24,
                    maximum=24,
                    step=1,
                    label=i18n("Pitch"),
                    value=0,
                    interactive=True,
                )
                filter_radius = gr.Slider(
                    minimum=0,
                    maximum=7,
                    label=i18n(
                        "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness"
                    ),
                    value=3,
                    step=1,
                    interactive=True,
                )
                index_rate = gr.Slider(
                    minimum=0,
                    maximum=1,
                    label=i18n("Search Feature Ratio"),
                    value=0.75,
                    interactive=True,
                )
                hop_length = gr.Slider(
                    minimum=1,
                    maximum=512,
                    step=1,
                    label=i18n("Hop Length"),
                    value=128,
                    interactive=True,
                )
            with gr.Column():
                f0method = gr.Radio(
                    label=i18n("Pitch extraction algorithm"),
                    choices=[
                        "pm",
                        "harvest",
                        "dio",
                        "crepe",
                        "crepe-tiny",
                        "rmvpe",
                    ],
                    value="rmvpe",
                    interactive=True,
                )

        convert_button1 = gr.Button(i18n("Convert"))

        with gr.Row():  # Defines output info + output audio download after conversion
            vc_output1 = gr.Textbox(label=i18n("Output Information"))
            vc_output2 = gr.Audio(label=i18n("Export Audio"))

    # Batch inference tab
    with gr.Tab(i18n("Batch")):
        with gr.Row():
            with gr.Column():
                input_folder_batch = gr.Textbox(
                    label=i18n("Input Folder"),
                    placeholder=i18n("Enter input path"),
                    value=os.path.join(now_dir, "assets", "audios"),
                    interactive=True,
                )
                output_folder_batch = gr.Textbox(
                    label=i18n("Output Folder"),
                    placeholder=i18n("Enter output path"),
                    value=os.path.join(now_dir, "assets", "audios"),
                    interactive=True,
                )
        with gr.Accordion(i18n("Advanced Settings"), open=False):
            with gr.Column():
                clear_outputs = gr.Button(
                    i18n("Clear Outputs (Deletes all audios in assets/audios)")
                )
                pitch_batch = gr.Slider(
                    minimum=-24,
                    maximum=24,
                    step=1,
                    label=i18n("Pitch"),
                    value=0,
                    interactive=True,
                )
                filter_radius_batch = gr.Slider(
                    minimum=0,
                    maximum=7,
                    label=i18n(
                        "If >=3: apply median filtering to the harvested pitch results. The value represents the filter radius and can reduce breathiness"
                    ),
                    value=3,
                    step=1,
                    interactive=True,
                )
                index_rate_batch = gr.Slider(
                    minimum=0,
                    maximum=1,
                    label=i18n("Search Feature Ratio"),
                    value=0.75,
                    interactive=True,
                )
                hop_length_batch = gr.Slider(
                    minimum=1,
                    maximum=512,
                    step=1,
                    label=i18n("Hop Length"),
                    value=128,
                    interactive=True,
                )
            with gr.Column():
                f0method_batch = gr.Radio(
                    label=i18n("Pitch extraction algorithm"),
                    choices=[
                        "pm",
                        "harvest",
                        "dio",
                        "crepe",
                        "crepe-tiny",
                        "rmvpe",
                    ],
                    value="rmvpe",
                    interactive=True,
                )

        convert_button2 = gr.Button(i18n("Convert"))

        with gr.Row():  # Defines output info + output audio download after conversion
            vc_output3 = gr.Textbox(label=i18n("Output Information"))

    def toggle_visible(checkbox):
        return {"visible": checkbox, "__type__": "update"}

    refresh_button.click(
        fn=change_choices,
        inputs=[],
        outputs=[model_file, index_file, audio],
    )
    audio.change(
        fn=output_path_fn,
        inputs=[audio],
        outputs=[output_path],
    )
    upload_audio.upload(
        fn=save_to_wav2,
        inputs=[upload_audio],
        outputs=[audio, output_path],
    )
    upload_audio.stop_recording(
        fn=save_to_wav,
        inputs=[upload_audio],
        outputs=[audio, output_path],
    )
    clear_outputs.click(
        fn=delete_outputs,
        inputs=[],
        outputs=[],
    )
    convert_button1.click(
        fn=run_infer_script,
        inputs=[
            pitch,
            filter_radius,
            index_rate,
            hop_length,
            f0method,
            audio,
            output_path,
            model_file,
            index_file,
            split_audio,
        ],
        outputs=[vc_output1, vc_output2],
    )
    convert_button2.click(
        fn=run_batch_infer_script,
        inputs=[
            pitch_batch,
            filter_radius_batch,
            index_rate_batch,
            hop_length_batch,
            f0method_batch,
            input_folder_batch,
            output_folder_batch,
            model_file,
            index_file,
        ],
        outputs=[vc_output3],
    )