Spaces:
Sleeping
Sleeping
File size: 6,455 Bytes
32b2aaa 627d3d7 bf13828 32b2aaa ae79826 32b2aaa bf13828 32b2aaa ae79826 32b2aaa bf13828 32b2aaa f83b1b7 32b2aaa |
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 |
import io
import gradio as gr
import torch
from modules.utils.hf import spaces
from modules.webui import webui_config, webui_utils
from modules.webui.webui_utils import get_speakers, tts_generate
from modules.speaker import speaker_mgr, Speaker
import tempfile
def spk_to_tensor(spk):
spk = spk.split(" : ")[1].strip() if " : " in spk else spk
if spk == "None" or spk == "":
return None
return speaker_mgr.get_speaker(spk).emb
def get_speaker_show_name(spk):
if spk.gender == "*" or spk.gender == "":
return spk.name
return f"{spk.gender} : {spk.name}"
def merge_spk(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
):
tensor_a = spk_to_tensor(spk_a)
tensor_b = spk_to_tensor(spk_b)
tensor_c = spk_to_tensor(spk_c)
tensor_d = spk_to_tensor(spk_d)
assert (
tensor_a is not None
or tensor_b is not None
or tensor_c is not None
or tensor_d is not None
), "At least one speaker should be selected"
merge_tensor = torch.zeros_like(
tensor_a
if tensor_a is not None
else (
tensor_b
if tensor_b is not None
else tensor_c if tensor_c is not None else tensor_d
)
)
total_weight = 0
if tensor_a is not None:
merge_tensor += spk_a_w * tensor_a
total_weight += spk_a_w
if tensor_b is not None:
merge_tensor += spk_b_w * tensor_b
total_weight += spk_b_w
if tensor_c is not None:
merge_tensor += spk_c_w * tensor_c
total_weight += spk_c_w
if tensor_d is not None:
merge_tensor += spk_d_w * tensor_d
total_weight += spk_d_w
if total_weight > 0:
merge_tensor /= total_weight
merged_spk = Speaker.from_tensor(merge_tensor)
merged_spk.name = "<MIX>"
return merged_spk
@torch.inference_mode()
@spaces.GPU
def merge_and_test_spk_voice(
spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w, test_text
):
merged_spk = merge_spk(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
)
return tts_generate(
spk=merged_spk,
text=test_text,
)
@torch.inference_mode()
@spaces.GPU
def merge_spk_to_file(
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
speaker_name,
speaker_gender,
speaker_desc,
):
merged_spk = merge_spk(
spk_a, spk_a_w, spk_b, spk_b_w, spk_c, spk_c_w, spk_d, spk_d_w
)
merged_spk.name = speaker_name
merged_spk.gender = speaker_gender
merged_spk.desc = speaker_desc
with tempfile.NamedTemporaryFile(delete=False, suffix=".pt") as tmp_file:
torch.save(merged_spk, tmp_file)
tmp_file_path = tmp_file.name
return tmp_file_path
# 显示 a b c d 四个选择框,选择一个或多个,然后可以试音,并导出
def create_speaker_merger():
def get_spk_choices():
speakers, speaker_names = webui_utils.get_speaker_names()
speaker_names = ["None"] + speaker_names
return speaker_names
gr.Markdown("SPEAKER_MERGER_GUIDE")
def spk_picker(label_tail: str):
with gr.Row():
spk_a = gr.Dropdown(
choices=get_spk_choices(), value="None", label=f"Speaker {label_tail}"
)
refresh_a_btn = gr.Button("🔄", variant="secondary")
def refresh_a():
speaker_mgr.refresh_speakers()
speaker_names = get_spk_choices()
return gr.update(choices=speaker_names)
refresh_a_btn.click(refresh_a, outputs=[spk_a])
spk_a_w = gr.Slider(
value=1,
minimum=0,
maximum=10,
step=0.1,
label=f"Weight {label_tail}",
)
return spk_a, spk_a_w
with gr.Row():
with gr.Column(scale=5):
with gr.Row():
with gr.Group():
spk_a, spk_a_w = spk_picker("A")
with gr.Group():
spk_b, spk_b_w = spk_picker("B")
with gr.Group():
spk_c, spk_c_w = spk_picker("C")
with gr.Group():
spk_d, spk_d_w = spk_picker("D")
with gr.Row():
with gr.Column(scale=3):
with gr.Group():
gr.Markdown("🎤Test voice")
with gr.Row():
test_voice_btn = gr.Button(
"Test Voice", variant="secondary"
)
with gr.Column(scale=4):
test_text = gr.Textbox(
label="Test Text",
placeholder="Please input test text",
value=webui_config.localization.DEFAULT_SPEAKER_MERAGE_TEXT,
)
output_audio = gr.Audio(
label="Output Audio", format="mp3"
)
with gr.Column(scale=1):
with gr.Group():
gr.Markdown("🗃️Save to file")
speaker_name = gr.Textbox(label="Name", value="forge_speaker_merged")
speaker_gender = gr.Textbox(label="Gender", value="*")
speaker_desc = gr.Textbox(label="Description", value="merged speaker")
save_btn = gr.Button("Save Speaker", variant="primary")
merged_spker = gr.File(
label="Merged Speaker", interactive=False, type="binary"
)
test_voice_btn.click(
merge_and_test_spk_voice,
inputs=[
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
test_text,
],
outputs=[output_audio],
)
save_btn.click(
merge_spk_to_file,
inputs=[
spk_a,
spk_a_w,
spk_b,
spk_b_w,
spk_c,
spk_c_w,
spk_d,
spk_d_w,
speaker_name,
speaker_gender,
speaker_desc,
],
outputs=[merged_spker],
)
|