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import io
import gradio as gr
import torch
from modules.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],
)
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