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import gradio as gr
import torch
from modules.webui.webui_utils import (
get_speakers,
get_styles,
load_spk_info,
refine_text,
tts_generate,
)
from modules.webui import webui_config
from modules.webui.examples import example_texts
from modules import config
default_text_content = """
chat T T S 是一款强大的对话式文本转语音模型。它有中英混读和多说话人的能力。
""".strip()
def create_tts_interface():
speakers = get_speakers()
def get_speaker_show_name(spk):
if spk.gender == "*" or spk.gender == "":
return spk.name
return f"{spk.gender} : {spk.name}"
speaker_names = ["*random"] + [
get_speaker_show_name(speaker) for speaker in speakers
]
speaker_names.sort(key=lambda x: x.startswith("*") and "-1" or x)
styles = ["*auto"] + [s.get("name") for s in get_styles()]
history = []
with gr.Row():
with gr.Column(scale=1):
with gr.Group():
gr.Markdown("🎛️Sampling")
temperature_input = gr.Slider(
0.01, 2.0, value=0.3, step=0.01, label="Temperature"
)
top_p_input = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Top P")
top_k_input = gr.Slider(1, 50, value=20, step=1, label="Top K")
batch_size_input = gr.Slider(
1,
webui_config.max_batch_size,
value=4,
step=1,
label="Batch Size",
)
with gr.Row():
with gr.Group():
gr.Markdown("🎭Style")
gr.Markdown("- 后缀为 `_p` 表示带prompt，效果更强但是影响质量")
style_input_dropdown = gr.Dropdown(
choices=styles,
# label="Choose Style",
interactive=True,
show_label=False,
value="*auto",
)
with gr.Row():
with gr.Group():
gr.Markdown("🗣️Speaker")
with gr.Tabs():
with gr.Tab(label="Pick"):
spk_input_text = gr.Textbox(
label="Speaker (Text or Seed)",
value="female2",
show_label=False,
)
spk_input_dropdown = gr.Dropdown(
choices=speaker_names,
# label="Choose Speaker",
interactive=True,
value="female : female2",
show_label=False,
)
spk_rand_button = gr.Button(
value="🎲",
# tooltip="Random Seed",
variant="secondary",
)
spk_input_dropdown.change(
fn=lambda x: x.startswith("*")
and "-1"
or x.split(":")[-1].strip(),
inputs=[spk_input_dropdown],
outputs=[spk_input_text],
)
spk_rand_button.click(
lambda x: str(torch.randint(0, 2**32 - 1, (1,)).item()),
inputs=[spk_input_text],
outputs=[spk_input_text],
)
with gr.Tab(label="Upload"):
spk_file_upload = gr.File(label="Speaker (Upload)")
gr.Markdown("📝Speaker info")
infos = gr.Markdown("empty")
spk_file_upload.change(
fn=load_spk_info,
inputs=[spk_file_upload],
outputs=[infos],
),
with gr.Group():
gr.Markdown("💃Inference Seed")
infer_seed_input = gr.Number(
value=42,
label="Inference Seed",
show_label=False,
minimum=-1,
maximum=2**32 - 1,
)
infer_seed_rand_button = gr.Button(
value="🎲",
# tooltip="Random Seed",
variant="secondary",
)
# 感觉这个没必要设置...
use_decoder_input = gr.Checkbox(
value=True, label="Use Decoder", visible=False
)
infer_seed_rand_button.click(
lambda x: int(torch.randint(0, 2**32 - 1, (1,)).item()),
inputs=[infer_seed_input],
outputs=[infer_seed_input],
)
with gr.Column(scale=4):
with gr.Group():
input_title = gr.Markdown(
"📝Text Input",
elem_id="input-title",
)
gr.Markdown(f"- 字数限制{webui_config.tts_max:,}字，超过部分截断")
gr.Markdown("- 如果尾字吞字不读，可以试试结尾加上 `[lbreak]`")
gr.Markdown(
"- If the input text is all in English, it is recommended to check disable_normalize"
)
text_input = gr.Textbox(
show_label=False,
label="Text to Speech",
lines=10,
placeholder="输入文本或选择示例",
elem_id="text-input",
value=default_text_content,
)
# TODO 字数统计，其实实现很好写，但是就是会触发loading...并且还要和后端交互...
# text_input.change(
# fn=lambda x: (
# f"📝Text Input ({len(x)} char)"
# if x
# else (
# "📝Text Input (0 char)"
# if not x
# else "📝Text Input (0 char)"
# )
# ),
# inputs=[text_input],
# outputs=[input_title],
# )
with gr.Row():
contorl_tokens = [
"[laugh]",
"[uv_break]",
"[v_break]",
"[lbreak]",
]
for tk in contorl_tokens:
t_btn = gr.Button(tk)
t_btn.click(
lambda text, tk=tk: text + " " + tk,
inputs=[text_input],
outputs=[text_input],
)
with gr.Group():
gr.Markdown("🎄Examples")
sample_dropdown = gr.Dropdown(
choices=[sample["text"] for sample in example_texts],
show_label=False,
value=None,
interactive=True,
)
sample_dropdown.change(
fn=lambda x: x,
inputs=[sample_dropdown],
outputs=[text_input],
)
with gr.Group():
gr.Markdown("🎨Output")
tts_output = gr.Audio(label="Generated Audio", format="mp3")
with gr.Column(scale=1):
with gr.Group():
gr.Markdown("🎶Refiner")
refine_prompt_input = gr.Textbox(
label="Refine Prompt",
value="[oral_2][laugh_0][break_6]",
)
refine_button = gr.Button("✍️Refine Text")
with gr.Group():
gr.Markdown("🔧Prompt engineering")
prompt1_input = gr.Textbox(label="Prompt 1")
prompt2_input = gr.Textbox(label="Prompt 2")
prefix_input = gr.Textbox(label="Prefix")
prompt_audio = gr.File(
label="prompt_audio", visible=webui_config.experimental
)
with gr.Group():
gr.Markdown("🔊Generate")
disable_normalize_input = gr.Checkbox(
value=False, label="Disable Normalize"
)
with gr.Group():
gr.Markdown("💪🏼Enhance")
enable_enhance = gr.Checkbox(value=True, label="Enable Enhance")
enable_de_noise = gr.Checkbox(value=False, label="Enable De-noise")
tts_button = gr.Button(
"🔊Generate Audio",
variant="primary",
elem_classes="big-button",
)
refine_button.click(
refine_text,
inputs=[text_input, refine_prompt_input],
outputs=[text_input],
)
tts_button.click(
tts_generate,
inputs=[
text_input,
temperature_input,
top_p_input,
top_k_input,
spk_input_text,
infer_seed_input,
use_decoder_input,
prompt1_input,
prompt2_input,
prefix_input,
style_input_dropdown,
disable_normalize_input,
batch_size_input,
enable_enhance,
enable_de_noise,
spk_file_upload,
],
outputs=tts_output,
)
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