import gradio as gr
import os
from constants import VOICE_METHODS, BARK_VOICES, EDGE_VOICES
import platform
from models.model import *
from tts.conversion import COQUI_LANGUAGES
import pytube
import os
import traceback
from pydub import AudioSegment
# from audio_enhance.functions import audio_enhance
import ast
import argparse
import glob
import pickle
import numpy as np
import pandas as pd
block_css = """
#notice_markdown {
font-size: 104%
}
#notice_markdown th {
display: none;
}
#notice_markdown td {
padding-top: 6px;
padding-bottom: 6px;
}
#leaderboard_markdown {
font-size: 104%
}
#leaderboard_markdown td {
padding-top: 6px;
padding-bottom: 6px;
}
#leaderboard_dataframe td {
line-height: 0.1em;
}
footer {
display:none !important
}
.image-container {
display: flex;
align-items: center;
padding: 1px;
}
.image-container img {
margin: 0 30px;
height: 20px;
max-height: 100%;
width: auto;
max-width: 20%;
}
"""
def model_hyperlink(model_name, link):
return f'{model_name}'
def load_leaderboard_table_csv(filename, add_hyperlink=True):
lines = open(filename).readlines()
heads = [v.strip() for v in lines[0].split(",")]
rows = []
for i in range(1, len(lines)):
row = [v.strip() for v in lines[i].split(",")]
for j in range(len(heads)):
item = {}
for h, v in zip(heads, row):
if h != "AI歌手名/AI Singer" and h != "歌手代表作或介绍链接" and h != "模型zip链接/Link to Model Zip File" and h != "模型贡献者/Model Contributor":
item[h] = int(v)
else:
item[h] = v
if add_hyperlink:
item["AI歌手名/AI Singer"] = model_hyperlink(item["AI歌手名/AI Singer"], item["歌手代表作或介绍链接"])
rows.append(item)
return rows
def get_arena_table(model_table_df):
# sort by rating
model_table_df = model_table_df.sort_values(by=["训练素材时长/Duration of Training Dataset(min)"], ascending=False)
values = []
for i in range(len(model_table_df)):
row = []
model_key = model_table_df.index[i]
model_name = model_table_df["AI歌手名/AI Singer"].values[model_key]
# rank
row.append(i + 1)
# model display name
row.append(model_name)
row.append(
model_table_df["模型zip链接/Link to Model Zip File"].values[model_key]
)
row.append(
model_table_df["训练素材时长/Duration of Training Dataset(min)"].values[model_key]
)
row.append(
model_table_df["训练epoch数/Epoch"].values[model_key]
)
row.append(
model_table_df["模型贡献者/Model Contributor"].values[model_key]
)
values.append(row)
return values
title_markdown = ("""
🌊💕🎶 滔滔AI，AI歌手模型开源社区
🌟 完全开源、完全免费、共建共享！全网AI歌手任您选择！
""")
pic_markdown = ("""
""")
data = load_leaderboard_table_csv("./OCRBench.csv")
model_table_df = pd.DataFrame(data)
text_size = gr.themes.sizes.text_lg
with gr.Blocks(theme=gr.themes.Base(text_size=text_size), css=block_css) as app:
gr.Markdown(title_markdown)
with gr.Tab("✨模型搜索及上传"):
gr.HTML("1. 搜索AI歌手模型
")
gr.Markdown("##### 点击[此链接](https://docs.google.com/spreadsheets/d/1owfUtQuLW9ReiIwg6U9UkkDmPOTkuNHf0OKQtWu1iaI/edit?gid=1227575351#gid=1227575351)，查看全网所有开源AI歌手模型，超9000个模型任您挑选 🥳")
search_name = gr.Textbox(placeholder="孙燕姿", label="请填写模型名称进行搜索", show_label=True)
# Salida
with gr.Row():
sarch_output = gr.Markdown(label="搜索结果")
btn_search_model = gr.Button(value="开始搜索吧💖", variant="primary")
btn_search_model.click(fn=search_model, inputs=[search_name], outputs=[sarch_output])
gr.HTML("2. 上传AI歌手模型至社区
")
gr.HTML("上传完成后您立即可以搜索到您上传的模型
")
post_name = gr.Textbox(placeholder="滔滔歌姬", label="请填写模型名称", show_label=True)
post_model_url = gr.Textbox(placeholder="https://huggingface.co/kevinwang676/RVC-models/resolve/main/talktalkgirl.zip", label="模型链接", info="1.推荐使用Hugging Face存放模型 2.复制Hugging Face模型链接后，需要将链接中的blob四个字母替换成resolve，使模型可以通过链接直接下载", show_label=True)
post_creator = gr.Textbox(placeholder="滔滔AI", label="模型贡献者", info="可填写您的昵称或任何有趣的ID", show_label=True)
post_version = gr.Dropdown(choices=["RVC v1", "RVC v2"], value="RVC v2", label="RVC模型版本", show_label=True)
# Salida
with gr.Row():
post_output = gr.Markdown(label="模型上传状态")
btn_post_model = gr.Button(value="开始上传吧💕", variant="primary")
btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
with gr.Tab("🍻滔滔AI精选模型"):
arena_table_vals = get_arena_table(model_table_df)
md = """
AI翻唱🎶：您可以在社区中复制您喜欢的AI歌手的“模型zip链接”，之后就可以在“🌟重磅首发 - AI歌手全明星💕”页面中通过粘贴zip链接来使用您喜欢的AI歌手模型啦！\n
[手机端📱](https://g-app-center-40055665-0593-xqmmjg6.openxlab.space)查看 滔滔AI精选模型
"""
gr.Markdown(md, elem_id="leaderboard_markdown")
gr.Dataframe(
headers=[
"排序",
"AI歌手名/AI Singer",
"模型zip链接/Link to Model Zip File",
"训练素材时长/Duration of Training Dataset(min)",
"训练epoch数/Epoch",
"模型贡献者/Model Contributor",
],
datatype=[
"str",
"markdown",
"str",
"number",
"number",
"str",
],
value=arena_table_vals,
elem_id="arena_leaderboard_dataframe",
height=800,
column_widths=[50, 100, 205, 95, 95, 95],
wrap=True,
)
gr.Markdown(pic_markdown)
gr.Markdown("###### 注意❗：请不要生成会对个人以及组织造成侵害的内容，此程序仅供科研、学习及个人娱乐使用。请自觉合规使用此程序，程序开发者不负有任何责任。")
gr.HTML('''
''')
app.queue(max_size=40, api_open=False)
app.launch(max_threads=400, show_error=True)