Linly / app_talk.py
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import os
import random
import gradio as gr
from src.cost_time import calculate_time
from configs import *
os.environ["GRADIO_TEMP_DIR"]= './temp'
description = """<p style="text-align: center; font-weight: bold;">
<span style="font-size: 28px;">Linly 智能对话系统 (Linly-Talker)</span>
<br>
<span style="font-size: 18px;" id="paper-info">
[<a href="https://zhuanlan.zhihu.com/p/671006998" target="_blank">知乎</a>]
[<a href="https://www.bilibili.com/video/BV1rN4y1a76x/" target="_blank">bilibili</a>]
[<a href="https://github.com/Kedreamix/Linly-Talker" target="_blank">GitHub</a>]
[<a herf="https://kedreamix.github.io/" target="_blank">个人主页</a>]
</span>
<br>
<span>Linly-Talker 是一款智能 AI 对话系统,结合了大型语言模型 (LLMs) 与视觉模型,是一种新颖的人工智能交互方式。</span>
</p>
"""
# 设定默认参数值,可修改
# source_image = r'example.png'
blink_every = True
size_of_image = 256
preprocess_type = 'crop'
facerender = 'facevid2vid'
enhancer = False
is_still_mode = False
exp_weight = 1
use_ref_video = False
ref_video = None
ref_info = 'pose'
use_idle_mode = False
length_of_audio = 5
@calculate_time
def TTS_response(text,
voice, rate, volume, pitch,
am, voc, lang, male,
tts_method = 'PaddleTTS', save_path = 'answer.wav'):
print(text, voice, rate, volume, pitch, am, voc, lang, male, tts_method, save_path)
if tts_method == 'Edge-TTS':
try:
edgetts.predict(text, voice, rate, volume, pitch , 'answer.wav', 'answer.vtt')
except:
os.system(f'edge-tts --text "{text}" --voice {voice} --write-media answer.wav')
return 'answer.wav'
elif tts_method == 'PaddleTTS':
paddletts.predict(text, am, voc, lang = lang, male=male, save_path = save_path)
return save_path
@calculate_time
def Talker_response(source_image, source_video, method = 'SadTalker', driven_audio = '', batch_size = 2):
# print(source_image, method , driven_audio, batch_size)
if source_video:
source_image = source_video
print(source_image, method , driven_audio, batch_size)
pose_style = random.randint(0, 45)
if method == 'SadTalker':
video = sadtalker.test2(source_image,
driven_audio,
preprocess_type,
is_still_mode,
enhancer,
batch_size,
size_of_image,
pose_style,
facerender,
exp_weight,
use_ref_video,
ref_video,
ref_info,
use_idle_mode,
length_of_audio,
blink_every,
fps=20)
elif method == 'Wav2Lip':
video = wav2lip.predict(source_image, driven_audio, batch_size)
elif method == 'ER-NeRF':
video = ernerf.predict(driven_audio)
else:
gr.Warning("不支持的方法:" + method)
return None
return video
def main():
with gr.Blocks(analytics_enabled=False, title = 'Linly-Talker') as inference:
gr.HTML(description)
with gr.Row(equal_height=False):
with gr.Column(variant='panel'):
with gr.Tabs():
with gr.Tab("图片人物"):
source_image = gr.Image(label='Source image', type = 'filepath')
with gr.Tab("视频人物"):
source_video = gr.Video(label="Source video")
with gr.Tabs():
input_audio = gr.Audio(sources=['upload', 'microphone'], type="filepath", label = '语音')
input_text = gr.Textbox(label="Input Text", lines=3)
with gr.Column():
tts_method = gr.Radio(["Edge-TTS", "PaddleTTS"], label="Text To Speech Method (Edge-TTS利用微软的TTS,PaddleSpeech是离线的TTS,不过第一次运行会自动下载模型)",
value = 'Edge-TTS')
with gr.Tabs("TTS Method"):
# with gr.Accordion("Advanced Settings(高级设置语音参数) ", open=False):
with gr.Tab("Edge-TTS"):
voice = gr.Dropdown(edgetts.SUPPORTED_VOICE,
value='zh-CN-XiaoxiaoNeural',
label="Voice")
rate = gr.Slider(minimum=-100,
maximum=100,
value=0,
step=1.0,
label='Rate')
volume = gr.Slider(minimum=0,
maximum=100,
value=100,
step=1,
label='Volume')
pitch = gr.Slider(minimum=-100,
maximum=100,
value=0,
step=1,
label='Pitch')
with gr.Tab("PaddleTTS"):
am = gr.Dropdown(["FastSpeech2"], label="声学模型选择", value = 'FastSpeech2')
voc = gr.Dropdown(["PWGan", "HifiGan"], label="声码器选择", value = 'PWGan')
lang = gr.Dropdown(["zh", "en", "mix", "canton"], label="语言选择", value = 'zh')
male = gr.Checkbox(label="男声(Male)", value=False)
with gr.Column(variant='panel'):
batch_size = gr.Slider(minimum=1,
maximum=10,
value=2,
step=1,
label='Talker Batch size')
button_text = gr.Button('语音生成')
button_text.click(fn=TTS_response,inputs=[input_text, voice, rate, volume, pitch, am, voc, lang, male, tts_method],
outputs=[input_audio])
with gr.Column(variant='panel'):
with gr.Tabs():
with gr.TabItem('数字人问答'):
method = gr.Radio(choices = ['SadTalker', 'Wav2Lip', 'ER-NeRF'], value = 'SadTalker', label = '模型选择')
gen_video = gr.Video(label="Generated video", format="mp4", scale=1, autoplay=True)
video_button = gr.Button("提交", variant='primary')
video_button.click(fn=Talker_response,inputs=[source_image, source_video, method, input_audio, batch_size] ,
outputs=[gen_video])
with gr.Row():
examples = [
[
'examples/source_image/full_body_2.png',
'应对压力最有效的方法是什么?',
],
[
'examples/source_image/full_body_1.png',
'如何进行时间管理?',
],
[
'examples/source_image/full3.png',
'为什么有些人选择使用纸质地图或寻求方向,而不是依赖GPS设备或智能手机应用程序?',
],
[
'examples/source_image/full4.jpeg',
'近日,苹果公司起诉高通公司,状告其未按照相关合约进行合作,高通方面尚未回应。这句话中“其”指的是谁?',
],
[
'examples/source_image/art_13.png',
'三年级同学种树80颗,四、五年级种的棵树比三年级种的2倍多14棵,三个年级共种树多少棵?',
],
[
'examples/source_image/art_5.png',
'撰写一篇交响乐音乐会评论,讨论乐团的表演和观众的整体体验。',
],
]
gr.Examples(examples=examples,
inputs=[
source_image,
input_text,
],
)
return inference
if __name__ == "__main__":
try:
from TFG import SadTalker
sadtalker = SadTalker(lazy_load=True)
except Exception as e:
print("SadTalker Error: ", e)
print("如果使用SadTalker,请先下载SadTalker模型")
try:
from TFG import Wav2Lip
wav2lip = Wav2Lip("checkpoints/wav2lip_gan.pth")
except Exception as e:
print("Wav2Lip Error: ", e)
print("如果使用Wav2Lip,请先下载Wav2Lip模型")
try:
from TFG import ERNeRF
ernerf = ERNeRF()
ernerf.init_model('checkpoints/Obama_ave.pth', 'checkpoints/Obama.json')
except Exception as e:
print("ERNeRF Error: ", e)
print("如果使用ERNeRF,请先下载ERNeRF模型")
try:
from TTS import EdgeTTS
edgetts = EdgeTTS()
except Exception as e:
print("EdgeTTS Error: ", e)
print("如果使用EdgeTTS,请先下载EdgeTTS模型")
try:
from TTS import PaddleTTS
paddletts = PaddleTTS()
except Exception as e:
print("PaddleTTS Error: ", e)
print("如果使用PaddleTTS,请先下载PaddleTTS模型")
gr.close_all()
demo = main()
demo.queue()
# demo.launch()
demo.launch(server_name=ip, # 本地端口localhost:127.0.0.1 全局端口转发:"0.0.0.0"
server_port=port,
# 似乎在Gradio4.0以上版本可以不使用证书也可以进行麦克风对话
ssl_certfile=ssl_certfile,
ssl_keyfile=ssl_keyfile,
ssl_verify=False,
debug=True)