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import gradio
from DeepFakeAI.uis.components import about, processors, execution, benchmark
from DeepFakeAI.utilities import conditional_download
def pre_check() -> bool:
conditional_download('.assets/examples',
[
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/source.jpg',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-240p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-360p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-540p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-720p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-1080p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-1440p.mp4',
'https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/examples/target-2160p.mp4'
])
return True
def render() -> gradio.Blocks:
with gradio.Blocks() as layout:
with gradio.Row():
with gradio.Column(scale = 2):
about.render()
processors.render()
execution.render()
with gradio.Column(scale= 5):
benchmark.render()
return layout
def listen() -> None:
processors.listen()
execution.listen()
benchmark.listen()
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