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from typing import Tuple, Optional
import gradio
import DeepFakeAI.globals
from DeepFakeAI import wording
from DeepFakeAI.core import conditional_process
from DeepFakeAI.uis.typing import Update
from DeepFakeAI.utilities import is_image, is_video, normalize_output_path, clear_temp
OUTPUT_START_BUTTON : Optional[gradio.Button] = None
OUTPUT_CLEAR_BUTTON : Optional[gradio.Button] = None
OUTPUT_IMAGE : Optional[gradio.Image] = None
OUTPUT_VIDEO : Optional[gradio.Video] = None
def render() -> None:
global OUTPUT_START_BUTTON
global OUTPUT_CLEAR_BUTTON
global OUTPUT_IMAGE
global OUTPUT_VIDEO
with gradio.Row():
with gradio.Box():
OUTPUT_IMAGE = gradio.Image(
label = wording.get('output_image_or_video_label'),
visible = False
)
OUTPUT_VIDEO = gradio.Video(
label = wording.get('output_image_or_video_label')
)
with gradio.Row():
OUTPUT_START_BUTTON = gradio.Button(wording.get('start_button_label'))
OUTPUT_CLEAR_BUTTON = gradio.Button(wording.get('clear_button_label'))
def listen() -> None:
OUTPUT_START_BUTTON.click(update, outputs = [ OUTPUT_IMAGE, OUTPUT_VIDEO ])
OUTPUT_CLEAR_BUTTON.click(clear, outputs = [ OUTPUT_IMAGE, OUTPUT_VIDEO ])
def update() -> Tuple[Update, Update]:
DeepFakeAI.globals.output_path = normalize_output_path(DeepFakeAI.globals.source_path, DeepFakeAI.globals.target_path, '.')
if DeepFakeAI.globals.output_path:
conditional_process()
if is_image(DeepFakeAI.globals.output_path):
return gradio.update(value = DeepFakeAI.globals.output_path, visible = True), gradio.update(value = None, visible = False)
if is_video(DeepFakeAI.globals.output_path):
return gradio.update(value = None, visible = False), gradio.update(value = DeepFakeAI.globals.output_path, visible = True)
return gradio.update(value = None, visible = False), gradio.update(value = None, visible = False)
def clear() -> Tuple[Update, Update]:
if DeepFakeAI.globals.target_path:
clear_temp(DeepFakeAI.globals.target_path)
return gradio.update(value = None), gradio.update(value = None)
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