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from typing import Tuple, Optional
import gradio
import DeepFakeAI.globals
from DeepFakeAI import wording
from DeepFakeAI.core import limit_resources, conditional_process
from DeepFakeAI.uis.core import get_ui_component
from DeepFakeAI.normalizer import normalize_output_path
from DeepFakeAI.filesystem import is_image, is_video, clear_temp
OUTPUT_IMAGE : Optional[gradio.Image] = None
OUTPUT_VIDEO : Optional[gradio.Video] = None
OUTPUT_START_BUTTON : Optional[gradio.Button] = None
OUTPUT_CLEAR_BUTTON : Optional[gradio.Button] = None
def render() -> None:
global OUTPUT_IMAGE
global OUTPUT_VIDEO
global OUTPUT_START_BUTTON
global OUTPUT_CLEAR_BUTTON
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')
)
OUTPUT_START_BUTTON = gradio.Button(
value = wording.get('start_button_label'),
variant = 'primary',
size = 'sm'
)
OUTPUT_CLEAR_BUTTON = gradio.Button(
value = wording.get('clear_button_label'),
size = 'sm'
)
def listen() -> None:
output_path_textbox = get_ui_component('output_path_textbox')
if output_path_textbox:
OUTPUT_START_BUTTON.click(start, inputs = output_path_textbox, outputs = [ OUTPUT_IMAGE, OUTPUT_VIDEO ])
OUTPUT_CLEAR_BUTTON.click(clear, outputs = [ OUTPUT_IMAGE, OUTPUT_VIDEO ])
def start(output_path : str) -> Tuple[gradio.Image, gradio.Video]:
DeepFakeAI.globals.output_path = normalize_output_path(DeepFakeAI.globals.source_paths, DeepFakeAI.globals.target_path, output_path)
limit_resources()
conditional_process()
if is_image(DeepFakeAI.globals.output_path):
return gradio.Image(value = DeepFakeAI.globals.output_path, visible = True), gradio.Video(value = None, visible = False)
if is_video(DeepFakeAI.globals.output_path):
return gradio.Image(value = None, visible = False), gradio.Video(value = DeepFakeAI.globals.output_path, visible = True)
return gradio.Image(), gradio.Video()
def clear() -> Tuple[gradio.Image, gradio.Video]:
if DeepFakeAI.globals.target_path:
clear_temp(DeepFakeAI.globals.target_path)
return gradio.Image(value = None), gradio.Video(value = None)
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