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from typing import List, Optional, Tuple, Any, Dict
from time import sleep
import cv2
import gradio
import DeepFakeAI.choices
import DeepFakeAI.globals
from DeepFakeAI import wording
from DeepFakeAI.capturer import get_video_frame
from DeepFakeAI.face_analyser import get_many_faces
from DeepFakeAI.face_reference import clear_face_reference
from DeepFakeAI.typing import Frame, FaceRecognition
from DeepFakeAI.uis import core as ui
from DeepFakeAI.uis.typing import ComponentName, Update
from DeepFakeAI.utilities import is_image, is_video
FACE_RECOGNITION_DROPDOWN : Optional[gradio.Dropdown] = None
REFERENCE_FACE_POSITION_GALLERY : Optional[gradio.Gallery] = None
REFERENCE_FACE_DISTANCE_SLIDER : Optional[gradio.Slider] = None
def render() -> None:
global FACE_RECOGNITION_DROPDOWN
global REFERENCE_FACE_POSITION_GALLERY
global REFERENCE_FACE_DISTANCE_SLIDER
with gradio.Box():
reference_face_gallery_args: Dict[str, Any] = {
'label': wording.get('reference_face_gallery_label'),
'height': 120,
'object_fit': 'cover',
'columns': 10,
'allow_preview': False,
'visible': 'reference' in DeepFakeAI.globals.face_recognition
}
if is_image(DeepFakeAI.globals.target_path):
reference_frame = cv2.imread(DeepFakeAI.globals.target_path)
reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
if is_video(DeepFakeAI.globals.target_path):
reference_frame = get_video_frame(DeepFakeAI.globals.target_path, DeepFakeAI.globals.reference_frame_number)
reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
FACE_RECOGNITION_DROPDOWN = gradio.Dropdown(
label = wording.get('face_recognition_dropdown_label'),
choices = DeepFakeAI.choices.face_recognition,
value = DeepFakeAI.globals.face_recognition
)
REFERENCE_FACE_POSITION_GALLERY = gradio.Gallery(**reference_face_gallery_args)
REFERENCE_FACE_DISTANCE_SLIDER = gradio.Slider(
label = wording.get('reference_face_distance_slider_label'),
value = DeepFakeAI.globals.reference_face_distance,
maximum = 3,
step = 0.05,
visible = 'reference' in DeepFakeAI.globals.face_recognition
)
ui.register_component('face_recognition_dropdown', FACE_RECOGNITION_DROPDOWN)
ui.register_component('reference_face_position_gallery', REFERENCE_FACE_POSITION_GALLERY)
ui.register_component('reference_face_distance_slider', REFERENCE_FACE_DISTANCE_SLIDER)
def listen() -> None:
FACE_RECOGNITION_DROPDOWN.select(update_face_recognition, inputs = FACE_RECOGNITION_DROPDOWN, outputs = [ REFERENCE_FACE_POSITION_GALLERY, REFERENCE_FACE_DISTANCE_SLIDER ])
REFERENCE_FACE_POSITION_GALLERY.select(clear_and_update_face_reference_position)
REFERENCE_FACE_DISTANCE_SLIDER.change(update_reference_face_distance, inputs = REFERENCE_FACE_DISTANCE_SLIDER)
update_component_names : List[ComponentName] =\
[
'target_file',
'preview_frame_slider'
]
for component_name in update_component_names:
component = ui.get_component(component_name)
if component:
component.change(update_face_reference_position, outputs = REFERENCE_FACE_POSITION_GALLERY)
select_component_names : List[ComponentName] =\
[
'face_analyser_direction_dropdown',
'face_analyser_age_dropdown',
'face_analyser_gender_dropdown'
]
for component_name in select_component_names:
component = ui.get_component(component_name)
if component:
component.select(update_face_reference_position, outputs = REFERENCE_FACE_POSITION_GALLERY)
def update_face_recognition(face_recognition : FaceRecognition) -> Tuple[Update, Update]:
if face_recognition == 'reference':
DeepFakeAI.globals.face_recognition = face_recognition
return gradio.update(visible = True), gradio.update(visible = True)
if face_recognition == 'many':
DeepFakeAI.globals.face_recognition = face_recognition
return gradio.update(visible = False), gradio.update(visible = False)
def clear_and_update_face_reference_position(event: gradio.SelectData) -> Update:
clear_face_reference()
return update_face_reference_position(event.index)
def update_face_reference_position(reference_face_position : int = 0) -> Update:
sleep(0.2)
gallery_frames = []
DeepFakeAI.globals.reference_face_position = reference_face_position
if is_image(DeepFakeAI.globals.target_path):
reference_frame = cv2.imread(DeepFakeAI.globals.target_path)
gallery_frames = extract_gallery_frames(reference_frame)
if is_video(DeepFakeAI.globals.target_path):
reference_frame = get_video_frame(DeepFakeAI.globals.target_path, DeepFakeAI.globals.reference_frame_number)
gallery_frames = extract_gallery_frames(reference_frame)
if gallery_frames:
return gradio.update(value = gallery_frames)
return gradio.update(value = None)
def update_reference_face_distance(reference_face_distance : float) -> Update:
DeepFakeAI.globals.reference_face_distance = reference_face_distance
return gradio.update(value = reference_face_distance)
def extract_gallery_frames(reference_frame : Frame) -> List[Frame]:
crop_frames = []
faces = get_many_faces(reference_frame)
for face in faces:
start_x, start_y, end_x, end_y = map(int, face['bbox'])
padding_x = int((end_x - start_x) * 0.25)
padding_y = int((end_y - start_y) * 0.25)
start_x = max(0, start_x - padding_x)
start_y = max(0, start_y - padding_y)
end_x = max(0, end_x + padding_x)
end_y = max(0, end_y + padding_y)
crop_frame = reference_frame[start_y:end_y, start_x:end_x]
crop_frames.append(ui.normalize_frame(crop_frame))
return crop_frames
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