Inferencer's picture
Upload 66 files
e04e4d5 verified
from typing import Any, Dict, List, Optional
from time import sleep
import cv2
import gradio
import facefusion.globals
from facefusion import wording, logger
from facefusion.core import conditional_append_reference_faces
from facefusion.face_store import clear_static_faces, get_reference_faces, clear_reference_faces
from facefusion.typing import Frame, Face, FaceSet
from facefusion.vision import get_video_frame, count_video_frame_total, normalize_frame_color, resize_frame_resolution, read_static_image, read_static_images
from facefusion.filesystem import is_image, is_video
from facefusion.face_analyser import get_average_face, clear_face_analyser
from facefusion.content_analyser import analyse_frame
from facefusion.processors.frame.core import load_frame_processor_module
from facefusion.uis.typing import ComponentName
from facefusion.uis.core import get_ui_component, register_ui_component
PREVIEW_IMAGE : Optional[gradio.Image] = None
PREVIEW_FRAME_SLIDER : Optional[gradio.Slider] = None
def render() -> None:
global PREVIEW_IMAGE
global PREVIEW_FRAME_SLIDER
preview_image_args: Dict[str, Any] =\
{
'label': wording.get('preview_image_label'),
'interactive': False
}
preview_frame_slider_args: Dict[str, Any] =\
{
'label': wording.get('preview_frame_slider_label'),
'step': 1,
'minimum': 0,
'maximum': 100,
'visible': False
}
conditional_append_reference_faces()
source_frames = read_static_images(facefusion.globals.source_paths)
source_face = get_average_face(source_frames)
reference_faces = get_reference_faces() if 'reference' in facefusion.globals.face_selector_mode else None
if is_image(facefusion.globals.target_path):
target_frame = read_static_image(facefusion.globals.target_path)
preview_frame = process_preview_frame(source_face, reference_faces, target_frame)
preview_image_args['value'] = normalize_frame_color(preview_frame)
if is_video(facefusion.globals.target_path):
temp_frame = get_video_frame(facefusion.globals.target_path, facefusion.globals.reference_frame_number)
preview_frame = process_preview_frame(source_face, reference_faces, temp_frame)
preview_image_args['value'] = normalize_frame_color(preview_frame)
preview_image_args['visible'] = True
preview_frame_slider_args['value'] = facefusion.globals.reference_frame_number
preview_frame_slider_args['maximum'] = count_video_frame_total(facefusion.globals.target_path)
preview_frame_slider_args['visible'] = True
PREVIEW_IMAGE = gradio.Image(**preview_image_args)
PREVIEW_FRAME_SLIDER = gradio.Slider(**preview_frame_slider_args)
register_ui_component('preview_frame_slider', PREVIEW_FRAME_SLIDER)
def listen() -> None:
PREVIEW_FRAME_SLIDER.release(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
multi_one_component_names : List[ComponentName] =\
[
'source_image',
'target_image',
'target_video'
]
for component_name in multi_one_component_names:
component = get_ui_component(component_name)
if component:
for method in [ 'upload', 'change', 'clear' ]:
getattr(component, method)(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
multi_two_component_names : List[ComponentName] =\
[
'target_image',
'target_video'
]
for component_name in multi_two_component_names:
component = get_ui_component(component_name)
if component:
for method in [ 'upload', 'change', 'clear' ]:
getattr(component, method)(update_preview_frame_slider, outputs = PREVIEW_FRAME_SLIDER)
select_component_names : List[ComponentName] =\
[
'reference_face_position_gallery',
'face_analyser_order_dropdown',
'face_analyser_age_dropdown',
'face_analyser_gender_dropdown'
]
for component_name in select_component_names:
component = get_ui_component(component_name)
if component:
component.select(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
change_one_component_names : List[ComponentName] =\
[
'face_debugger_items_checkbox_group',
'face_enhancer_blend_slider',
'frame_enhancer_blend_slider',
'face_selector_mode_dropdown',
'reference_face_distance_slider',
'face_mask_types_checkbox_group',
'face_mask_blur_slider',
'face_mask_padding_top_slider',
'face_mask_padding_bottom_slider',
'face_mask_padding_left_slider',
'face_mask_padding_right_slider',
'face_mask_region_checkbox_group'
]
for component_name in change_one_component_names:
component = get_ui_component(component_name)
if component:
component.change(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
change_two_component_names : List[ComponentName] =\
[
'frame_processors_checkbox_group',
'face_enhancer_model_dropdown',
'face_swapper_model_dropdown',
'frame_enhancer_model_dropdown',
'face_detector_model_dropdown',
'face_detector_size_dropdown',
'face_detector_score_slider'
]
for component_name in change_two_component_names:
component = get_ui_component(component_name)
if component:
component.change(clear_and_update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
def clear_and_update_preview_image(frame_number : int = 0) -> gradio.Image:
clear_face_analyser()
clear_reference_faces()
clear_static_faces()
sleep(0.5)
return update_preview_image(frame_number)
def update_preview_image(frame_number : int = 0) -> gradio.Image:
for frame_processor in facefusion.globals.frame_processors:
frame_processor_module = load_frame_processor_module(frame_processor)
while not frame_processor_module.post_check():
logger.disable()
sleep(0.5)
logger.enable()
conditional_append_reference_faces()
source_frames = read_static_images(facefusion.globals.source_paths)
source_face = get_average_face(source_frames)
reference_faces = get_reference_faces() if 'reference' in facefusion.globals.face_selector_mode else None
if is_image(facefusion.globals.target_path):
target_frame = read_static_image(facefusion.globals.target_path)
preview_frame = process_preview_frame(source_face, reference_faces, target_frame)
preview_frame = normalize_frame_color(preview_frame)
return gradio.Image(value = preview_frame)
if is_video(facefusion.globals.target_path):
temp_frame = get_video_frame(facefusion.globals.target_path, frame_number)
preview_frame = process_preview_frame(source_face, reference_faces, temp_frame)
preview_frame = normalize_frame_color(preview_frame)
return gradio.Image(value = preview_frame)
return gradio.Image(value = None)
def update_preview_frame_slider() -> gradio.Slider:
if is_video(facefusion.globals.target_path):
video_frame_total = count_video_frame_total(facefusion.globals.target_path)
return gradio.Slider(maximum = video_frame_total, visible = True)
return gradio.Slider(value = None, maximum = None, visible = False)
def process_preview_frame(source_face : Face, reference_faces : FaceSet, temp_frame : Frame) -> Frame:
temp_frame = resize_frame_resolution(temp_frame, 640, 640)
if analyse_frame(temp_frame):
return cv2.GaussianBlur(temp_frame, (99, 99), 0)
for frame_processor in facefusion.globals.frame_processors:
frame_processor_module = load_frame_processor_module(frame_processor)
logger.disable()
if frame_processor_module.pre_process('preview'):
logger.enable()
temp_frame = frame_processor_module.process_frame(
source_face,
reference_faces,
temp_frame
)
return temp_frame