vnyash
208 lines
8.8 KiB
Python
Executable File
208 lines
8.8 KiB
Python
Executable File
from typing import Any, Dict, Optional
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from time import sleep
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import cv2
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import gradio
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import numpy
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import deepfuze.globals
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from deepfuze import logger, wording
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from deepfuze.audio import get_audio_frame, create_empty_audio_frame
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from deepfuze.common_helper import get_first
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from deepfuze.core import conditional_append_reference_faces
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from deepfuze.face_analyser import get_average_face, clear_face_analyser
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from deepfuze.face_store import clear_static_faces, get_reference_faces, clear_reference_faces
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from deepfuze.typing import Face, FaceSet, AudioFrame, VisionFrame
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from deepfuze.vision import get_video_frame, count_video_frame_total, normalize_frame_color, resize_frame_resolution, read_static_image, read_static_images
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from deepfuze.filesystem import is_image, is_video, filter_audio_paths
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from deepfuze.content_analyser import analyse_frame
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from deepfuze.processors.frame.core import load_frame_processor_module
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from deepfuze.uis.core import get_ui_component, get_ui_components, register_ui_component
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PREVIEW_IMAGE : Optional[gradio.Image] = None
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PREVIEW_FRAME_SLIDER : Optional[gradio.Slider] = None
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def render() -> None:
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global PREVIEW_IMAGE
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global PREVIEW_FRAME_SLIDER
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preview_image_args : Dict[str, Any] =\
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{
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'label': wording.get('uis.preview_image'),
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'interactive': False
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}
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preview_frame_slider_args : Dict[str, Any] =\
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{
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'label': wording.get('uis.preview_frame_slider'),
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'step': 1,
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'minimum': 0,
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'maximum': 100,
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'visible': False
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}
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conditional_append_reference_faces()
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reference_faces = get_reference_faces() if 'reference' in deepfuze.globals.face_selector_mode else None
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source_frames = read_static_images(deepfuze.globals.source_paths)
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source_face = get_average_face(source_frames)
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source_audio_path = get_first(filter_audio_paths(deepfuze.globals.source_paths))
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source_audio_frame = create_empty_audio_frame()
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if source_audio_path and deepfuze.globals.output_video_fps and deepfuze.globals.reference_frame_number:
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temp_audio_frame = get_audio_frame(source_audio_path, deepfuze.globals.output_video_fps, deepfuze.globals.reference_frame_number)
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if numpy.any(temp_audio_frame):
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source_audio_frame = temp_audio_frame
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if is_image(deepfuze.globals.target_path):
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target_vision_frame = read_static_image(deepfuze.globals.target_path)
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preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, target_vision_frame)
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preview_image_args['value'] = normalize_frame_color(preview_vision_frame)
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if is_video(deepfuze.globals.target_path):
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temp_vision_frame = get_video_frame(deepfuze.globals.target_path, deepfuze.globals.reference_frame_number)
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preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, temp_vision_frame)
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preview_image_args['value'] = normalize_frame_color(preview_vision_frame)
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preview_image_args['visible'] = True
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preview_frame_slider_args['value'] = deepfuze.globals.reference_frame_number
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preview_frame_slider_args['maximum'] = count_video_frame_total(deepfuze.globals.target_path)
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preview_frame_slider_args['visible'] = True
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PREVIEW_IMAGE = gradio.Image(**preview_image_args)
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PREVIEW_FRAME_SLIDER = gradio.Slider(**preview_frame_slider_args)
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register_ui_component('preview_frame_slider', PREVIEW_FRAME_SLIDER)
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def listen() -> None:
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PREVIEW_FRAME_SLIDER.release(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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reference_face_position_gallery = get_ui_component('reference_face_position_gallery')
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if reference_face_position_gallery:
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reference_face_position_gallery.select(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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for ui_component in get_ui_components(
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[
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'source_audio',
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'source_image',
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'target_image',
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'target_video'
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]):
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for method in [ 'upload', 'change', 'clear' ]:
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getattr(ui_component, method)(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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for ui_component in get_ui_components(
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[
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'target_image',
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'target_video'
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]):
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for method in [ 'upload', 'change', 'clear' ]:
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getattr(ui_component, method)(update_preview_frame_slider, outputs = PREVIEW_FRAME_SLIDER)
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for ui_component in get_ui_components(
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[
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'face_debugger_items_checkbox_group',
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'frame_colorizer_size_dropdown',
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'face_selector_mode_dropdown',
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'face_mask_types_checkbox_group',
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'face_mask_region_checkbox_group',
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'face_analyser_order_dropdown',
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'face_analyser_age_dropdown',
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'face_analyser_gender_dropdown'
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]):
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ui_component.change(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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for ui_component in get_ui_components(
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[
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'face_enhancer_blend_slider',
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'frame_colorizer_blend_slider',
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'frame_enhancer_blend_slider',
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'trim_frame_start_slider',
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'trim_frame_end_slider',
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'reference_face_distance_slider',
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'face_mask_blur_slider',
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'face_mask_padding_top_slider',
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'face_mask_padding_bottom_slider',
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'face_mask_padding_left_slider',
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'face_mask_padding_right_slider',
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'output_video_fps_slider'
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]):
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ui_component.release(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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for ui_component in get_ui_components(
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[
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'frame_processors_checkbox_group',
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'face_enhancer_model_dropdown',
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'face_swapper_model_dropdown',
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'frame_colorizer_model_dropdown',
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'frame_enhancer_model_dropdown',
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'lip_syncer_model_dropdown',
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'face_detector_model_dropdown',
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'face_detector_size_dropdown'
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]):
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ui_component.change(clear_and_update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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for ui_component in get_ui_components(
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[
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'face_detector_score_slider',
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'face_landmarker_score_slider'
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]):
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ui_component.release(clear_and_update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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def clear_and_update_preview_image(frame_number : int = 0) -> gradio.Image:
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clear_face_analyser()
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clear_reference_faces()
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clear_static_faces()
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return update_preview_image(frame_number)
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def update_preview_image(frame_number : int = 0) -> gradio.Image:
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for frame_processor in deepfuze.globals.frame_processors:
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frame_processor_module = load_frame_processor_module(frame_processor)
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while not frame_processor_module.post_check():
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logger.disable()
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sleep(0.5)
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logger.enable()
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conditional_append_reference_faces()
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reference_faces = get_reference_faces() if 'reference' in deepfuze.globals.face_selector_mode else None
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source_frames = read_static_images(deepfuze.globals.source_paths)
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source_face = get_average_face(source_frames)
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source_audio_path = get_first(filter_audio_paths(deepfuze.globals.source_paths))
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source_audio_frame = create_empty_audio_frame()
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if source_audio_path and deepfuze.globals.output_video_fps and deepfuze.globals.reference_frame_number:
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reference_audio_frame_number = deepfuze.globals.reference_frame_number
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if deepfuze.globals.trim_frame_start:
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reference_audio_frame_number -= deepfuze.globals.trim_frame_start
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temp_audio_frame = get_audio_frame(source_audio_path, deepfuze.globals.output_video_fps, reference_audio_frame_number)
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if numpy.any(temp_audio_frame):
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source_audio_frame = temp_audio_frame
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if is_image(deepfuze.globals.target_path):
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target_vision_frame = read_static_image(deepfuze.globals.target_path)
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preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, target_vision_frame)
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preview_vision_frame = normalize_frame_color(preview_vision_frame)
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return gradio.Image(value = preview_vision_frame)
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if is_video(deepfuze.globals.target_path):
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temp_vision_frame = get_video_frame(deepfuze.globals.target_path, frame_number)
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preview_vision_frame = process_preview_frame(reference_faces, source_face, source_audio_frame, temp_vision_frame)
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preview_vision_frame = normalize_frame_color(preview_vision_frame)
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return gradio.Image(value = preview_vision_frame)
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return gradio.Image(value = None)
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def update_preview_frame_slider() -> gradio.Slider:
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if is_video(deepfuze.globals.target_path):
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video_frame_total = count_video_frame_total(deepfuze.globals.target_path)
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return gradio.Slider(maximum = video_frame_total, visible = True)
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return gradio.Slider(value = None, maximum = None, visible = False)
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def process_preview_frame(reference_faces : FaceSet, source_face : Face, source_audio_frame : AudioFrame, target_vision_frame : VisionFrame) -> VisionFrame:
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target_vision_frame = resize_frame_resolution(target_vision_frame, (640, 640))
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if analyse_frame(target_vision_frame):
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return cv2.GaussianBlur(target_vision_frame, (99, 99), 0)
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for frame_processor in deepfuze.globals.frame_processors:
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frame_processor_module = load_frame_processor_module(frame_processor)
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logger.disable()
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if frame_processor_module.pre_process('preview'):
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logger.enable()
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target_vision_frame = frame_processor_module.process_frame(
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{
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'reference_faces': reference_faces,
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'source_face': source_face,
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'source_audio_frame': source_audio_frame,
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'target_vision_frame': target_vision_frame
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})
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return target_vision_frame
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