* feat/yoloface (#334) * added yolov8 to face_detector (#323) * added yolov8 to face_detector * added yolov8 to face_detector * Initial cleanup and renaming * Update README * refactored detect_with_yoloface (#329) * refactored detect_with_yoloface * apply review * Change order again * Restore working code * modified code (#330) * refactored detect_with_yoloface * apply review * use temp_frame in detect_with_yoloface * reorder * modified * reorder models * Tiny cleanup --------- Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com> * include audio file functions (#336) * Add testing for audio handlers * Change order * Fix naming * Use correct typing in choices * Update help message for arguments, Notation based wording approach (#347) * Update help message for arguments, Notation based wording approach * Fix installer * Audio functions (#345) * Update ffmpeg.py * Create audio.py * Update ffmpeg.py * Update audio.py * Update audio.py * Update typing.py * Update ffmpeg.py * Update audio.py * Rename Frame to VisionFrame (#346) * Minor tidy up * Introduce audio testing * Add more todo for testing * Add more todo for testing * Fix indent * Enable venv on the fly * Enable venv on the fly * Revert venv on the fly * Revert venv on the fly * Force Gradio to shut up * Force Gradio to shut up * Clear temp before processing * Reduce terminal output * include audio file functions * Enforce output resolution on merge video * Minor cleanups * Add age and gender to face debugger items (#353) * Add age and gender to face debugger items * Rename like suggested in the code review * Fix the output framerate vs. time * Lip Sync (#356) * Cli implementation of wav2lip * - create get_first_item() - remove non gan wav2lip model - implement video memory strategy - implement get_reference_frame() - implement process_image() - rearrange crop_mask_list - implement test_cli * Simplify testing * Rename to lip syncer * Fix testing * Fix testing * Minor cleanup * Cuda 12 installer (#362) * Make cuda nightly (12) the default * Better keep legacy cuda just in case * Use CUDA and ROCM versions * Remove MacOS options from installer (CoreML include in default package) * Add lip-syncer support to source component * Add lip-syncer support to source component * Fix the check in the source component * Add target image check * Introduce more helpers to suite the lip-syncer needs * Downgrade onnxruntime as of buggy 1.17.0 release * Revert "Downgrade onnxruntime as of buggy 1.17.0 release" This reverts commit f4a7ae6824fed87f0be50906bbc7e2d61d00617b. * More testing and add todos * Fix the frame processor API to at least not throw errors * Introduce dict based frame processor inputs (#364) * Introduce dict based frame processor inputs * Forgot to adjust webcam * create path payloads (#365) * create index payload to paths for process_frames * rename to payload_paths * This code now is poetry * Fix the terminal output * Make lip-syncer work in the preview * Remove face debugger test for now * Reoder reference_faces, Fix testing * Use inswapper_128 on buggy onnxruntime 1.17.0 * Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0 * Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0 * Fix lip_syncer occluder & region mask issue * Fix preview once in case there was no output video fps * fix lip_syncer custom fps * remove unused import * Add 68 landmark functions (#367) * Add 68 landmark model * Add landmark to face object * Re-arrange and modify typing * Rename function * Rearrange * Rearrange * ignore type * ignore type * change type * ignore * name * Some cleanup * Some cleanup * Opps, I broke something * Feat/face analyser refactoring (#369) * Restructure face analyser and start TDD * YoloFace and Yunet testing are passing * Remove offset from yoloface detection * Cleanup code * Tiny fix * Fix get_many_faces() * Tiny fix (again) * Use 320x320 fallback for retinaface * Fix merging mashup * Upload wave2lip model * Upload 2dfan2 model and rename internal to face_predictor * Downgrade onnxruntime for most cases * Update for the face debugger to render landmark 68 * Try to make detect_face_landmark_68() and detect_gender_age() more uniform * Enable retinaface testing for 320x320 * Make detect_face_landmark_68() and detect_gender_age() as uniform as … (#370) * Make detect_face_landmark_68() and detect_gender_age() as uniform as possible * Revert landmark scale and translation * Make box-mask for lip-syncer adjustable * Add create_bbox_from_landmark() * Remove currently unused code * Feat/uniface (#375) * add uniface (#373) * Finalize UniFace implementation --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * My approach how todo it * edit * edit * replace vertical blur with gaussian * remove region mask * Rebase against next and restore method * Minor improvements * Minor improvements * rename & add forehead padding * Adjust and host uniface model * Use 2dfan4 model * Rename to face landmarker * Feat/replace bbox with bounding box (#380) * Add landmark 68 to 5 convertion * Add landmark 68 to 5 convertion * Keep 5, 5/68 and 68 landmarks * Replace kps with landmark * Replace bbox with bounding box * Reshape face_landmark5_list different * Make yoloface the default * Move convert_face_landmark_68_to_5 to face_helper * Minor spacing issue * Dynamic detector sizes according to model (#382) * Dynamic detector sizes according to model * Dynamic detector sizes according to model * Undo false commited files * Add lib syncer model to the UI * fix halo (#383) * Bump to 2.3.0 * Update README and wording * Update README and wording * Fix spacing * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix, Move mouth mask to face_masker.py * Apply _vision suffix * Apply _vision suffix * increase forehead padding --------- Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
197 lines
8.5 KiB
Python
Executable File
197 lines
8.5 KiB
Python
Executable File
from typing import Any, Dict, List, 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 facefusion.globals
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from facefusion import wording, logger
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from facefusion.audio import get_audio_frame
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from facefusion.common_helper import get_first
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from facefusion.core import conditional_append_reference_faces
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from facefusion.face_analyser import get_average_face, clear_face_analyser
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from facefusion.face_store import clear_static_faces, get_reference_faces, clear_reference_faces
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from facefusion.typing import Face, FaceSet, AudioFrame, VisionFrame
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from facefusion.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 facefusion.filesystem import is_image, is_video, filter_audio_paths
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from facefusion.content_analyser import analyse_frame
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from facefusion.processors.frame.core import load_frame_processor_module
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from facefusion.uis.typing import ComponentName
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from facefusion.uis.core import get_ui_component, 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 facefusion.globals.face_selector_mode else None
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source_frames = read_static_images(facefusion.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(facefusion.globals.source_paths))
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if source_audio_path and facefusion.globals.output_video_fps:
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source_audio_frame = get_audio_frame(source_audio_path, facefusion.globals.output_video_fps, facefusion.globals.reference_frame_number)
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else:
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source_audio_frame = None
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if is_image(facefusion.globals.target_path):
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target_vision_frame = read_static_image(facefusion.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(facefusion.globals.target_path):
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temp_vision_frame = get_video_frame(facefusion.globals.target_path, facefusion.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'] = facefusion.globals.reference_frame_number
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preview_frame_slider_args['maximum'] = count_video_frame_total(facefusion.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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multi_one_component_names : List[ComponentName] =\
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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 component_name in multi_one_component_names:
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component = get_ui_component(component_name)
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if component:
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for method in [ 'upload', 'change', 'clear' ]:
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getattr(component, method)(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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multi_two_component_names : List[ComponentName] =\
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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 component_name in multi_two_component_names:
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component = get_ui_component(component_name)
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if component:
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for method in [ 'upload', 'change', 'clear' ]:
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getattr(component, method)(update_preview_frame_slider, outputs = PREVIEW_FRAME_SLIDER)
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change_one_component_names : List[ComponentName] =\
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[
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'face_debugger_items_checkbox_group',
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'face_enhancer_blend_slider',
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'frame_enhancer_blend_slider',
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'face_selector_mode_dropdown',
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'reference_face_distance_slider',
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'face_mask_types_checkbox_group',
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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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'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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'output_video_fps_slider'
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]
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for component_name in change_one_component_names:
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component = get_ui_component(component_name)
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if component:
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component.change(update_preview_image, inputs = PREVIEW_FRAME_SLIDER, outputs = PREVIEW_IMAGE)
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change_two_component_names : List[ComponentName] =\
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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_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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'face_detector_score_slider'
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]
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for component_name in change_two_component_names:
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component = get_ui_component(component_name)
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if component:
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component.change(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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sleep(0.5)
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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 facefusion.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 facefusion.globals.face_selector_mode else None
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source_frames = read_static_images(facefusion.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(facefusion.globals.source_paths))
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if source_audio_path and facefusion.globals.output_video_fps:
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source_audio_frame = get_audio_frame(source_audio_path, facefusion.globals.output_video_fps, facefusion.globals.reference_frame_number)
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else:
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source_audio_frame = None
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if is_image(facefusion.globals.target_path):
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target_vision_frame = read_static_image(facefusion.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(facefusion.globals.target_path):
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temp_vision_frame = get_video_frame(facefusion.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(facefusion.globals.target_path):
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video_frame_total = count_video_frame_total(facefusion.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 facefusion.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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