* 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>
166 lines
7.1 KiB
Python
166 lines
7.1 KiB
Python
from typing import List, Optional, Tuple, Any, Dict
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import gradio
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import facefusion.globals
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import facefusion.choices
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from facefusion import wording
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from facefusion.face_store import clear_static_faces, clear_reference_faces
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from facefusion.vision import get_video_frame, read_static_image, normalize_frame_color
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from facefusion.filesystem import is_image, is_video
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from facefusion.face_analyser import get_many_faces
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from facefusion.typing import VisionFrame, FaceSelectorMode
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from facefusion.uis.core import get_ui_component, register_ui_component
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from facefusion.uis.typing import ComponentName
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FACE_SELECTOR_MODE_DROPDOWN : Optional[gradio.Dropdown] = None
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REFERENCE_FACE_POSITION_GALLERY : Optional[gradio.Gallery] = None
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REFERENCE_FACE_DISTANCE_SLIDER : Optional[gradio.Slider] = None
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def render() -> None:
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global FACE_SELECTOR_MODE_DROPDOWN
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global REFERENCE_FACE_POSITION_GALLERY
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global REFERENCE_FACE_DISTANCE_SLIDER
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reference_face_gallery_args: Dict[str, Any] =\
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{
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'label': wording.get('uis.reference_face_gallery'),
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'object_fit': 'cover',
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'columns': 8,
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'allow_preview': False,
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'visible': 'reference' in facefusion.globals.face_selector_mode
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}
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if is_image(facefusion.globals.target_path):
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reference_frame = read_static_image(facefusion.globals.target_path)
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reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
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if is_video(facefusion.globals.target_path):
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reference_frame = get_video_frame(facefusion.globals.target_path, facefusion.globals.reference_frame_number)
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reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
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FACE_SELECTOR_MODE_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.face_selector_mode_dropdown'),
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choices = facefusion.choices.face_selector_modes,
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value = facefusion.globals.face_selector_mode
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)
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REFERENCE_FACE_POSITION_GALLERY = gradio.Gallery(**reference_face_gallery_args)
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REFERENCE_FACE_DISTANCE_SLIDER = gradio.Slider(
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label = wording.get('uis.reference_face_distance_slider'),
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value = facefusion.globals.reference_face_distance,
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step = facefusion.choices.reference_face_distance_range[1] - facefusion.choices.reference_face_distance_range[0],
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minimum = facefusion.choices.reference_face_distance_range[0],
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maximum = facefusion.choices.reference_face_distance_range[-1],
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visible = 'reference' in facefusion.globals.face_selector_mode
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)
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register_ui_component('face_selector_mode_dropdown', FACE_SELECTOR_MODE_DROPDOWN)
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register_ui_component('reference_face_position_gallery', REFERENCE_FACE_POSITION_GALLERY)
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register_ui_component('reference_face_distance_slider', REFERENCE_FACE_DISTANCE_SLIDER)
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def listen() -> None:
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FACE_SELECTOR_MODE_DROPDOWN.change(update_face_selector_mode, inputs = FACE_SELECTOR_MODE_DROPDOWN, outputs = [ REFERENCE_FACE_POSITION_GALLERY, REFERENCE_FACE_DISTANCE_SLIDER ])
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REFERENCE_FACE_POSITION_GALLERY.select(clear_and_update_reference_face_position)
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REFERENCE_FACE_DISTANCE_SLIDER.change(update_reference_face_distance, inputs = REFERENCE_FACE_DISTANCE_SLIDER)
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multi_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_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_reference_face_position)
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getattr(component, method)(update_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
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change_one_component_names : List[ComponentName] =\
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[
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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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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_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
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change_two_component_names : List[ComponentName] =\
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[
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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_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
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preview_frame_slider = get_ui_component('preview_frame_slider')
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if preview_frame_slider:
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preview_frame_slider.change(update_reference_frame_number, inputs = preview_frame_slider)
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preview_frame_slider.release(update_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
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def update_face_selector_mode(face_selector_mode : FaceSelectorMode) -> Tuple[gradio.Gallery, gradio.Slider]:
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if face_selector_mode == 'reference':
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facefusion.globals.face_selector_mode = face_selector_mode
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return gradio.Gallery(visible = True), gradio.Slider(visible = True)
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if face_selector_mode == 'one':
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facefusion.globals.face_selector_mode = face_selector_mode
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return gradio.Gallery(visible = False), gradio.Slider(visible = False)
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if face_selector_mode == 'many':
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facefusion.globals.face_selector_mode = face_selector_mode
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return gradio.Gallery(visible = False), gradio.Slider(visible = False)
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def clear_and_update_reference_face_position(event : gradio.SelectData) -> gradio.Gallery:
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clear_reference_faces()
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clear_static_faces()
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update_reference_face_position(event.index)
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return update_reference_position_gallery()
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def update_reference_face_position(reference_face_position : int = 0) -> None:
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facefusion.globals.reference_face_position = reference_face_position
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def update_reference_face_distance(reference_face_distance : float) -> None:
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facefusion.globals.reference_face_distance = reference_face_distance
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def update_reference_frame_number(reference_frame_number : int) -> None:
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facefusion.globals.reference_frame_number = reference_frame_number
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def clear_and_update_reference_position_gallery() -> gradio.Gallery:
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clear_reference_faces()
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clear_static_faces()
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return update_reference_position_gallery()
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def update_reference_position_gallery() -> gradio.Gallery:
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gallery_vision_frames = []
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if is_image(facefusion.globals.target_path):
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temp_vision_frame = read_static_image(facefusion.globals.target_path)
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gallery_vision_frames = extract_gallery_frames(temp_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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gallery_vision_frames = extract_gallery_frames(temp_vision_frame)
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if gallery_vision_frames:
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return gradio.Gallery(value = gallery_vision_frames)
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return gradio.Gallery(value = None)
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def extract_gallery_frames(temp_vision_frame : VisionFrame) -> List[VisionFrame]:
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gallery_vision_frames = []
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faces = get_many_faces(temp_vision_frame)
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for face in faces:
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start_x, start_y, end_x, end_y = map(int, face.bounding_box)
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padding_x = int((end_x - start_x) * 0.25)
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padding_y = int((end_y - start_y) * 0.25)
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start_x = max(0, start_x - padding_x)
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start_y = max(0, start_y - padding_y)
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end_x = max(0, end_x + padding_x)
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end_y = max(0, end_y + padding_y)
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crop_vision_frame = temp_vision_frame[start_y:end_y, start_x:end_x]
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crop_vision_frame = normalize_frame_color(crop_vision_frame)
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gallery_vision_frames.append(crop_vision_frame)
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return gallery_vision_frames
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