Files
facefusion/facefusion/uis/components/face_selector.py
Henry Ruhs 6587d2def1 Next (#216)
* Simplify bbox access

* Code cleanup

* Simplify bbox access

* Move code to face helper

* Swap and paste back without insightface

* Swap and paste back without insightface

* Remove semaphore where possible

* Improve paste back performance

* Cosmetic changes

* Move the predictor to ONNX to avoid tensorflow, Use video ranges for prediction

* Make CI happy

* Move template and size to the options

* Fix different color on box

* Uniform model handling for predictor

* Uniform frame handling for predictor

* Pass kps direct to warp_face

* Fix urllib

* Analyse based on matches

* Analyse based on rate

* Fix CI

* ROCM and OpenVINO mapping for torch backends

* Fix the paste back speed

* Fix import

* Replace retinaface with yunet (#168)

* Remove insightface dependency

* Fix urllib

* Some fixes

* Analyse based on matches

* Analyse based on rate

* Fix CI

* Migrate to Yunet

* Something is off here

* We indeed need semaphore for yunet

* Normalize the normed_embedding

* Fix download of models

* Fix download of models

* Fix download of models

* Add score and improve affine_matrix

* Temp fix for bbox out of frame

* Temp fix for bbox out of frame

* ROCM and OpenVINO mapping for torch backends

* Normalize bbox

* Implement gender age

* Cosmetics on cli args

* Prevent face jumping

* Fix the paste back speed

* FIx import

* Introduce detection size

* Cosmetics on face analyser ARGS and globals

* Temp fix for shaking face

* Accurate event handling

* Accurate event handling

* Accurate event handling

* Set the reference_frame_number in face_selector component

* Simswap model (#171)

* Add simswap models

* Add ghost models

* Introduce normed template

* Conditional prepare and normalize for ghost

* Conditional prepare and normalize for ghost

* Get simswap working

* Get simswap working

* Fix refresh of swapper model

* Refine face selection and detection (#174)

* Refine face selection and detection

* Update README.md

* Fix some face analyser UI

* Fix some face analyser UI

* Introduce range handling for CLI arguments

* Introduce range handling for CLI arguments

* Fix some spacings

* Disable onnxruntime warnings

* Use cv2.blur over cv2.GaussianBlur for better performance

* Revert "Use cv2.blur over cv2.GaussianBlur for better performance"

This reverts commit bab666d6f9216a9f24faa84ead2d006b76f30159.

* Prepare universal face detection

* Prepare universal face detection part2

* Reimplement retinaface

* Introduce cached anchors creation

* Restore filtering to enhance performance

* Minor changes

* Minor changes

* More code but easier to understand

* Minor changes

* Rename predictor to content analyser

* Change detection/recognition to detector/recognizer

* Fix crop frame borders

* Fix spacing

* Allow normalize output without a source

* Improve conditional set face reference

* Update dependencies

* Add timeout for get_download_size

* Fix performance due disorder

* Move models to assets repository, Adjust namings

* Refactor face analyser

* Rename models once again

* Fix spacing

* Highres simswap (#192)

* Introduce highres simswap

* Fix simswap 256 color issue (#191)

* Fix simswap 256 color issue

* Update face_swapper.py

* Normalize models and host in our repo

* Normalize models and host in our repo

---------

Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>

* Rename face analyser direction to face analyser order

* Improve the UI for face selector

* Add best-worst, worst-best detector ordering

* Clear as needed and fix zero score bug

* Fix linter

* Improve startup time by multi thread remote download size

* Just some cosmetics

* Normalize swagger source input, Add blendface_256 (unfinished)

* New paste back (#195)

* add new paste_back (#194)

* add new paste_back

* Update face_helper.py

* Update face_helper.py

* add commandline arguments and gui

* fix conflict

* Update face_mask.py

* type fix

* Clean some wording and typing

---------

Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>

* Clean more names, use blur range approach

* Add blur padding range

* Change the padding order

* Fix yunet filename

* Introduce face debugger

* Use percent for mask padding

* Ignore this

* Ignore this

* Simplify debugger output

* implement blendface (#198)

* Clean up after the genius

* Add gpen_bfr_256

* Cosmetics

* Ignore face_mask_padding on face enhancer

* Update face_debugger.py (#202)

* Shrink debug_face() to a minimum

* Mark as 2.0.0 release

* remove unused (#204)

* Apply NMS (#205)

* Apply NMS

* Apply NMS part2

* Fix restoreformer url

* Add debugger cli and gui components (#206)

* Add debugger cli and gui components

* update

* Polishing the types

* Fix usage in README.md

* Update onnxruntime

* Support for webp

* Rename paste-back to face-mask

* Add license to README

* Add license to README

* Extend face selector mode by one

* Update utilities.py (#212)

* Stop inline camera on stream

* Minor webcam updates

* Gracefully start and stop webcam

* Rename capture to video_capture

* Make get webcam capture pure

* Check webcam to not be None

* Remove some is not None

* Use index 0 for webcam

* Remove memory lookup within progress bar

* Less progress bar updates

* Uniform progress bar

* Use classic progress bar

* Fix image and video validation

* Use different hash for cache

* Use best-worse order for webcam

* Normalize padding like CSS

* Update preview

* Fix max memory

* Move disclaimer and license to the docs

* Update wording in README

* Add LICENSE.md

* Fix argument in README

---------

Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
Co-authored-by: alex00ds <31631959+alex00ds@users.noreply.github.com>
2023-11-28 17:29:24 +01:00

166 lines
7.0 KiB
Python

from typing import List, Optional, Tuple, Any, Dict
import gradio
import facefusion.globals
import facefusion.choices
from facefusion import wording
from facefusion.face_cache import clear_faces_cache
from facefusion.vision import get_video_frame, read_static_image, normalize_frame_color
from facefusion.face_analyser import get_many_faces
from facefusion.face_reference import clear_face_reference
from facefusion.typing import Frame, FaceSelectorMode
from facefusion.utilities import is_image, is_video
from facefusion.uis.core import get_ui_component, register_ui_component
from facefusion.uis.typing import ComponentName
FACE_SELECTOR_MODE_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_SELECTOR_MODE_DROPDOWN
global REFERENCE_FACE_POSITION_GALLERY
global REFERENCE_FACE_DISTANCE_SLIDER
reference_face_gallery_args: Dict[str, Any] =\
{
'label': wording.get('reference_face_gallery_label'),
'object_fit': 'cover',
'columns': 8,
'allow_preview': False,
'visible': 'reference' in facefusion.globals.face_selector_mode
}
if is_image(facefusion.globals.target_path):
reference_frame = read_static_image(facefusion.globals.target_path)
reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
if is_video(facefusion.globals.target_path):
reference_frame = get_video_frame(facefusion.globals.target_path, facefusion.globals.reference_frame_number)
reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
FACE_SELECTOR_MODE_DROPDOWN = gradio.Dropdown(
label = wording.get('face_selector_mode_dropdown_label'),
choices = facefusion.choices.face_selector_modes,
value = facefusion.globals.face_selector_mode
)
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 = facefusion.globals.reference_face_distance,
step = facefusion.choices.reference_face_distance_range[1] - facefusion.choices.reference_face_distance_range[0],
minimum = facefusion.choices.reference_face_distance_range[0],
maximum = facefusion.choices.reference_face_distance_range[-1],
visible = 'reference' in facefusion.globals.face_selector_mode
)
register_ui_component('face_selector_mode_dropdown', FACE_SELECTOR_MODE_DROPDOWN)
register_ui_component('reference_face_position_gallery', REFERENCE_FACE_POSITION_GALLERY)
register_ui_component('reference_face_distance_slider', REFERENCE_FACE_DISTANCE_SLIDER)
def listen() -> None:
FACE_SELECTOR_MODE_DROPDOWN.select(update_face_selector_mode, inputs = FACE_SELECTOR_MODE_DROPDOWN, outputs = [ REFERENCE_FACE_POSITION_GALLERY, REFERENCE_FACE_DISTANCE_SLIDER ])
REFERENCE_FACE_POSITION_GALLERY.select(clear_and_update_reference_face_position)
REFERENCE_FACE_DISTANCE_SLIDER.change(update_reference_face_distance, inputs = REFERENCE_FACE_DISTANCE_SLIDER)
multi_component_names : List[ComponentName] =\
[
'target_image',
'target_video'
]
for component_name in multi_component_names:
component = get_ui_component(component_name)
if component:
for method in [ 'upload', 'change', 'clear' ]:
getattr(component, method)(update_reference_face_position)
getattr(component, method)(update_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
change_one_component_names : List[ComponentName] =\
[
'face_analyser_order_dropdown',
'face_analyser_age_dropdown',
'face_analyser_gender_dropdown'
]
for component_name in change_one_component_names:
component = get_ui_component(component_name)
if component:
component.change(update_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
change_two_component_names : List[ComponentName] =\
[
'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_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
preview_frame_slider = get_ui_component('preview_frame_slider')
if preview_frame_slider:
preview_frame_slider.change(update_reference_frame_number, inputs = preview_frame_slider)
preview_frame_slider.release(update_reference_position_gallery, outputs = REFERENCE_FACE_POSITION_GALLERY)
def update_face_selector_mode(face_selector_mode : FaceSelectorMode) -> Tuple[gradio.Gallery, gradio.Slider]:
if face_selector_mode == 'reference':
facefusion.globals.face_selector_mode = face_selector_mode
return gradio.Gallery(visible = True), gradio.Slider(visible = True)
if face_selector_mode == 'one':
facefusion.globals.face_selector_mode = face_selector_mode
return gradio.Gallery(visible = False), gradio.Slider(visible = False)
if face_selector_mode == 'many':
facefusion.globals.face_selector_mode = face_selector_mode
return gradio.Gallery(visible = False), gradio.Slider(visible = False)
def clear_and_update_reference_face_position(event : gradio.SelectData) -> gradio.Gallery:
clear_face_reference()
clear_faces_cache()
update_reference_face_position(event.index)
return update_reference_position_gallery()
def update_reference_face_position(reference_face_position : int = 0) -> None:
facefusion.globals.reference_face_position = reference_face_position
def update_reference_face_distance(reference_face_distance : float) -> None:
facefusion.globals.reference_face_distance = reference_face_distance
def update_reference_frame_number(reference_frame_number : int) -> None:
facefusion.globals.reference_frame_number = reference_frame_number
def clear_and_update_reference_position_gallery() -> gradio.Gallery:
clear_face_reference()
clear_faces_cache()
return update_reference_position_gallery()
def update_reference_position_gallery() -> gradio.Gallery:
gallery_frames = []
if is_image(facefusion.globals.target_path):
reference_frame = read_static_image(facefusion.globals.target_path)
gallery_frames = extract_gallery_frames(reference_frame)
if is_video(facefusion.globals.target_path):
reference_frame = get_video_frame(facefusion.globals.target_path, facefusion.globals.reference_frame_number)
gallery_frames = extract_gallery_frames(reference_frame)
if gallery_frames:
return gradio.Gallery(value = gallery_frames)
return gradio.Gallery(value = None)
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_frame = normalize_frame_color(crop_frame)
crop_frames.append(crop_frame)
return crop_frames