6e67d7bff6
* Update official url for cuda 12-2 wheels * Fix preview for audio to image * Prevent download loop when remote is unreachable * Prevent download loop when remote is unreachable * changes (#444) * Tidy up monkey patch * Use cpu core count for concurrency count * Dynamic concurrency_count for ideal Gradio performance * Conditional download face analyser models * Fix testing via pre_check() * Introduce checking to process manager for blocking the UI * Introduce checking to process manager for blocking the UI * Introduce checking to process manager for blocking the UI * Introduce checking to process manager for blocking the UI * Move the blocking while model download to the correct position * Remove unused imports --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
124 lines
6.3 KiB
Python
124 lines
6.3 KiB
Python
from typing import Optional, Dict, Any, Tuple
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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 face_analyser, wording
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from facefusion.typing import FaceAnalyserOrder, FaceAnalyserAge, FaceAnalyserGender, FaceDetectorModel
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from facefusion.uis.core import register_ui_component
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FACE_ANALYSER_ORDER_DROPDOWN : Optional[gradio.Dropdown] = None
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FACE_ANALYSER_AGE_DROPDOWN : Optional[gradio.Dropdown] = None
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FACE_ANALYSER_GENDER_DROPDOWN : Optional[gradio.Dropdown] = None
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FACE_DETECTOR_MODEL_DROPDOWN : Optional[gradio.Dropdown] = None
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FACE_DETECTOR_SIZE_DROPDOWN : Optional[gradio.Dropdown] = None
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FACE_DETECTOR_SCORE_SLIDER : Optional[gradio.Slider] = None
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FACE_LANDMARKER_SCORE_SLIDER : Optional[gradio.Slider] = None
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def render() -> None:
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global FACE_ANALYSER_ORDER_DROPDOWN
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global FACE_ANALYSER_AGE_DROPDOWN
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global FACE_ANALYSER_GENDER_DROPDOWN
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global FACE_DETECTOR_MODEL_DROPDOWN
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global FACE_DETECTOR_SIZE_DROPDOWN
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global FACE_DETECTOR_SCORE_SLIDER
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global FACE_LANDMARKER_SCORE_SLIDER
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face_detector_size_dropdown_args : Dict[str, Any] =\
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{
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'label': wording.get('uis.face_detector_size_dropdown'),
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'value': facefusion.globals.face_detector_size
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}
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if facefusion.globals.face_detector_size in facefusion.choices.face_detector_set[facefusion.globals.face_detector_model]:
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face_detector_size_dropdown_args['choices'] = facefusion.choices.face_detector_set[facefusion.globals.face_detector_model]
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with gradio.Row():
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FACE_ANALYSER_ORDER_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.face_analyser_order_dropdown'),
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choices = facefusion.choices.face_analyser_orders,
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value = facefusion.globals.face_analyser_order
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)
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FACE_ANALYSER_AGE_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.face_analyser_age_dropdown'),
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choices = [ 'none' ] + facefusion.choices.face_analyser_ages,
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value = facefusion.globals.face_analyser_age or 'none'
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)
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FACE_ANALYSER_GENDER_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.face_analyser_gender_dropdown'),
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choices = [ 'none' ] + facefusion.choices.face_analyser_genders,
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value = facefusion.globals.face_analyser_gender or 'none'
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)
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FACE_DETECTOR_MODEL_DROPDOWN = gradio.Dropdown(
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label = wording.get('uis.face_detector_model_dropdown'),
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choices = facefusion.choices.face_detector_set.keys(),
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value = facefusion.globals.face_detector_model
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)
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FACE_DETECTOR_SIZE_DROPDOWN = gradio.Dropdown(**face_detector_size_dropdown_args)
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with gradio.Row():
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FACE_DETECTOR_SCORE_SLIDER = gradio.Slider(
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label = wording.get('uis.face_detector_score_slider'),
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value = facefusion.globals.face_detector_score,
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step = facefusion.choices.face_detector_score_range[1] - facefusion.choices.face_detector_score_range[0],
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minimum = facefusion.choices.face_detector_score_range[0],
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maximum = facefusion.choices.face_detector_score_range[-1]
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)
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FACE_LANDMARKER_SCORE_SLIDER = gradio.Slider(
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label = wording.get('uis.face_landmarker_score_slider'),
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value = facefusion.globals.face_landmarker_score,
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step = facefusion.choices.face_landmarker_score_range[1] - facefusion.choices.face_landmarker_score_range[0],
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minimum = facefusion.choices.face_landmarker_score_range[0],
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maximum = facefusion.choices.face_landmarker_score_range[-1]
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)
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register_ui_component('face_analyser_order_dropdown', FACE_ANALYSER_ORDER_DROPDOWN)
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register_ui_component('face_analyser_age_dropdown', FACE_ANALYSER_AGE_DROPDOWN)
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register_ui_component('face_analyser_gender_dropdown', FACE_ANALYSER_GENDER_DROPDOWN)
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register_ui_component('face_detector_model_dropdown', FACE_DETECTOR_MODEL_DROPDOWN)
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register_ui_component('face_detector_size_dropdown', FACE_DETECTOR_SIZE_DROPDOWN)
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register_ui_component('face_detector_score_slider', FACE_DETECTOR_SCORE_SLIDER)
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register_ui_component('face_landmarker_score_slider', FACE_LANDMARKER_SCORE_SLIDER)
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def listen() -> None:
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FACE_ANALYSER_ORDER_DROPDOWN.change(update_face_analyser_order, inputs = FACE_ANALYSER_ORDER_DROPDOWN)
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FACE_ANALYSER_AGE_DROPDOWN.change(update_face_analyser_age, inputs = FACE_ANALYSER_AGE_DROPDOWN)
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FACE_ANALYSER_GENDER_DROPDOWN.change(update_face_analyser_gender, inputs = FACE_ANALYSER_GENDER_DROPDOWN)
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FACE_DETECTOR_MODEL_DROPDOWN.change(update_face_detector_model, inputs = FACE_DETECTOR_MODEL_DROPDOWN, outputs = [ FACE_DETECTOR_MODEL_DROPDOWN, FACE_DETECTOR_SIZE_DROPDOWN ])
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FACE_DETECTOR_SIZE_DROPDOWN.change(update_face_detector_size, inputs = FACE_DETECTOR_SIZE_DROPDOWN)
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FACE_DETECTOR_SCORE_SLIDER.release(update_face_detector_score, inputs = FACE_DETECTOR_SCORE_SLIDER)
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FACE_LANDMARKER_SCORE_SLIDER.release(update_face_landmarker_score, inputs = FACE_LANDMARKER_SCORE_SLIDER)
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def update_face_analyser_order(face_analyser_order : FaceAnalyserOrder) -> None:
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facefusion.globals.face_analyser_order = face_analyser_order if face_analyser_order != 'none' else None
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def update_face_analyser_age(face_analyser_age : FaceAnalyserAge) -> None:
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facefusion.globals.face_analyser_age = face_analyser_age if face_analyser_age != 'none' else None
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def update_face_analyser_gender(face_analyser_gender : FaceAnalyserGender) -> None:
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facefusion.globals.face_analyser_gender = face_analyser_gender if face_analyser_gender != 'none' else None
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def update_face_detector_model(face_detector_model : FaceDetectorModel) -> Tuple[gradio.Dropdown, gradio.Dropdown]:
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facefusion.globals.face_detector_model = face_detector_model
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update_face_detector_size('640x640')
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if face_analyser.pre_check():
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if facefusion.globals.face_detector_size in facefusion.choices.face_detector_set[face_detector_model]:
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return gradio.Dropdown(value = facefusion.globals.face_detector_model), gradio.Dropdown(value = facefusion.globals.face_detector_size, choices = facefusion.choices.face_detector_set[face_detector_model])
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return gradio.Dropdown(value = facefusion.globals.face_detector_model), gradio.Dropdown(value = facefusion.globals.face_detector_size, choices = [ facefusion.globals.face_detector_size ])
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return gradio.Dropdown(), gradio.Dropdown()
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def update_face_detector_size(face_detector_size : str) -> None:
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facefusion.globals.face_detector_size = face_detector_size
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def update_face_detector_score(face_detector_score : float) -> None:
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facefusion.globals.face_detector_score = face_detector_score
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def update_face_landmarker_score(face_landmarker_score : float) -> None:
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facefusion.globals.face_landmarker_score = face_landmarker_score
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