Move clear over to the UI (#825)
This commit is contained in:
Henry Ruhs
GitHub
parent
48440407e2
commit
b4f1a0e083
@ -101,7 +101,7 @@ def pre_check() -> bool:
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def common_pre_check() -> bool:
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modules =\
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common_modules =\
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[
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content_analyser,
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face_classifier,
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@ -112,7 +112,7 @@ def common_pre_check() -> bool:
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voice_extractor
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]
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return all(module.pre_check() for module in modules)
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return all(module.pre_check() for module in common_modules)
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def processors_pre_check() -> bool:
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@ -122,77 +122,23 @@ def processors_pre_check() -> bool:
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return True
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def conditional_process() -> ErrorCode:
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start_time = time()
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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if not processor_module.pre_process('output'):
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return 2
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conditional_append_reference_faces()
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if is_image(state_manager.get_item('target_path')):
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return process_image(start_time)
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if is_video(state_manager.get_item('target_path')):
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return process_video(start_time)
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return 0
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def conditional_append_reference_faces() -> None:
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if 'reference' in state_manager.get_item('face_selector_mode') and not get_reference_faces():
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source_frames = read_static_images(state_manager.get_item('source_paths'))
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source_faces = get_many_faces(source_frames)
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source_face = get_average_face(source_faces)
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if is_video(state_manager.get_item('target_path')):
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reference_frame = get_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
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else:
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reference_frame = read_image(state_manager.get_item('target_path'))
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reference_faces = sort_and_filter_faces(get_many_faces([ reference_frame ]))
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reference_face = get_one_face(reference_faces, state_manager.get_item('reference_face_position'))
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append_reference_face('origin', reference_face)
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if source_face and reference_face:
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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abstract_reference_frame = processor_module.get_reference_frame(source_face, reference_face, reference_frame)
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if numpy.any(abstract_reference_frame):
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abstract_reference_faces = sort_and_filter_faces(get_many_faces([ abstract_reference_frame ]))
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abstract_reference_face = get_one_face(abstract_reference_faces, state_manager.get_item('reference_face_position'))
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append_reference_face(processor_module.__name__, abstract_reference_face)
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def clear_model_sets() -> None:
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available_processors = list_directory('facefusion/processors/modules')
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def force_download() -> ErrorCode:
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common_modules =\
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[
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content_analyser,
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face_classifier,
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face_detector,
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face_landmarker,
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face_recognizer,
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face_masker,
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face_recognizer,
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voice_extractor
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]
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available_processors = list_directory('facefusion/processors/modules')
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processor_modules = get_processors_modules(available_processors)
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for module in common_modules + processor_modules:
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if hasattr(module, 'create_static_model_set'):
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module.create_static_model_set.cache_clear()
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def force_download() -> ErrorCode:
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available_processors = list_directory('facefusion/processors/modules')
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common_modules =\
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[
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content_analyser,
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face_classifier,
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face_detector,
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face_landmarker,
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face_recognizer,
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face_masker,
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voice_extractor
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]
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processor_modules = get_processors_modules(available_processors)
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for module in common_modules + processor_modules:
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if hasattr(module, 'create_model_set'):
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for model in module.create_model_set().values():
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for model in module.create_static_model_set().values():
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model_hashes = model.get('hashes')
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model_sources = model.get('sources')
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@ -306,19 +252,6 @@ def route_job_runner() -> ErrorCode:
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return 2
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def process_step(job_id : str, step_index : int, step_args : Args) -> bool:
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clear_reference_faces()
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step_total = job_manager.count_step_total(job_id)
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step_args.update(collect_job_args())
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apply_args(step_args, state_manager.set_item)
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logger.info(wording.get('processing_step').format(step_current = step_index + 1, step_total = step_total), __name__)
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if common_pre_check() and processors_pre_check():
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error_code = conditional_process()
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return error_code == 0
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return False
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def process_headless(args : Args) -> ErrorCode:
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job_id = job_helper.suggest_job_id('headless')
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step_args = reduce_step_args(args)
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@ -357,6 +290,54 @@ def process_batch(args : Args) -> ErrorCode:
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return 1
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def process_step(job_id : str, step_index : int, step_args : Args) -> bool:
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clear_reference_faces()
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step_total = job_manager.count_step_total(job_id)
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step_args.update(collect_job_args())
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apply_args(step_args, state_manager.set_item)
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logger.info(wording.get('processing_step').format(step_current = step_index + 1, step_total = step_total), __name__)
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if common_pre_check() and processors_pre_check():
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error_code = conditional_process()
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return error_code == 0
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return False
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def conditional_process() -> ErrorCode:
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start_time = time()
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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if not processor_module.pre_process('output'):
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return 2
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conditional_append_reference_faces()
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if is_image(state_manager.get_item('target_path')):
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return process_image(start_time)
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if is_video(state_manager.get_item('target_path')):
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return process_video(start_time)
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return 0
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def conditional_append_reference_faces() -> None:
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if 'reference' in state_manager.get_item('face_selector_mode') and not get_reference_faces():
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source_frames = read_static_images(state_manager.get_item('source_paths'))
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source_faces = get_many_faces(source_frames)
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source_face = get_average_face(source_faces)
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if is_video(state_manager.get_item('target_path')):
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reference_frame = get_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
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else:
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reference_frame = read_image(state_manager.get_item('target_path'))
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reference_faces = sort_and_filter_faces(get_many_faces([ reference_frame ]))
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reference_face = get_one_face(reference_faces, state_manager.get_item('reference_face_position'))
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append_reference_face('origin', reference_face)
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if source_face and reference_face:
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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abstract_reference_frame = processor_module.get_reference_frame(source_face, reference_face, reference_frame)
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if numpy.any(abstract_reference_frame):
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abstract_reference_faces = sort_and_filter_faces(get_many_faces([ abstract_reference_frame ]))
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abstract_reference_face = get_one_face(abstract_reference_faces, state_manager.get_item('reference_face_position'))
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append_reference_face(processor_module.__name__, abstract_reference_face)
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def process_image(start_time : float) -> ErrorCode:
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if analyse_image(state_manager.get_item('target_path')):
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return 3
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@ -53,12 +53,6 @@ def get_processors_modules(processors : List[str]) -> List[ModuleType]:
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return processor_modules
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def clear_processors_modules(processors : List[str]) -> None:
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for processor in processors:
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processor_module = load_processor_module(processor)
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processor_module.clear_inference_pool()
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def multi_process_frames(source_paths : List[str], temp_frame_paths : List[str], process_frames : ProcessFrames) -> None:
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queue_payloads = create_queue_payloads(temp_frame_paths)
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with tqdm(total = len(queue_payloads), desc = wording.get('processing'), unit = 'frame', ascii = ' =', disable = state_manager.get_item('log_level') in [ 'warn', 'error' ]) as progress:
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@ -2,9 +2,10 @@ from typing import List, Optional
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import gradio
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from facefusion import state_manager, wording
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from facefusion import content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, state_manager, voice_extractor, wording
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from facefusion.choices import download_provider_set
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from facefusion.core import clear_model_sets
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from facefusion.filesystem import list_directory
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from facefusion.processors.core import get_processors_modules
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from facefusion.typing import DownloadProviderKey
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DOWNLOAD_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
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@ -25,7 +26,23 @@ def listen() -> None:
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def update_download_providers(download_providers : List[DownloadProviderKey]) -> gradio.CheckboxGroup:
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clear_model_sets()
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common_modules =\
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[
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content_analyser,
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face_classifier,
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face_detector,
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face_landmarker,
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face_recognizer,
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face_masker,
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voice_extractor
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]
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available_processors = list_directory('facefusion/processors/modules')
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processor_modules = get_processors_modules(available_processors)
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for module in common_modules + processor_modules:
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if hasattr(module, 'create_static_model_set'):
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module.create_static_model_set.cache_clear()
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download_providers = download_providers or list(download_provider_set.keys())
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state_manager.set_item('download_providers', download_providers)
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return gradio.CheckboxGroup(value = state_manager.get_item('download_providers'))
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@ -4,7 +4,8 @@ import gradio
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from facefusion import content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, state_manager, voice_extractor, wording
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from facefusion.execution import get_execution_provider_set
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from facefusion.processors.core import clear_processors_modules
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from facefusion.filesystem import list_directory
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from facefusion.processors.core import get_processors_modules
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from facefusion.typing import ExecutionProviderKey
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EXECUTION_PROVIDERS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
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@ -25,14 +26,23 @@ def listen() -> None:
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def update_execution_providers(execution_providers : List[ExecutionProviderKey]) -> gradio.CheckboxGroup:
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content_analyser.clear_inference_pool()
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face_classifier.clear_inference_pool()
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face_detector.clear_inference_pool()
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face_landmarker.clear_inference_pool()
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face_masker.clear_inference_pool()
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face_recognizer.clear_inference_pool()
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voice_extractor.clear_inference_pool()
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clear_processors_modules(state_manager.get_item('processors'))
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common_modules =\
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[
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content_analyser,
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face_classifier,
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face_detector,
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face_landmarker,
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face_masker,
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face_recognizer,
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voice_extractor
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]
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available_processors = list_directory('facefusion/processors/modules')
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processor_modules = get_processors_modules(available_processors)
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for module in common_modules + processor_modules:
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if hasattr(module, 'clear_inference_pool'):
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module.clear_inference_pool()
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execution_providers = execution_providers or list(get_execution_provider_set())
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state_manager.set_item('execution_providers', execution_providers)
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return gradio.CheckboxGroup(value = state_manager.get_item('execution_providers'))
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@ -4,7 +4,7 @@ import gradio
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from facefusion import state_manager, wording
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from facefusion.filesystem import list_directory
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from facefusion.processors.core import clear_processors_modules, get_processors_modules
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from facefusion.processors.core import get_processors_modules
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from facefusion.uis.core import register_ui_component
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PROCESSORS_CHECKBOX_GROUP : Optional[gradio.CheckboxGroup] = None
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@ -26,12 +26,15 @@ def listen() -> None:
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def update_processors(processors : List[str]) -> gradio.CheckboxGroup:
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clear_processors_modules(state_manager.get_item('processors'))
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state_manager.set_item('processors', processors)
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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if hasattr(processor_module, 'clear_inference_pool'):
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processor_module.clear_inference_pool()
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for processor_module in get_processors_modules(processors):
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if not processor_module.pre_check():
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return gradio.CheckboxGroup()
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state_manager.set_item('processors', processors)
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return gradio.CheckboxGroup(value = state_manager.get_item('processors'), choices = sort_processors(state_manager.get_item('processors')))
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