decouple common modules from core

facefusion/core.py

@@ -5,7 +5,7 @@ import signal
 import sys
 from time import time
 
-from facefusion import benchmarker, cli_helper, content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, hash_helper, logger, state_manager, translator, voice_extractor
+from facefusion import benchmarker, cli_helper, content_analyser, hash_helper, logger, state_manager, translator
 from facefusion.args import apply_args, collect_job_args, reduce_job_args, reduce_step_args
 from facefusion.download import conditional_download_hashes, conditional_download_sources
 from facefusion.exit_helper import hard_exit, signal_exit
@@ -101,21 +101,10 @@ def pre_check() -> bool:
 
 
 def common_pre_check() -> bool:
-	common_modules =\
-	[
-		content_analyser,
-		face_classifier,
-		face_detector,
-		face_landmarker,
-		face_masker,
-		face_recognizer,
-		voice_extractor
-	]
-
 	content_analyser_content = inspect.getsource(content_analyser).encode()
 	content_analyser_hash = hash_helper.create_hash(content_analyser_content)
 
-	return all(module.pre_check() for module in common_modules) and content_analyser_hash == '05843613'
+	return content_analyser_hash == '05843613'
 
 
 def processors_pre_check() -> bool:
@@ -126,22 +115,19 @@ def processors_pre_check() -> bool:
 
 
 def force_download() -> ErrorCode:
-	common_modules =\
-	[
-		content_analyser,
-		face_classifier,
-		face_detector,
-		face_landmarker,
-		face_masker,
-		face_recognizer,
-		voice_extractor
-	]
+	download_scope = state_manager.get_item('download_scope')
 	available_processors = [ get_file_name(file_path) for file_path in resolve_file_paths('facefusion/processors/modules') ]
 	processor_modules = get_processors_modules(available_processors)
+	common_modules = []
+
+	for processor_module in processor_modules:
+		for common_module in processor_module.get_common_modules():
+			if common_module not in common_modules:
+				common_modules.append(common_module)
 
 	for module in common_modules + processor_modules:
 		if hasattr(module, 'create_static_model_set'):
-			for model in module.create_static_model_set(state_manager.get_item('download_scope')).values():
+			for model in module.create_static_model_set(download_scope).values():
 				model_hash_set = model.get('hashes')
 				model_source_set = model.get('sources')
 

facefusion/processors/core.py

@@ -12,6 +12,7 @@ PROCESSORS_METHODS =\
 	'clear_inference_pool',
 	'register_args',
 	'apply_args',
+	'get_common_modules',
 	'pre_check',
 	'pre_process',
 	'post_process',

facefusion/processors/modules/age_modifier/core.py

@@ -1,5 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
+from typing import List
 
 import cv2
 import numpy
@@ -133,10 +135,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('age_modifier_direction', args.get('age_modifier_direction'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -157,15 +167,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def modify_age(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/background_remover/core.py

@@ -1,5 +1,6 @@
 from argparse import ArgumentParser
 from functools import lru_cache, partial
+from types import ModuleType
 from typing import List, Tuple
 
 import cv2
@@ -507,10 +508,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('background_remover_despill_color', normalize_color(args.get('background_remover_despill_color')))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -531,10 +540,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def remove_background(temp_vision_frame : VisionFrame) -> Tuple[VisionFrame, Mask]:

facefusion/processors/modules/deep_swapper/core.py

@@ -1,6 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
-from typing import Tuple
+from types import ModuleType
+from typing import List, Tuple
 
 import cv2
 import numpy
@@ -286,10 +287,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('deep_swapper_morph', args.get('deep_swapper_morph'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	if model_hash_set and model_source_set:
 		return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 	return True
@@ -312,15 +321,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/expression_restorer/core.py

@@ -1,6 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
-from typing import Tuple
+from types import ModuleType
+from typing import List, Tuple
 
 import cv2
 import numpy
@@ -111,10 +112,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('expression_restorer_areas', args.get('expression_restorer_areas'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -138,15 +147,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def restore_expression(target_face : Face, target_vision_frame : VisionFrame, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/face_debugger/core.py

@@ -1,4 +1,6 @@
 from argparse import ArgumentParser
+from types import ModuleType
+from typing import List
 
 import cv2
 import numpy
@@ -38,7 +40,14 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_debugger_items', args.get('face_debugger_items'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
 	return True
 
 
@@ -59,13 +68,10 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def debug_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/face_editor/core.py

@@ -1,6 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
-from typing import Tuple
+from types import ModuleType
+from typing import List, Tuple
 
 import cv2
 import numpy
@@ -165,10 +166,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_editor_head_roll', args.get('face_editor_head_roll'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -189,15 +198,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def edit_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/face_enhancer/core.py

@@ -1,5 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
+from typing import List
 
 import numpy
 
@@ -304,10 +306,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_enhancer_weight', args.get('face_enhancer_weight'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -328,15 +338,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def enhance_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/face_swapper/core.py

@@ -1,5 +1,6 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
 from typing import List, Optional, Tuple
 
 import cv2
@@ -541,10 +542,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('face_swapper_weight', args.get('face_swapper_weight'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -580,16 +589,14 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		get_static_model_initializer.cache_clear()
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def swap_face(source_face : Face, target_face : Face, source_vision_frame : VisionFrame, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/frame_colorizer/core.py

@@ -1,5 +1,6 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
 from typing import List
 
 import cv2
@@ -198,10 +199,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('frame_colorizer_size', args.get('frame_colorizer_size'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -222,10 +231,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def colorize_frame(temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/frame_enhancer/core.py

@@ -1,5 +1,6 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
 from typing import List
 
 import cv2
@@ -591,10 +592,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('frame_enhancer_blend', args.get('frame_enhancer_blend'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -615,10 +624,13 @@ def post_process() -> None:
 	read_static_image.cache_clear()
 	read_static_video_frame.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def enhance_frame(temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/processors/modules/lip_syncer/core.py

@@ -1,5 +1,7 @@
 from argparse import ArgumentParser
 from functools import lru_cache
+from types import ModuleType
+from typing import List
 
 import cv2
 import numpy
@@ -142,10 +144,18 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('lip_syncer_weight', args.get('lip_syncer_weight'))
 
 
+def get_common_modules() -> List[ModuleType]:
+	return [ content_analyser, face_classifier, face_detector, face_landmarker, face_masker, face_recognizer, voice_extractor ]
+
+
 def pre_check() -> bool:
 	model_hash_set = get_model_options().get('hashes')
 	model_source_set = get_model_options().get('sources')
 
+	for common_module in get_common_modules():
+		if not common_module.pre_check():
+			return False
+
 	return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
 
 
@@ -161,16 +171,13 @@ def post_process() -> None:
 	read_static_video_frame.cache_clear()
 	read_static_voice.cache_clear()
 	video_manager.clear_video_pool()
+
 	if state_manager.get_item('video_memory_strategy') in [ 'strict', 'moderate' ]:
 		clear_inference_pool()
+
 	if state_manager.get_item('video_memory_strategy') == 'strict':
-		content_analyser.clear_inference_pool()
-		face_classifier.clear_inference_pool()
-		face_detector.clear_inference_pool()
-		face_landmarker.clear_inference_pool()
-		face_masker.clear_inference_pool()
-		face_recognizer.clear_inference_pool()
-		voice_extractor.clear_inference_pool()
+		for common_module in get_common_modules():
+			common_module.clear_inference_pool()
 
 
 def sync_lip(target_face : Face, source_voice_frame : AudioFrame, temp_vision_frame : VisionFrame) -> VisionFrame:

facefusion/uis/components/source.py

@@ -2,7 +2,7 @@ from typing import List, Optional, Tuple
 
 import gradio
 
-from facefusion import state_manager, translator
+from facefusion import state_manager, translator, voice_extractor
 from facefusion.common_helper import get_first
 from facefusion.filesystem import filter_audio_paths, filter_image_paths, has_audio, has_image
 from facefusion.uis.core import register_ui_component
@@ -55,6 +55,10 @@ def update(files : List[File]) -> Tuple[gradio.Audio, gradio.Image]:
 		source_audio_path = get_first(filter_audio_paths(file_names))
 		source_image_path = get_first(filter_image_paths(file_names))
 		state_manager.set_item('source_paths', file_names)
+
+		if has_source_audio:
+			voice_extractor.pre_check()
+
 		return gradio.Audio(value = source_audio_path, visible = has_source_audio), gradio.Image(value = source_image_path, visible = has_source_image)
 
 	state_manager.clear_item('source_paths')

facefusion/uis/layouts/default.py

@@ -1,10 +1,21 @@
 import gradio
 
+import facefusion.face_classifier
+import facefusion.face_detector
+import facefusion.face_landmarker
+import facefusion.face_masker
+import facefusion.face_recognizer
 from facefusion import state_manager
 from facefusion.uis.components import about, age_modifier_options, background_remover_options, common_options, deep_swapper_options, download, execution, execution_thread_count, expression_restorer_options, face_debugger_options, face_detector, face_editor_options, face_enhancer_options, face_landmarker, face_masker, face_selector, face_swapper_options, frame_colorizer_options, frame_enhancer_options, instant_runner, job_manager, job_runner, lip_syncer_options, memory, output, output_options, preview, preview_options, processors, source, target, temp_frame, terminal, trim_frame, ui_workflow, voice_extractor
 
 
 def pre_check() -> bool:
+	common_modules = [ facefusion.face_classifier, facefusion.face_detector, facefusion.face_landmarker, facefusion.face_masker, facefusion.face_recognizer ]
+
+	for common_module in common_modules:
+		if not common_module.pre_check():
+			return False
+
 	return True