Introduce download scopes (#826)

* Introduce download scopes

* Limit download scopes to force-download command

facefusion.ini

@@ -103,6 +103,7 @@ execution_queue_count =
 
 [download]
 download_providers =
+download_scope =
 
 [memory]
 video_memory_strategy =

facefusion/args.py

@@ -120,6 +120,7 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
 	apply_state_item('execution_queue_count', args.get('execution_queue_count'))
 	# download
 	apply_state_item('download_providers', args.get('download_providers'))
+	apply_state_item('download_scope', args.get('download_scope'))
 	# memory
 	apply_state_item('video_memory_strategy', args.get('video_memory_strategy'))
 	apply_state_item('system_memory_limit', args.get('system_memory_limit'))

facefusion/choices.py

@@ -2,7 +2,7 @@ import logging
 from typing import List, Sequence
 
 from facefusion.common_helper import create_float_range, create_int_range
-from facefusion.typing import Angle, DownloadProviderSet, ExecutionProviderSet, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
+from facefusion.typing import Angle, DownloadProviderSet, DownloadScope, ExecutionProviderSet, FaceDetectorSet, FaceLandmarkerModel, FaceMaskRegion, FaceMaskType, FaceSelectorMode, FaceSelectorOrder, Gender, JobStatus, LogLevelSet, OutputAudioEncoder, OutputVideoEncoder, OutputVideoPreset, Race, Score, TempFrameFormat, UiWorkflow, VideoMemoryStrategy
 
 video_memory_strategies : List[VideoMemoryStrategy] = [ 'strict', 'moderate', 'tolerant' ]
 
@@ -43,6 +43,7 @@ download_provider_set : DownloadProviderSet =\
 	'github': 'https://github.com/facefusion/facefusion-assets/releases/download/{base_name}/{file_name}',
 	'huggingface': 'https://huggingface.co/facefusion/{base_name}/resolve/main/{file_name}'
 }
+download_scopes : List[DownloadScope] = [ 'lite', 'full' ]
 
 log_level_set : LogLevelSet =\
 {

facefusion/content_analyser.py

@@ -8,7 +8,7 @@ from facefusion import inference_manager, state_manager, wording
 from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Fps, InferencePool, ModelOptions, ModelSet, VisionFrame
+from facefusion.typing import DownloadScope, Fps, InferencePool, ModelOptions, ModelSet, VisionFrame
 from facefusion.vision import count_video_frame_total, detect_video_fps, get_video_frame, read_image
 
 PROBABILITY_LIMIT = 0.80
@@ -17,7 +17,7 @@ STREAM_COUNTER = 0
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'open_nsfw':
@@ -54,7 +54,7 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return create_static_model_set().get('open_nsfw')
+	return create_static_model_set('full').get('open_nsfw')
 
 
 def pre_check() -> bool:

facefusion/core.py

@@ -138,7 +138,7 @@ def force_download() -> ErrorCode:
 
 	for module in common_modules + processor_modules:
 		if hasattr(module, 'create_static_model_set'):
-			for model in module.create_static_model_set().values():
+			for model in module.create_static_model_set(state_manager.get_item('download_scope')).values():
 				model_hashes = model.get('hashes')
 				model_sources = model.get('sources')
 

facefusion/face_classifier.py

@@ -8,11 +8,11 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
 from facefusion.face_helper import warp_face_by_face_landmark_5
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Age, FaceLandmark5, Gender, InferencePool, ModelOptions, ModelSet, Race, VisionFrame
+from facefusion.typing import Age, DownloadScope, FaceLandmark5, Gender, InferencePool, ModelOptions, ModelSet, Race, VisionFrame
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'fairface':
@@ -51,7 +51,7 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return create_static_model_set().get('fairface')
+	return create_static_model_set('full').get('fairface')
 
 
 def pre_check() -> bool:

facefusion/face_detector.py

@@ -9,12 +9,12 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
 from facefusion.face_helper import create_rotated_matrix_and_size, create_static_anchors, distance_to_bounding_box, distance_to_face_landmark_5, normalize_bounding_box, transform_bounding_box, transform_points
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import Angle, BoundingBox, Detection, DownloadSet, FaceLandmark5, InferencePool, ModelSet, Score, VisionFrame
+from facefusion.typing import Angle, BoundingBox, Detection, DownloadScope, DownloadSet, FaceLandmark5, InferencePool, ModelSet, Score, VisionFrame
 from facefusion.vision import resize_frame_resolution, unpack_resolution
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'retinaface':
@@ -91,7 +91,7 @@ def clear_inference_pool() -> None:
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
 	model_hashes = {}
 	model_sources = {}
-	model_set = create_static_model_set()
+	model_set = create_static_model_set('full')
 
 	if state_manager.get_item('face_detector_model') in [ 'many', 'retinaface' ]:
 		model_hashes['retinaface'] = model_set.get('retinaface').get('hashes').get('retinaface')

facefusion/face_landmarker.py

@@ -9,11 +9,11 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
 from facefusion.face_helper import create_rotated_matrix_and_size, estimate_matrix_by_face_landmark_5, transform_points, warp_face_by_translation
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Angle, BoundingBox, DownloadSet, FaceLandmark5, FaceLandmark68, InferencePool, ModelSet, Prediction, Score, VisionFrame
+from facefusion.typing import Angle, BoundingBox, DownloadScope, DownloadSet, FaceLandmark5, FaceLandmark68, InferencePool, ModelSet, Prediction, Score, VisionFrame
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'2dfan4':
@@ -90,7 +90,7 @@ def clear_inference_pool() -> None:
 
 
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
-	model_set = create_static_model_set()
+	model_set = create_static_model_set('full')
 	model_hashes =\
 	{
 		'fan_68_5': model_set.get('fan_68_5').get('hashes').get('fan_68_5')
@@ -132,7 +132,7 @@ def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox
 
 
 def detect_with_2dfan4(temp_vision_frame: VisionFrame, bounding_box: BoundingBox, face_angle: Angle) -> Tuple[FaceLandmark68, Score]:
-	model_size = create_static_model_set().get('2dfan4').get('size')
+	model_size = create_static_model_set('full').get('2dfan4').get('size')
 	scale = 195 / numpy.subtract(bounding_box[2:], bounding_box[:2]).max().clip(1, None)
 	translation = (model_size[0] - numpy.add(bounding_box[2:], bounding_box[:2]) * scale) * 0.5
 	rotated_matrix, rotated_size = create_rotated_matrix_and_size(face_angle, model_size)
@@ -151,7 +151,7 @@ def detect_with_2dfan4(temp_vision_frame: VisionFrame, bounding_box: BoundingBox
 
 
 def detect_with_peppa_wutz(temp_vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]:
-	model_size = create_static_model_set().get('peppa_wutz').get('size')
+	model_size = create_static_model_set('full').get('peppa_wutz').get('size')
 	scale = 195 / numpy.subtract(bounding_box[2:], bounding_box[:2]).max().clip(1, None)
 	translation = (model_size[0] - numpy.add(bounding_box[2:], bounding_box[:2]) * scale) * 0.5
 	rotated_matrix, rotated_size = create_rotated_matrix_and_size(face_angle, model_size)

facefusion/face_masker.py

@@ -9,7 +9,7 @@ from facefusion import inference_manager
 from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import DownloadSet, FaceLandmark68, FaceMaskRegion, InferencePool, Mask, ModelSet, Padding, VisionFrame
+from facefusion.typing import DownloadScope, DownloadSet, FaceLandmark68, FaceMaskRegion, InferencePool, Mask, ModelSet, Padding, VisionFrame
 
 FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
 {
@@ -27,7 +27,7 @@ FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'face_occluder':
@@ -83,7 +83,7 @@ def clear_inference_pool() -> None:
 
 
 def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
-	model_set = create_static_model_set()
+	model_set = create_static_model_set('full')
 	model_hashes =\
 	{
 		'face_occluder': model_set.get('face_occluder').get('hashes').get('face_occluder'),
@@ -118,7 +118,7 @@ def create_static_box_mask(crop_size : Size, face_mask_blur : float, face_mask_p
 
 
 def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
-	model_size = create_static_model_set().get('face_occluder').get('size')
+	model_size = create_static_model_set('full').get('face_occluder').get('size')
 	prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
 	prepare_vision_frame = numpy.expand_dims(prepare_vision_frame, axis = 0).astype(numpy.float32) / 255
 	prepare_vision_frame = prepare_vision_frame.transpose(0, 1, 2, 3)
@@ -130,7 +130,7 @@ def create_occlusion_mask(crop_vision_frame : VisionFrame) -> Mask:
 
 
 def create_region_mask(crop_vision_frame : VisionFrame, face_mask_regions : List[FaceMaskRegion]) -> Mask:
-	model_size = create_static_model_set().get('face_parser').get('size')
+	model_size = create_static_model_set('full').get('face_parser').get('size')
 	prepare_vision_frame = cv2.resize(crop_vision_frame, model_size)
 	prepare_vision_frame = prepare_vision_frame[:, :, ::-1].astype(numpy.float32) / 255
 	prepare_vision_frame = numpy.subtract(prepare_vision_frame, numpy.array([ 0.485, 0.456, 0.406 ]).astype(numpy.float32))

facefusion/face_recognizer.py

@@ -8,11 +8,11 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
 from facefusion.face_helper import warp_face_by_face_landmark_5
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import Embedding, FaceLandmark5, InferencePool, ModelOptions, ModelSet, VisionFrame
+from facefusion.typing import DownloadScope, Embedding, FaceLandmark5, InferencePool, ModelOptions, ModelSet, VisionFrame
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'arcface':
@@ -49,7 +49,7 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return create_static_model_set().get('arcface')
+	return create_static_model_set('full').get('arcface')
 
 
 def pre_check() -> bool:

facefusion/processors/modules/age_modifier.py

@@ -23,12 +23,12 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import AgeModifierDirection, AgeModifierInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import match_frame_color, read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'styleganex_age':
@@ -76,7 +76,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	age_modifier_model = state_manager.get_item('age_modifier_model')
-	return create_static_model_set().get(age_modifier_model)
+	return create_static_model_set('full').get(age_modifier_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/deep_swapper.py

@@ -21,13 +21,16 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import DeepSwapperInputs, DeepSwapperMorph
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, Mask, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import conditional_match_frame_color, read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
-	model_config =\
+	model_config = []
+
+	if download_scope == 'full':
+		model_config.extend(
 		[
 			('druuzil', 'adrianne_palicki_384', (384, 384)),
 			('druuzil', 'agnetha_falskog_224', (224, 224)),
@@ -99,7 +102,11 @@ def create_static_model_set() -> ModelSet:
 			('edel', 'ivanka_trump_224', (224, 224)),
 			('edel', 'lize_dzjabrailova_224', (224, 224)),
 			('edel', 'sidney_sweeney_224', (224, 224)),
-		('edel', 'winona_ryder_224', (224, 224)),
+			('edel', 'winona_ryder_224', (224, 224))
+		])
+	if download_scope in [ 'lite', 'full' ]:
+		model_config.extend(
+		[
 			('iperov', 'alexandra_daddario_224', (224, 224)),
 			('iperov', 'alexei_navalny_224', (224, 224)),
 			('iperov', 'amber_heard_224', (224, 224)),
@@ -123,7 +130,11 @@ def create_static_model_set() -> ModelSet:
 			('iperov', 'thomas_cruise_224', (224, 224)),
 			('iperov', 'thomas_holland_224', (224, 224)),
 			('iperov', 'vin_diesel_224', (224, 224)),
-		('iperov', 'vladimir_putin_224', (224, 224)),
+			('iperov', 'vladimir_putin_224', (224, 224))
+		])
+	if download_scope == 'full':
+		model_config.extend(
+		[
 			('jen', 'angelica_trae_288', (288, 288)),
 			('jen', 'ella_freya_224', (224, 224)),
 			('jen', 'emma_myers_320', (320, 320)),
@@ -175,7 +186,7 @@ def create_static_model_set() -> ModelSet:
 			('rumateus', 'shay_mitchell_224', (224, 224)),
 			('rumateus', 'sophie_turner_224', (224, 224)),
 			('rumateus', 'taylor_swift_224', (224, 224))
-	]
+		])
 	model_set : ModelSet = {}
 
 	for model_creator, model_name, model_size in model_config:
@@ -219,7 +230,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	deep_swapper_model = state_manager.get_item('deep_swapper_model')
-	return create_static_model_set().get(deep_swapper_model)
+	return create_static_model_set('full').get(deep_swapper_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/expression_restorer.py

@@ -23,12 +23,12 @@ from facefusion.processors.typing import ExpressionRestorerInputs
 from facefusion.processors.typing import LivePortraitExpression, LivePortraitFeatureVolume, LivePortraitMotionPoints, LivePortraitPitch, LivePortraitRoll, LivePortraitScale, LivePortraitTranslation, LivePortraitYaw
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore, thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import get_video_frame, read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'live_portrait':
@@ -87,7 +87,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	expression_restorer_model = state_manager.get_item('expression_restorer_model')
-	return create_static_model_set().get(expression_restorer_model)
+	return create_static_model_set('full').get(expression_restorer_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/face_editor.py

@@ -22,12 +22,12 @@ from facefusion.processors.live_portrait import create_rotation, limit_euler_ang
 from facefusion.processors.typing import FaceEditorInputs, LivePortraitExpression, LivePortraitFeatureVolume, LivePortraitMotionPoints, LivePortraitPitch, LivePortraitRoll, LivePortraitRotation, LivePortraitScale, LivePortraitTranslation, LivePortraitYaw
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore, thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, FaceLandmark68, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, FaceLandmark68, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'live_portrait':
@@ -117,7 +117,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_editor_model = state_manager.get_item('face_editor_model')
-	return create_static_model_set().get(face_editor_model)
+	return create_static_model_set('full').get(face_editor_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/face_enhancer.py

@@ -21,12 +21,12 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FaceEnhancerInputs, FaceEnhancerWeight
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'codeformer':
@@ -234,7 +234,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_enhancer_model = state_manager.get_item('face_enhancer_model')
-	return create_static_model_set().get(face_enhancer_model)
+	return create_static_model_set('full').get(face_enhancer_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/face_swapper.py

@@ -24,12 +24,12 @@ from facefusion.processors.pixel_boost import explode_pixel_boost, implode_pixel
 from facefusion.processors.typing import FaceSwapperInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Embedding, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Embedding, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, read_static_images, unpack_resolution, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'blendswap_256':
@@ -348,7 +348,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	face_swapper_model = state_manager.get_item('face_swapper_model')
-	return create_static_model_set().get(face_swapper_model)
+	return create_static_model_set('full').get(face_swapper_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/frame_colorizer.py

@@ -16,12 +16,12 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FrameColorizerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, unpack_resolution, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'ddcolor':
@@ -140,7 +140,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	frame_colorizer_model = state_manager.get_item('frame_colorizer_model')
-	return create_static_model_set().get(frame_colorizer_model)
+	return create_static_model_set('full').get(frame_colorizer_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/frame_enhancer.py

@@ -16,12 +16,12 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import FrameEnhancerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import create_tile_frames, merge_tile_frames, read_image, read_static_image, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'clear_reality_x4':
@@ -397,7 +397,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	frame_enhancer_model = state_manager.get_item('frame_enhancer_model')
-	return create_static_model_set().get(frame_enhancer_model)
+	return create_static_model_set('full').get(frame_enhancer_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/processors/modules/lip_syncer.py

@@ -22,12 +22,12 @@ from facefusion.processors import choices as processors_choices
 from facefusion.processors.typing import LipSyncerInputs
 from facefusion.program_helper import find_argument_group
 from facefusion.thread_helper import conditional_thread_semaphore
-from facefusion.typing import ApplyStateItem, Args, AudioFrame, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
+from facefusion.typing import ApplyStateItem, Args, AudioFrame, DownloadScope, Face, InferencePool, ModelOptions, ModelSet, ProcessMode, QueuePayload, UpdateProgress, VisionFrame
 from facefusion.vision import read_image, read_static_image, restrict_video_fps, write_image
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'wav2lip_96':
@@ -86,7 +86,7 @@ def clear_inference_pool() -> None:
 
 def get_model_options() -> ModelOptions:
 	lip_syncer_model = state_manager.get_item('lip_syncer_model')
-	return create_static_model_set().get(lip_syncer_model)
+	return create_static_model_set('full').get(lip_syncer_model)
 
 
 def register_args(program : ArgumentParser) -> None:

facefusion/program.py

@@ -207,6 +207,14 @@ def create_download_providers_program() -> ArgumentParser:
 	return program
 
 
+def create_download_scope_program() -> ArgumentParser:
+	program = ArgumentParser(add_help = False)
+	group_download = program.add_argument_group('download')
+	group_download.add_argument('--download-scope', help = wording.get('help.download_scope'), default = config.get_str_value('download.download_scope', 'lite'), choices = list(facefusion.choices.download_scopes))
+	job_store.register_job_keys([ 'download_scope' ])
+	return program
+
+
 def create_memory_program() -> ArgumentParser:
 	program = ArgumentParser(add_help = False)
 	group_memory = program.add_argument_group('memory')
@@ -260,7 +268,7 @@ def create_program() -> ArgumentParser:
 	sub_program.add_parser('run', help = wording.get('help.run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), create_uis_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
 	sub_program.add_parser('headless-run', help = wording.get('help.headless_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_paths_program(), create_target_path_program(), create_output_path_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
 	sub_program.add_parser('batch-run', help = wording.get('help.batch_run'), parents = [ create_config_path_program(), create_temp_path_program(), create_jobs_path_program(), create_source_pattern_program(), create_target_pattern_program(), create_output_pattern_program(), collect_step_program(), collect_job_program() ], formatter_class = create_help_formatter_large)
-	sub_program.add_parser('force-download', help = wording.get('help.force_download'), parents = [ create_download_providers_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
+	sub_program.add_parser('force-download', help = wording.get('help.force_download'), parents = [ create_download_providers_program(), create_download_scope_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
 	# job manager
 	sub_program.add_parser('job-list', help = wording.get('help.job_list'), parents = [ create_job_status_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)
 	sub_program.add_parser('job-create', help = wording.get('help.job_create'), parents = [ create_job_id_program(), create_jobs_path_program(), create_log_level_program() ], formatter_class = create_help_formatter_large)

facefusion/typing.py

@@ -119,6 +119,7 @@ ExecutionProviderSet = Dict[ExecutionProviderKey, ExecutionProviderValue]
 
 DownloadProviderKey = Literal['github', 'huggingface']
 DownloadProviderSet = Dict[DownloadProviderKey, str]
+DownloadScope = Literal['lite', 'full']
 Download = TypedDict('Download',
 {
 	'url' : str,
@@ -249,6 +250,7 @@ StateKey = Literal\
 	'execution_thread_count',
 	'execution_queue_count',
 	'download_providers',
+	'download_scope',
 	'video_memory_strategy',
 	'system_memory_limit',
 	'log_level',
@@ -309,6 +311,7 @@ State = TypedDict('State',
 	'execution_thread_count' : int,
 	'execution_queue_count' : int,
 	'download_providers' : List[DownloadProviderKey],
+	'download_scope' : DownloadScope,
 	'video_memory_strategy' : VideoMemoryStrategy,
 	'system_memory_limit' : int,
 	'log_level' : LogLevel,

facefusion/uis/components/face_detector.py

@@ -3,7 +3,7 @@ from typing import Optional, Sequence, Tuple
 import gradio
 
 import facefusion.choices
-from facefusion import choices, face_detector, state_manager, wording
+from facefusion import face_detector, state_manager, wording
 from facefusion.common_helper import calc_float_step, get_last
 from facefusion.typing import Angle, FaceDetectorModel, Score
 from facefusion.uis.core import register_ui_component
@@ -65,7 +65,7 @@ def update_face_detector_model(face_detector_model : FaceDetectorModel) -> Tuple
 	state_manager.set_item('face_detector_model', face_detector_model)
 
 	if face_detector.pre_check():
-		face_detector_size_choices = choices.face_detector_set.get(state_manager.get_item('face_detector_model'))
+		face_detector_size_choices = facefusion.choices.face_detector_set.get(state_manager.get_item('face_detector_model'))
 		state_manager.set_item('face_detector_size', get_last(face_detector_size_choices))
 		return gradio.Dropdown(value = state_manager.get_item('face_detector_model')), gradio.Dropdown(value = state_manager.get_item('face_detector_size'), choices = face_detector_size_choices)
 	return gradio.Dropdown(), gradio.Dropdown()

facefusion/voice_extractor.py

@@ -8,11 +8,11 @@ from facefusion import inference_manager
 from facefusion.download import conditional_download_hashes, conditional_download_sources, resolve_download_url
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import thread_semaphore
-from facefusion.typing import Audio, AudioChunk, InferencePool, ModelOptions, ModelSet
+from facefusion.typing import Audio, AudioChunk, DownloadScope, InferencePool, ModelOptions, ModelSet
 
 
 @lru_cache(maxsize = None)
-def create_static_model_set() -> ModelSet:
+def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return\
 	{
 		'kim_vocal_2':
@@ -47,7 +47,7 @@ def clear_inference_pool() -> None:
 
 
 def get_model_options() -> ModelOptions:
-	return create_static_model_set().get('kim_vocal_2')
+	return create_static_model_set('full').get('kim_vocal_2')
 
 
 def pre_check() -> bool:

facefusion/wording.py

@@ -185,6 +185,7 @@ WORDING : Dict[str, Any] =\
 		'execution_queue_count': 'specify the amount of frames each thread is processing',
 		# download
 		'download_providers': 'download using different providers (choices: {choices}, ...)',
+		'download_scope': 'specify the download scope',
 		# memory
 		'video_memory_strategy': 'balance fast processing and low VRAM usage',
 		'system_memory_limit': 'limit the available RAM that can be used while processing',