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Feat/simplify hashes sources download (#814)

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* Extract download directory path from assets path

* Fix lint

* Fix force-download command, Fix urls in frame enhancer
This commit is contained in:
Henry Ruhs 2024-11-14 22:34:23 +01:00 committed by GitHub
parent 74c61108dd
commit 9d0c377aa0
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GPG Key ID: B5690EEEBB952194
19 changed files with 45 additions and 53 deletions
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3
facefusion/content_analyser.py
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@ -54,11 +54,10 @@ def get_model_options() -> ModelOptions:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def analyse_stream(vision_frame : VisionFrame, video_fps : Fps) -> bool: def analyse_stream(vision_frame : VisionFrame, video_fps : Fps) -> bool:

5
facefusion/core.py
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@ -16,7 +16,7 @@ from facefusion.face_analyser import get_average_face, get_many_faces, get_one_f
from facefusion.face_selector import sort_and_filter_faces from facefusion.face_selector import sort_and_filter_faces
from facefusion.face_store import append_reference_face, clear_reference_faces, get_reference_faces from facefusion.face_store import append_reference_face, clear_reference_faces, get_reference_faces
from facefusion.ffmpeg import copy_image, extract_frames, finalize_image, merge_video, replace_audio, restore_audio from facefusion.ffmpeg import copy_image, extract_frames, finalize_image, merge_video, replace_audio, restore_audio
from facefusion.filesystem import filter_audio_paths, is_image, is_video, list_directory, resolve_file_pattern, resolve_relative_path from facefusion.filesystem import filter_audio_paths, is_image, is_video, list_directory, resolve_file_pattern
from facefusion.jobs import job_helper, job_manager, job_runner from facefusion.jobs import job_helper, job_manager, job_runner
from facefusion.jobs.job_list import compose_job_list from facefusion.jobs.job_list import compose_job_list
from facefusion.memory import limit_system_memory from facefusion.memory import limit_system_memory
@ -158,7 +158,6 @@ def conditional_append_reference_faces() -> None:
def force_download() -> ErrorCode: def force_download() -> ErrorCode:
download_directory_path = resolve_relative_path('../.assets/models')
available_processors = list_directory('facefusion/processors/modules') available_processors = list_directory('facefusion/processors/modules')
common_modules =\ common_modules =\
[ [
@ -179,7 +178,7 @@ def force_download() -> ErrorCode:
model_sources = model.get('sources') model_sources = model.get('sources')
if model_hashes and model_sources: if model_hashes and model_sources:
if not conditional_download_hashes(download_directory_path, model_hashes) or not conditional_download_sources(download_directory_path, model_sources): if not conditional_download_hashes(model_hashes) or not conditional_download_sources(model_sources):
return 1 return 1
return 0 return 0

6
facefusion/download.py
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@ -48,7 +48,7 @@ def get_download_size(url : str) -> int:
return 0 return 0
def conditional_download_hashes(download_directory_path : str, hashes : DownloadSet) -> bool: def conditional_download_hashes(hashes : DownloadSet) -> bool:
hash_paths = [ hashes.get(hash_key).get('path') for hash_key in hashes.keys() ] hash_paths = [ hashes.get(hash_key).get('path') for hash_key in hashes.keys() ]
process_manager.check() process_manager.check()
@ -58,6 +58,7 @@ def conditional_download_hashes(download_directory_path : str, hashes : Download
for index in hashes: for index in hashes:
if hashes.get(index).get('path') in invalid_hash_paths: if hashes.get(index).get('path') in invalid_hash_paths:
invalid_hash_url = hashes.get(index).get('url') invalid_hash_url = hashes.get(index).get('url')
download_directory_path = os.path.dirname(hashes.get(index).get('path'))
conditional_download(download_directory_path, [ invalid_hash_url ]) conditional_download(download_directory_path, [ invalid_hash_url ])
valid_hash_paths, invalid_hash_paths = validate_hash_paths(hash_paths) valid_hash_paths, invalid_hash_paths = validate_hash_paths(hash_paths)
@ -73,7 +74,7 @@ def conditional_download_hashes(download_directory_path : str, hashes : Download
return not invalid_hash_paths return not invalid_hash_paths
def conditional_download_sources(download_directory_path : str, sources : DownloadSet) -> bool: def conditional_download_sources(sources : DownloadSet) -> bool:
source_paths = [ sources.get(source_key).get('path') for source_key in sources.keys() ] source_paths = [ sources.get(source_key).get('path') for source_key in sources.keys() ]
process_manager.check() process_manager.check()
@ -83,6 +84,7 @@ def conditional_download_sources(download_directory_path : str, sources : Downlo
for index in sources: for index in sources:
if sources.get(index).get('path') in invalid_source_paths: if sources.get(index).get('path') in invalid_source_paths:
invalid_source_url = sources.get(index).get('url') invalid_source_url = sources.get(index).get('url')
download_directory_path = os.path.dirname(sources.get(index).get('path'))
conditional_download(download_directory_path, [ invalid_source_url ]) conditional_download(download_directory_path, [ invalid_source_url ])
valid_source_paths, invalid_source_paths = validate_source_paths(source_paths) valid_source_paths, invalid_source_paths = validate_source_paths(source_paths)

3
facefusion/face_classifier.py
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@ -51,11 +51,10 @@ def get_model_options() -> ModelOptions:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def classify_face(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Gender, Age, Race]: def classify_face(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Gender, Age, Race]:

3
facefusion/face_detector.py
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@ -101,10 +101,9 @@ def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes, model_sources = collect_model_downloads() model_hashes, model_sources = collect_model_downloads()
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def detect_faces(vision_frame : VisionFrame) -> Tuple[List[BoundingBox], List[Score], List[FaceLandmark5]]: def detect_faces(vision_frame : VisionFrame) -> Tuple[List[BoundingBox], List[Score], List[FaceLandmark5]]:

3
facefusion/face_landmarker.py
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@ -105,10 +105,9 @@ def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes, model_sources = collect_model_downloads() model_hashes, model_sources = collect_model_downloads()
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]: def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]:

3
facefusion/face_masker.py
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@ -93,10 +93,9 @@ def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes, model_sources = collect_model_downloads() model_hashes, model_sources = collect_model_downloads()
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
@lru_cache(maxsize = None) @lru_cache(maxsize = None)

3
facefusion/face_recognizer.py
View File

@ -49,11 +49,10 @@ def get_model_options() -> ModelOptions:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def calc_embedding(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Embedding, Embedding]: def calc_embedding(temp_vision_frame : VisionFrame, face_landmark_5 : FaceLandmark5) -> Tuple[Embedding, Embedding]:

3
facefusion/processors/modules/age_modifier.py
View File

@ -91,11 +91,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

23
facefusion/processors/modules/deep_swapper.py
View File

@ -33,7 +33,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'emma_watson_224.hash'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'emma_watson_224.hash'),
'path': resolve_relative_path('../.assets/models/emma_watson_224.hash') 'path': resolve_relative_path('../.assets/models/iperov/emma_watson_224.hash')
} }
}, },
'sources': 'sources':
@ -41,7 +41,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'emma_watson_224.dfm'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'emma_watson_224.dfm'),
'path': resolve_relative_path('../.assets/models/emma_watson_224.dfm') 'path': resolve_relative_path('../.assets/models/iperov/emma_watson_224.dfm')
} }
}, },
'size': (224, 224), 'size': (224, 224),
@ -55,7 +55,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'jackie_chan_224.hash'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'jackie_chan_224.hash'),
'path': resolve_relative_path('../.assets/models/jackie_chan_224.hash') 'path': resolve_relative_path('../.assets/models/iperov/jackie_chan_224.hash')
} }
}, },
'sources': 'sources':
@ -63,7 +63,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'jackie_chan_224.dfm'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'jackie_chan_224.dfm'),
'path': resolve_relative_path('../.assets/models/jackie_chan_224.dfm') 'path': resolve_relative_path('../.assets/models/iperov/jackie_chan_224.dfm')
} }
}, },
'size': (224, 224), 'size': (224, 224),
@ -77,7 +77,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'keanu_reeves_320.hash'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'keanu_reeves_320.hash'),
'path': resolve_relative_path('../.assets/models/keanu_reeves_320.hash') 'path': resolve_relative_path('../.assets/models/iperov/keanu_reeves_320.hash')
} }
}, },
'sources': 'sources':
@ -85,7 +85,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'keanu_reeves_320.dfm'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'keanu_reeves_320.dfm'),
'path': resolve_relative_path('../.assets/models/keanu_reeves_320.dfm') 'path': resolve_relative_path('../.assets/models/iperov/keanu_reeves_320.dfm')
} }
}, },
'size': (320, 320), 'size': (320, 320),
@ -99,7 +99,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'sylvester_stallone_224.hash'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'sylvester_stallone_224.hash'),
'path': resolve_relative_path('../.assets/models/sylvester_stallone_224.hash') 'path': resolve_relative_path('../.assets/models/iperov/sylvester_stallone_224.hash')
} }
}, },
'sources': 'sources':
@ -107,7 +107,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'sylvester_stallone_224.dfm'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'sylvester_stallone_224.dfm'),
'path': resolve_relative_path('../.assets/models/sylvester_stallone_224.dfm') 'path': resolve_relative_path('../.assets/models/iperov/sylvester_stallone_224.dfm')
} }
}, },
'size': (224, 224), 'size': (224, 224),
@ -121,7 +121,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'taylor_swift_224.hash'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'taylor_swift_224.hash'),
'path': resolve_relative_path('../.assets/models/taylor_swift_224.hash') 'path': resolve_relative_path('../.assets/models/iperov/taylor_swift_224.hash')
} }
}, },
'sources': 'sources':
@ -129,7 +129,7 @@ def create_model_set() -> ModelSet:
'deep_swapper': 'deep_swapper':
{ {
'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'taylor_swift_224.dfm'), 'url': resolve_download_url_by_provider('huggingface', 'deepfacelive-models-iperov', 'taylor_swift_224.dfm'),
'path': resolve_relative_path('../.assets/models/taylor_swift_224.dfm') 'path': resolve_relative_path('../.assets/models/iperov/taylor_swift_224.dfm')
} }
}, },
'size': (224, 224), 'size': (224, 224),
@ -167,11 +167,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/expression_restorer.py
View File

@ -102,11 +102,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/face_editor.py
View File

@ -158,11 +158,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/face_enhancer.py
View File

@ -249,11 +249,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/face_swapper.py
View File

@ -365,11 +365,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/frame_colorizer.py
View File

@ -157,11 +157,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

7
facefusion/processors/modules/frame_enhancer.py
View File

@ -238,7 +238,7 @@ def create_model_set() -> ModelSet:
{ {
'frame_enhancer': 'frame_enhancer':
{ {
'url': resolve_download_url('models-3.0.0', 'real_web_photo_x4.hash'), 'url': resolve_download_url('models-3.1.0', 'real_web_photo_x4.hash'),
'path': resolve_relative_path('../.assets/models/real_web_photo_x4.hash') 'path': resolve_relative_path('../.assets/models/real_web_photo_x4.hash')
} }
}, },
@ -246,7 +246,7 @@ def create_model_set() -> ModelSet:
{ {
'frame_enhancer': 'frame_enhancer':
{ {
'url': resolve_download_url('models-3.0.0', 'real_web_photo_x4.onnx'), 'url': resolve_download_url('models-3.1.0', 'real_web_photo_x4.onnx'),
'path': resolve_relative_path('../.assets/models/real_web_photo_x4.onnx') 'path': resolve_relative_path('../.assets/models/real_web_photo_x4.onnx')
} }
}, },
@ -412,11 +412,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

3
facefusion/processors/modules/lip_syncer.py
View File

@ -99,11 +99,10 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def pre_process(mode : ProcessMode) -> bool: def pre_process(mode : ProcessMode) -> bool:

15
facefusion/program.py
View File

@ -199,12 +199,19 @@ def create_execution_program() -> ArgumentParser:
return program return program
def create_download_program() -> ArgumentParser: def create_download_providers_program() -> ArgumentParser:
program = ArgumentParser(add_help = False) program = ArgumentParser(add_help = False)
group_download = program.add_argument_group('download') group_download = program.add_argument_group('download')
group_download.add_argument('--download-providers', help = wording.get('help.download_providers').format(choices = ', '.join(list(facefusion.choices.download_provider_set.keys()))), default = config.get_str_list('download.download_providers', 'github'), choices = list(facefusion.choices.download_provider_set.keys()), nargs = '+', metavar = 'DOWNLOAD_PROVIDERS') group_download.add_argument('--download-providers', help = wording.get('help.download_providers').format(choices = ', '.join(list(facefusion.choices.download_provider_set.keys()))), default = config.get_str_list('download.download_providers', 'github'), choices = list(facefusion.choices.download_provider_set.keys()), nargs = '+', metavar = 'DOWNLOAD_PROVIDERS')
job_store.register_job_keys([ 'download_providers' ])
return program
def create_skip_download_program() -> ArgumentParser:
program = ArgumentParser(add_help = False)
group_download = program.add_argument_group('download')
group_download.add_argument('--skip-download', help = wording.get('help.skip_download'), action = 'store_true', default = config.get_bool_value('misc.skip_download')) group_download.add_argument('--skip-download', help = wording.get('help.skip_download'), action = 'store_true', default = config.get_bool_value('misc.skip_download'))
job_store.register_job_keys([ 'download_providers', 'skip_download' ]) job_store.register_job_keys([ 'skip_download' ])
return program return program
@ -249,7 +256,7 @@ def collect_step_program() -> ArgumentParser:
def collect_job_program() -> ArgumentParser: def collect_job_program() -> ArgumentParser:
return ArgumentParser(parents= [ create_execution_program(), create_download_program(), create_memory_program(), create_log_level_program() ], add_help = False) return ArgumentParser(parents= [ create_execution_program(), create_download_providers_program(), create_skip_download_program(), create_memory_program(), create_log_level_program() ], add_help = False)
def create_program() -> ArgumentParser: def create_program() -> ArgumentParser:
@ -261,7 +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('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('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('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_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_log_level_program() ], formatter_class = create_help_formatter_large)
# job manager # 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-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) 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)

3
facefusion/voice_extractor.py
View File

@ -47,11 +47,10 @@ def get_model_options() -> ModelOptions:
def pre_check() -> bool: def pre_check() -> bool:
download_directory_path = resolve_relative_path('../.assets/models')
model_hashes = get_model_options().get('hashes') model_hashes = get_model_options().get('hashes')
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return conditional_download_hashes(download_directory_path, model_hashes) and conditional_download_sources(download_directory_path, model_sources) return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
def batch_extract_voice(audio : Audio, chunk_size : int, step_size : int) -> Audio: def batch_extract_voice(audio : Audio, chunk_size : int, step_size : int) -> Audio: