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Provide different XSeg models

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This commit is contained in:
henryruhs 2024-12-16 23:17:32 +01:00
parent 29349f9675
commit 4b5336dac9
4 changed files with 35 additions and 11 deletions
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2
facefusion/choices.py
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@ -17,7 +17,7 @@ face_selector_modes : List[FaceSelectorMode] = [ 'many', 'one', 'reference' ]
face_selector_orders : List[FaceSelectorOrder] = [ 'left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best' ]
face_selector_genders : List[Gender] = [ 'female', 'male' ]
face_selector_races : List[Race] = [ 'white', 'black', 'latino', 'asian', 'indian', 'arabic' ]
face_occluder_models : List[FaceOccluderModel] = [ 'xseg_groggy_5' ]
face_occluder_models : List[FaceOccluderModel] = [ 'xseg_1', 'xseg_2' ]
face_parser_models : List[FaceParserModel] = [ 'bisenet_resnet_18', 'bisenet_resnet_34' ]
face_mask_types : List[FaceMaskType] = [ 'box', 'occlusion', 'region' ]
face_mask_regions : List[FaceMaskRegion] = [ 'skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip' ]

40
facefusion/face_masker.py
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@ -30,22 +30,42 @@ FACE_MASK_REGIONS : Dict[FaceMaskRegion, int] =\
def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
return\
{
'xseg_groggy_5':
'xseg_1':
{
'hashes':
{
'face_occluder':
{
'url': resolve_download_url('models-3.1.0', 'xseg_groggy_5.hash'),
'path': resolve_relative_path('../.assets/models/xseg_groggy_5.hash')
'url': resolve_download_url('models-3.1.0', 'xseg_1.hash'),
'path': resolve_relative_path('../.assets/models/xseg_1.hash')
}
},
'sources':
{
'face_occluder':
{
'url': resolve_download_url('models-3.1.0', 'xseg_groggy_5.onnx'),
'path': resolve_relative_path('../.assets/models/xseg_groggy_5.onnx')
'url': resolve_download_url('models-3.1.0', 'xseg_1.onnx'),
'path': resolve_relative_path('../.assets/models/xseg_1.onnx')
}
},
'size': (256, 256)
},
'xseg_2':
{
'hashes':
{
'face_occluder':
{
'url': resolve_download_url('models-3.1.0', 'xseg_2.hash'),
'path': resolve_relative_path('../.assets/models/xseg_2.hash')
}
},
'sources':
{
'face_occluder':
{
'url': resolve_download_url('models-3.1.0', 'xseg_2.onnx'),
'path': resolve_relative_path('../.assets/models/xseg_2.onnx')
}
},
'size': (256, 256)
@ -107,9 +127,13 @@ def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
model_sources = {}
model_set = create_static_model_set('full')
if state_manager.get_item('face_occluder_model') == 'xseg_groggy_5':
model_hashes['xseg_groggy_5'] = model_set.get('xseg_groggy_5').get('hashes').get('face_occluder')
model_sources['xseg_groggy_5'] = model_set.get('xseg_groggy_5').get('sources').get('face_occluder')
if state_manager.get_item('face_occluder_model') == 'xseg_1':
model_hashes['xseg_1'] = model_set.get('xseg_1').get('hashes').get('face_occluder')
model_sources['xseg_1'] = model_set.get('xseg_1').get('sources').get('face_occluder')
if state_manager.get_item('face_occluder_model') == 'xseg_2':
model_hashes['xseg_2'] = model_set.get('xseg_2').get('hashes').get('face_occluder')
model_sources['xseg_2'] = model_set.get('xseg_2').get('sources').get('face_occluder')
if state_manager.get_item('face_parser_model') == 'bisenet_resnet_18':
model_hashes['bisenet_resnet_18'] = model_set.get('bisenet_resnet_18').get('hashes').get('face_parser')

2
facefusion/program.py
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@ -132,7 +132,7 @@ def create_face_selector_program() -> ArgumentParser:
def create_face_masker_program() -> ArgumentParser:
program = ArgumentParser(add_help = False)
group_face_masker = program.add_argument_group('face masker')
group_face_masker.add_argument('--face-occluder-model', help = wording.get('help.face_occluder_model'), default = config.get_str_value('face_detector.face_occluder_model', 'xseg_groggy_5'), choices = facefusion.choices.face_occluder_models)
group_face_masker.add_argument('--face-occluder-model', help = wording.get('help.face_occluder_model'), default = config.get_str_value('face_detector.face_occluder_model', 'xseg_1'), choices = facefusion.choices.face_occluder_models)
group_face_masker.add_argument('--face-parser-model', help = wording.get('help.face_parser_model'), default = config.get_str_value('face_detector.face_parser_model', 'bisenet_resnet_34'), choices = facefusion.choices.face_parser_models)
group_face_masker.add_argument('--face-mask-types', help = wording.get('help.face_mask_types').format(choices = ', '.join(facefusion.choices.face_mask_types)), default = config.get_str_list('face_masker.face_mask_types', 'box'), choices = facefusion.choices.face_mask_types, nargs = '+', metavar = 'FACE_MASK_TYPES')
group_face_masker.add_argument('--face-mask-blur', help = wording.get('help.face_mask_blur'), type = float, default = config.get_float_value('face_masker.face_mask_blur', '0.3'), choices = facefusion.choices.face_mask_blur_range, metavar = create_float_metavar(facefusion.choices.face_mask_blur_range))

2
facefusion/typing.py
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@ -101,7 +101,7 @@ FaceLandmarkerModel = Literal['many', '2dfan4', 'peppa_wutz']
FaceDetectorSet = Dict[FaceDetectorModel, List[str]]
FaceSelectorMode = Literal['many', 'one', 'reference']
FaceSelectorOrder = Literal['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small', 'best-worst', 'worst-best']
FaceOccluderModel = Literal['xseg_groggy_5']
FaceOccluderModel = Literal['xseg_1', 'xseg_2']
FaceParserModel = Literal['bisenet_resnet_18', 'bisenet_resnet_34']
FaceMaskType = Literal['box', 'occlusion', 'region']
FaceMaskRegion = Literal['skin', 'left-eyebrow', 'right-eyebrow', 'left-eye', 'right-eye', 'glasses', 'nose', 'mouth', 'upper-lip', 'lower-lip']