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Qa/follow set naming (#867)

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* Follow set naming

* Follow set naming

* Disable type hints

* Uniform order
This commit is contained in:
Henry Ruhs
2025-02-09 09:35:56 +01:00
committed by henryruhs
parent 1bdc02014c
commit f3bbd3e16f
26 changed files with 172 additions and 157 deletions
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19
facefusion/face_landmarker.py
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@@ -80,8 +80,9 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_landmarker_model'), 'fan_68_5' ]
_, model_sources = collect_model_downloads()
return inference_manager.get_inference_pool(__name__, model_names, model_sources)
_, model_source_set = collect_model_downloads()
return inference_manager.get_inference_pool(__name__, model_names, model_source_set)
def clear_inference_pool() -> None:
@@ -91,27 +92,27 @@ def clear_inference_pool() -> None:
def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
model_set = create_static_model_set('full')
model_hashes =\
model_hash_set =\
{
'fan_68_5': model_set.get('fan_68_5').get('hashes').get('fan_68_5')
}
model_sources =\
model_source_set =\
{
'fan_68_5': model_set.get('fan_68_5').get('sources').get('fan_68_5')
}
for face_landmarker_model in [ '2dfan4', 'peppa_wutz' ]:
if state_manager.get_item('face_landmarker_model') in [ 'many', face_landmarker_model ]:
model_hashes[face_landmarker_model] = model_set.get(face_landmarker_model).get('hashes').get(face_landmarker_model)
model_sources[face_landmarker_model] = model_set.get(face_landmarker_model).get('sources').get(face_landmarker_model)
model_hash_set[face_landmarker_model] = model_set.get(face_landmarker_model).get('hashes').get(face_landmarker_model)
model_source_set[face_landmarker_model] = model_set.get(face_landmarker_model).get('sources').get(face_landmarker_model)
return model_hashes, model_sources
return model_hash_set, model_source_set
def pre_check() -> bool:
model_hashes, model_sources = collect_model_downloads()
model_hash_set, model_source_set = collect_model_downloads()
return conditional_download_hashes(model_hashes) and conditional_download_sources(model_sources)
return conditional_download_hashes(model_hash_set) and conditional_download_sources(model_source_set)
def detect_face_landmarks(vision_frame : VisionFrame, bounding_box : BoundingBox, face_angle : Angle) -> Tuple[FaceLandmark68, Score]: