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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
2025-04-28 10:03:25 +02:00
committed by henryruhs
parent 1bdc02014c
commit f3bbd3e16f
26 changed files with 172 additions and 157 deletions
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facefusion/face_detector.py
+10 -9
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@@ -79,8 +79,9 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_detector_model') ]
_, 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:
@@ -89,22 +90,22 @@ def clear_inference_pool() -> None:
def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:
model_hashes = {}
model_sources = {}
model_set = create_static_model_set('full')
model_hash_set = {}
model_source_set = {}
for face_detector_model in [ 'retinaface', 'scrfd', 'yolo_face' ]:
if state_manager.get_item('face_detector_model') in [ 'many', face_detector_model ]:
model_hashes[face_detector_model] = model_set.get(face_detector_model).get('hashes').get(face_detector_model)
model_sources[face_detector_model] = model_set.get(face_detector_model).get('sources').get(face_detector_model)
model_hash_set[face_detector_model] = model_set.get(face_detector_model).get('hashes').get(face_detector_model)
model_source_set[face_detector_model] = model_set.get(face_detector_model).get('sources').get(face_detector_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_faces(vision_frame : VisionFrame) -> Tuple[List[BoundingBox], List[Score], List[FaceLandmark5]]: