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Update device to be an override, keep core logic in place if value of device is None.

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baudneo 2025-08-01 16:18:27 -06:00
parent 2cc42db8b8
commit ade32c5c8b
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3 changed files with 24 additions and 17 deletions
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24
frigate/config/classification.py
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@ -130,10 +130,10 @@ class SemanticSearchConfig(FrigateBaseModel):
model_size: str = Field( model_size: str = Field(
default="small", title="The size of the embeddings model used." default="small", title="The size of the embeddings model used."
) )
device: str = Field( device: Optional[str] = Field(
default="CPU", default=None,
title="The device to use for semantic search.", title="The gpu id to use for semantic search.",
description="Use 'cpu' or 'gpu', to target a specific gpu use: '0', '1', etc.", description="This is an override, to target a specific gpu use: '0', '1', etc.",
) )
@ -201,10 +201,10 @@ class FaceRecognitionConfig(FrigateBaseModel):
blur_confidence_filter: bool = Field( blur_confidence_filter: bool = Field(
default=True, title="Apply blur quality filter to face confidence." default=True, title="Apply blur quality filter to face confidence."
) )
device: str = Field( device: Optional[str] = Field(
default="CPU", default=None,
title="The device to use for face recognition.", title="The gpu id to use for face recognition.",
description="Use 'cpu' or 'gpu', to target a specific gpu use: '0', '1', etc.", description="This is an override, to target a specific gpu use: '0', '1', etc.",
) )
@ -264,10 +264,10 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
default=False, default=False,
title="Save plates captured for LPR for debugging purposes.", title="Save plates captured for LPR for debugging purposes.",
) )
device: str = Field( device: Optional[str] = Field(
default="CPU", default=None,
title="The device to use for license plate recognition.", title="The gpu id to use for license plate recognition.",
description="Use 'cpu' or 'gpu', to target a specific gpu use: '0', '1', etc.", description="This is an override, to target a specific gpu use: '0', '1', etc.",
) )

6
frigate/embeddings/embeddings.py
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@ -112,7 +112,8 @@ class Embeddings:
self.embedding = JinaV2Embedding( self.embedding = JinaV2Embedding(
model_size=self.config.semantic_search.model_size, model_size=self.config.semantic_search.model_size,
requestor=self.requestor, requestor=self.requestor,
device=self.config.semantic_search.device, device=config.semantic_search.device
or ("GPU" if config.semantic_search.model_size == "large" else "CPU"),
) )
self.text_embedding = lambda input_data: self.embedding( self.text_embedding = lambda input_data: self.embedding(
input_data, embedding_type="text" input_data, embedding_type="text"
@ -129,7 +130,8 @@ class Embeddings:
self.vision_embedding = JinaV1ImageEmbedding( self.vision_embedding = JinaV1ImageEmbedding(
model_size=config.semantic_search.model_size, model_size=config.semantic_search.model_size,
requestor=self.requestor, requestor=self.requestor,
device=self.config.semantic_search.device, device=config.semantic_search.device
or ("GPU" if config.semantic_search.model_size == "large" else "CPU"),
) )
def update_stats(self) -> None: def update_stats(self) -> None:

7
frigate/embeddings/onnx/face_embedding.py
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@ -150,7 +150,12 @@ class ArcfaceEmbedding(BaseEmbedding):
self.runner = ONNXModelRunner( self.runner = ONNXModelRunner(
os.path.join(self.download_path, self.model_file), os.path.join(self.download_path, self.model_file),
device=self.config.face_recognition.device, device=self.config.face_recognition.device
or (
"GPU"
if self.config.face_recognition.model_size == "large"
else "CPU"
),
) )
def _preprocess_inputs(self, raw_inputs): def _preprocess_inputs(self, raw_inputs):