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Code Issues Actions 2 Packages Projects Releases Wiki Activity

Cleanup

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This commit is contained in:
Nicolas Mowen 2025-05-23 07:01:10 -06:00
parent 5df1cf6d1d
commit dd8085993d
3 changed files with 6 additions and 6 deletions
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6
frigate/config/classification.py
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@ -52,8 +52,8 @@ class CustomClassificationObjectConfig(FrigateBaseModel):
class CustomClassificationConfig(FrigateBaseModel): class CustomClassificationConfig(FrigateBaseModel):
enabled: bool = Field(default=True, title="Enable running the model.") enabled: bool = Field(default=True, title="Enable running the model.")
model_path: str = Field(title="Path to teachable machine tflite model.") model_path: str = Field(title="Path to custom classification tflite model.")
labelmap_path: str = Field(title="Path to teachable machine labelmap.") labelmap_path: str = Field(title="Path to custom classification model labelmap.")
object_config: CustomClassificationObjectConfig | None = Field(default=None) object_config: CustomClassificationObjectConfig | None = Field(default=None)
state_config: CustomClassificationStateConfig | None = Field(default=None) state_config: CustomClassificationStateConfig | None = Field(default=None)
@ -63,7 +63,7 @@ class ClassificationConfig(FrigateBaseModel):
default_factory=BirdClassificationConfig, title="Bird classification config." default_factory=BirdClassificationConfig, title="Bird classification config."
) )
custom: Dict[str, CustomClassificationConfig] = Field( custom: Dict[str, CustomClassificationConfig] = Field(
default={}, title="Teachable Machine Model Configs." default={}, title="Custom Classification Model Configs."
) )

2
frigate/data_processing/real_time/custom_classification.py
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@ -1,4 +1,4 @@
"""Real time processor that works with teachable machine tflite models.""" """Real time processor that works with classification tflite models."""
import logging import logging
from typing import Any from typing import Any

4
frigate/embeddings/maintainer.py
View File

@ -147,7 +147,7 @@ class EmbeddingMaintainer(threading.Thread):
) )
) )
for model in self.config.classification.teachable_machine.values(): for model in self.config.classification.custom.values():
self.realtime_processors.append( self.realtime_processors.append(
CustomStateClassificationProcessor(self.config, model, self.metrics) CustomStateClassificationProcessor(self.config, model, self.metrics)
if model.state_config != None if model.state_config != None
@ -482,7 +482,7 @@ class EmbeddingMaintainer(threading.Thread):
if ( if (
camera_config.type != CameraTypeEnum.lpr camera_config.type != CameraTypeEnum.lpr
or "license_plate" in camera_config.objects.track or "license_plate" in camera_config.objects.track
) and len(self.config.classification.teachable_machine) == 0: ) and len(self.config.classification.custom) == 0:
# no active features that use this data # no active features that use this data
return return