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Nicolas MowenandGitHub
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59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
import logging
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from typing import ClassVar, Literal
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from pydantic import ConfigDict, Field
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from frigate.detectors.detection_api import DetectionApi
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from frigate.detectors.detector_config import BaseDetectorConfig
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from frigate.log import suppress_stderr_during
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from ..detector_utils import TFLiteDetectionModel
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try:
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from tflite_runtime.interpreter import Interpreter
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except ModuleNotFoundError:
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from ai_edge_litert.interpreter import Interpreter
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logger = logging.getLogger(__name__)
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DETECTOR_KEY = "cpu"
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class CpuDetectorConfig(BaseDetectorConfig):
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"""CPU TFLite detector that runs TensorFlow Lite models on the host CPU without hardware acceleration. Not recommended."""
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model_config = ConfigDict(
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title="CPU",
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)
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device_spec_field: ClassVar[str] = "num_threads"
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device_spec_type: ClassVar[type] = int
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type: Literal[DETECTOR_KEY]
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num_threads: int = Field(
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default=3,
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title="Number of detection threads",
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description="The number of threads used for CPU-based inference.",
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)
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class CpuTfl(DetectionApi):
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type_key = DETECTOR_KEY
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supported_models = TFLiteDetectionModel.supported_models
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def __init__(self, detector_config: CpuDetectorConfig):
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# Suppress TFLite delegate creation messages that bypass Python logging
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with suppress_stderr_during("tflite_interpreter_init"):
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interpreter = Interpreter(
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model_path=detector_config.model.path,
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num_threads=detector_config.num_threads or 3,
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)
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self.tflite_model = TFLiteDetectionModel(
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interpreter, detector_config.model, DETECTOR_KEY
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)
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def detect_raw(self, tensor_input):
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return self.tflite_model.detect_raw(tensor_input)
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