mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-30 19:09:13 +01:00
420bcd7aa0
* refactor detectors * move create_detector and DetectorTypeEnum * fixed code formatting * add detector model config models * fix detector unit tests * adjust SharedMemory size to largest detector model shape * fix detector model config defaults * enable auto-discovery of detectors * simplify config * simplify config changes further * update detectors docs; detect detector configs dynamic * add suggested changes * remove custom detector doc * fix grammar, adjust device defaults
67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
import logging
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import numpy as np
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import openvino.runtime as ov
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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 typing import Literal
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from pydantic import Extra, Field
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logger = logging.getLogger(__name__)
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DETECTOR_KEY = "openvino"
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class OvDetectorConfig(BaseDetectorConfig):
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type: Literal[DETECTOR_KEY]
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device: str = Field(default=None, title="Device Type")
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class OvDetector(DetectionApi):
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type_key = DETECTOR_KEY
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def __init__(self, detector_config: OvDetectorConfig):
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self.ov_core = ov.Core()
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self.ov_model = self.ov_core.read_model(detector_config.model.path)
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self.interpreter = self.ov_core.compile_model(
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model=self.ov_model, device_name=detector_config.device
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)
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logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
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self.output_indexes = 0
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while True:
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try:
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tensor_shape = self.interpreter.output(self.output_indexes).shape
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logger.info(f"Model Output-{self.output_indexes} Shape: {tensor_shape}")
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self.output_indexes += 1
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except:
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logger.info(f"Model has {self.output_indexes} Output Tensors")
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break
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def detect_raw(self, tensor_input):
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infer_request = self.interpreter.create_infer_request()
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infer_request.infer([tensor_input])
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results = infer_request.get_output_tensor()
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detections = np.zeros((20, 6), np.float32)
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i = 0
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for object_detected in results.data[0, 0, :]:
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if object_detected[0] != -1:
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logger.debug(object_detected)
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if object_detected[2] < 0.1 or i == 20:
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break
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detections[i] = [
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object_detected[1], # Label ID
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float(object_detected[2]), # Confidence
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object_detected[4], # y_min
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object_detected[3], # x_min
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object_detected[6], # y_max
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object_detected[5], # x_max
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]
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i += 1
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return detections
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