blakeblackshear.frigate/frigate/data_processing/real_time/license_plate.py

45 lines
1.4 KiB
Python

"""Handle processing images for face detection and recognition."""
import logging
import numpy as np
from frigate.config import FrigateConfig
from frigate.data_processing.common.license_plate.mixin import (
LicensePlateProcessingMixin,
)
from frigate.data_processing.common.license_plate.model import (
LicensePlateModelRunner,
)
from ..types import DataProcessorMetrics
from .api import RealTimeProcessorApi
logger = logging.getLogger(__name__)
class LicensePlateRealTimeProcessor(LicensePlateProcessingMixin, RealTimeProcessorApi):
def __init__(
self,
config: FrigateConfig,
metrics: DataProcessorMetrics,
model_runner: LicensePlateModelRunner,
detected_license_plates: dict[str, dict[str, any]],
):
self.detected_license_plates = detected_license_plates
self.model_runner = model_runner
self.lpr_config = config.lpr
self.config = config
super().__init__(config, metrics)
def process_frame(self, obj_data: dict[str, any], frame: np.ndarray):
"""Look for license plates in image."""
self.lpr_process(obj_data, frame)
def handle_request(self, topic, request_data) -> dict[str, any] | None:
return
def expire_object(self, object_id: str):
if object_id in self.detected_license_plates:
self.detected_license_plates.pop(object_id)