blakeblackshear.frigate/frigate/detectors/plugins/openvino.py

67 lines
2.1 KiB
Python
Raw Normal View History

import logging
import numpy as np
import openvino.runtime as ov
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig
from typing import Literal
from pydantic import Extra, Field
logger = logging.getLogger(__name__)
DETECTOR_KEY = "openvino"
class OvDetectorConfig(BaseDetectorConfig):
type: Literal[DETECTOR_KEY]
device: str = Field(default=None, title="Device Type")
class OvDetector(DetectionApi):
type_key = DETECTOR_KEY
def __init__(self, detector_config: OvDetectorConfig):
self.ov_core = ov.Core()
self.ov_model = self.ov_core.read_model(detector_config.model.path)
self.interpreter = self.ov_core.compile_model(
model=self.ov_model, device_name=detector_config.device
)
logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
self.output_indexes = 0
while True:
try:
tensor_shape = self.interpreter.output(self.output_indexes).shape
logger.info(f"Model Output-{self.output_indexes} Shape: {tensor_shape}")
self.output_indexes += 1
except:
logger.info(f"Model has {self.output_indexes} Output Tensors")
break
def detect_raw(self, tensor_input):
infer_request = self.interpreter.create_infer_request()
infer_request.infer([tensor_input])
results = infer_request.get_output_tensor()
detections = np.zeros((20, 6), np.float32)
i = 0
for object_detected in results.data[0, 0, :]:
if object_detected[0] != -1:
logger.debug(object_detected)
if object_detected[2] < 0.1 or i == 20:
break
detections[i] = [
object_detected[1], # Label ID
float(object_detected[2]), # Confidence
object_detected[4], # y_min
object_detected[3], # x_min
object_detected[6], # y_max
object_detected[5], # x_max
]
i += 1
return detections