mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
20 lines
671 B
Python
20 lines
671 B
Python
|
import statistics
|
||
|
|
import numpy as np
|
||
|
|
from edgetpu.detection.engine import DetectionEngine
|
||
|
|
|
||
|
|
# Path to frozen detection graph. This is the actual model that is used for the object detection.
|
||
|
|
PATH_TO_CKPT = '/frozen_inference_graph.pb'
|
||
|
|
|
||
|
|
# Load the edgetpu engine and labels
|
||
|
|
engine = DetectionEngine(PATH_TO_CKPT)
|
||
|
|
|
||
|
|
frame = np.zeros((300,300,3), np.uint8)
|
||
|
|
flattened_frame = np.expand_dims(frame, axis=0).flatten()
|
||
|
|
|
||
|
|
detection_times = []
|
||
|
|
|
||
|
|
for x in range(0, 1000):
|
||
|
|
objects = engine.DetectWithInputTensor(flattened_frame, threshold=0.1, top_k=3)
|
||
|
|
detection_times.append(engine.get_inference_time())
|
||
|
|
|
||
|
|
print("Average inference time: " + str(statistics.mean(detection_times)))
|