DepthAI OAK low latency evaluation script

oak-low-latency.py

import depthai as dai
from depthai_sdk import FPSHandler as FPS

# Create pipeline
pipeline = dai.Pipeline()
pipeline.setXLinkChunkSize(0)

# Define source and output
camRgb = pipeline.create(dai.node.ColorCamera)
camRgb.setFps(30)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P)
camRgb.setIspScale(2,3)

# mono = pipeline.create(dai.node.MonoCamera)
# mono.setFps(60)
# mono.setBoardSocket(dai.CameraBoardSocket.RIGHT)
# mono.setResolution(dai.MonoCameraProperties.SensorResolution.THE_800_P)

videoEnc = pipeline.create(dai.node.VideoEncoder)
videoEnc.setDefaultProfilePreset(30, dai.VideoEncoderProperties.Profile.MJPEG)
camRgb.video.link(videoEnc.input)

xoutVideo = pipeline.create(dai.node.XLinkOut)
xoutVideo.setStreamName("video")
xoutVideo.input.setBlocking(False)
xoutVideo.input.setQueueSize(10)
# camRgb.isp.link(xoutVideo.input)
videoEnc.bitstream.link(xoutVideo.input)

# Connect to device and start pipeline
with dai.Device(pipeline) as device:
    print(device.getUsbSpeed())
    fps = FPS()
    video = device.getOutputQueue(name="video", maxSize=10, blocking=False)

    while True:
        videoIn = video.get()
        diff = dai.Clock.now() - videoIn.getTimestamp()
        print('diff', diff)
        fps.nextIter()
        print(fps.fps())