#!/usr/bin/env python3

import cv2

import depthai as dai

import queue

# Create pipeline

pipeline = dai.Pipeline()

# Add all three cameras

camRgb = pipeline.create(dai.node.ColorCamera)

left = pipeline.create(dai.node.MonoCamera)

right = pipeline.create(dai.node.MonoCamera)

# Create XLink output

xout = pipeline.create(dai.node.XLinkOut)

xout.setStreamName("frames")

# Properties

camRgb.setPreviewSize(300, 300)

left.setCamera("left")

left.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)

right.setCamera("right")

right.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)

# Stream all the camera streams through the same XLink node

camRgb.preview.link(xout.input)

left.out.link(xout.input)

right.out.link(xout.input)

q = queue.Queue()

def newFrame(inFrame):

global q

# Get "stream name" from the instance number

num = inFrame.getInstanceNum()

name = "color" if num == 0 else "left" if num == 1 else "right"

frame = inFrame.getCvFrame()

# This is a different thread and you could use it to

# run image processing algorithms here

q.put({"name": name, "frame": frame})

# Connect to device and start pipeline

with dai.Device(pipeline) as device:

# Add callback to the output queue "frames" for all newly arrived frames (color, left, right)

device.getOutputQueue(name="frames", maxSize=4, blocking=False).addCallback(newFrame)

while True:

# You could also get the data as non-blocking (block=False)

data = q.get(block=True)

cv2.imshow(data["name"], data["frame"])

if cv2.waitKey(1) == ord('q'):

break