diff.py

import depthai as dai
from pathlib import Path
from utils.arguments import initialize_argparser
from utils.colorize_diff import ColorizeDiff

NN_DIFF_SIZE = (720, 720)

_, args = initialize_argparser()

device = dai.Device(dai.DeviceInfo(args.device)) if args.device else dai.Device()
visualizer = dai.RemoteConnection(httpPort=8082)


with dai.Pipeline(device) as pipeline:
    platform = device.getPlatformAsString()

    cam_rgb = pipeline.create(dai.node.Camera).build(
        boardSocket=dai.CameraBoardSocket.CAM_A
    )
    cam_rgb_diff_out = cam_rgb.requestOutput(
        size=NN_DIFF_SIZE,
        type=dai.ImgFrame.Type.BGR888i
        if platform == "RVC4"
        else dai.ImgFrame.Type.BGR888p,
        fps=args.fps_limit,
    )

    script = pipeline.create(dai.node.Script)
    script.setScript("""
    old = node.io['in'].get()
    while True:
        frame = node.io['in'].get()
        node.io['img1'].send(old)
        node.io['img2'].send(frame)
        old = frame
    """)
    cam_rgb_diff_out.link(script.inputs["in"])

    # DIFF
    diff_nn_archive_path = Path(__file__).parent / Path(
        f"models/diff.{platform.lower()}.tar.xz"
    )
    diff_nn_archive = dai.NNArchive(archivePath=str(diff_nn_archive_path))
    nn_diff = pipeline.create(dai.node.NeuralNetwork)
    nn_diff.setNNArchive(diff_nn_archive)
    script.outputs["img1"].link(nn_diff.inputs["img1"])
    script.outputs["img2"].link(nn_diff.inputs["img2"])
    diff_color = pipeline.create(ColorizeDiff).build(nn=nn_diff.out)

    visualizer.addTopic("Diff", diff_color.out, "images")
    visualizer.addTopic("Passthrough", script.outputs["img1"], "images")

    print("Pipeline created.")

    pipeline.start()
    visualizer.registerPipeline(pipeline)

    while pipeline.isRunning():
        pipeline.processTasks()
        key = visualizer.waitKey(1)
        if key == ord("q"):
            print("Got q key from the remote connection!")
            break