DepthAI auto-reconnect

oak-reconnect.py

#!/usr/bin/env python3

import cv2
import depthai as dai
import numpy as np
import time
import blobconverter


# MobilenetSSD label texts
labelMap = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",
            "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"]

# Create pipeline
pipeline = dai.Pipeline()

# Define sources and outputs
camRgb = pipeline.create(dai.node.ColorCamera)
nn = pipeline.create(dai.node.MobileNetDetectionNetwork)
xoutRgb = pipeline.create(dai.node.XLinkOut)
nnOut = pipeline.create(dai.node.XLinkOut)
nnNetworkOut = pipeline.create(dai.node.XLinkOut)

xoutRgb.setStreamName("rgb")
nnOut.setStreamName("nn")
nnNetworkOut.setStreamName("nnNetwork")

# Properties
camRgb.setPreviewSize(300, 300)
camRgb.setInterleaved(False)
camRgb.setFps(40)
# Define a neural network that will make predictions based on the source frames
nn.setConfidenceThreshold(0.5)
nn.setBlobPath(blobconverter.from_zoo(name="mobilenet-ssd", shaves=6))
nn.input.setBlocking(False)

nn.passthrough.link(xoutRgb.input)
camRgb.preview.link(nn.input)
nn.out.link(nnOut.input)
nn.outNetwork.link(nnNetworkOut.input)

deviceInfo: dai.DeviceInfo = None
def connect_and_run():
    global deviceInfo
    with dai.Device(pipeline, deviceInfo) as device:

        # Output queues will be used to get the rgb frames and nn data from the outputs defined above
        qRgb = device.getOutputQueue(name="rgb", maxSize=4, blocking=False)
        qDet = device.getOutputQueue(name="nn", maxSize=4, blocking=False)
        qNN = device.getOutputQueue(name="nnNetwork", maxSize=4, blocking=False)

        frame = None
        detections = []
        startTime = time.monotonic()
        counter = 0
        color2 = (255, 255, 255)

        # nn data (bounding box locations) are in <0..1> range - they need to be normalized with frame width/height
        def frameNorm(frame, bbox):
            normVals = np.full(len(bbox), frame.shape[0])
            normVals[::2] = frame.shape[1]
            return (np.clip(np.array(bbox), 0, 1) * normVals).astype(int)

        def displayFrame(name, frame):
            color = (255, 0, 0)
            for detection in detections:
                bbox = frameNorm(frame, (detection.xmin, detection.ymin, detection.xmax, detection.ymax))
                cv2.putText(frame, labelMap[detection.label], (bbox[0] + 10, bbox[1] + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
                cv2.putText(frame, f"{int(detection.confidence * 100)}%", (bbox[0] + 10, bbox[1] + 40), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
                cv2.rectangle(frame, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color, 2)
            # Show the frame
            cv2.imshow(name, frame)

        printOutputLayersOnce = True

        while True:
            inRgb = qRgb.get()
            inDet = qDet.get()
            inNN = qNN.get()

            if inRgb is not None:
                frame = inRgb.getCvFrame()
                cv2.putText(frame, "NN fps: {:.2f}".format(counter / (time.monotonic() - startTime)),
                            (2, frame.shape[0] - 4), cv2.FONT_HERSHEY_TRIPLEX, 0.4, color2)

            if inDet is not None:
                detections = inDet.detections
                counter += 1

            if printOutputLayersOnce and inNN is not None:
                toPrint = 'Output layer names:'
                for ten in inNN.getAllLayerNames():
                    toPrint = f'{toPrint} {ten},'
                print(toPrint)
                printOutputLayersOnce = False;

            # If the frame is available, draw bounding boxes on it and show the frame
            if frame is not None:
                displayFrame("rgb", frame)

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

# Adding exception handling to retry the connection if it fails due to a device disconnection
import time
while True:
    try:
        connect_and_run()
    except RuntimeError as e:
        print(f"Runtime error: {e}. Retrying in 2 seconds...")
    except Exception as e:
        print(f"Error: {e}. Retrying in 2 seconds...")
    time.sleep(2)