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DepthAI

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  • Detection network Replay
  • Pipeline
  • Source code

Detection network Replay

Supported on:RVC2RVC4
This example demonstrates using DepthAI's RemoteConnection to stream and visualize YOLOv6 object detection results and video frames from a replayed video file.This example requires the DepthAI v3 API, see installation instructions.

Pipeline

Source code

Python
C++

Python

Python
GitHub
1#!/usr/bin/env python3
2import depthai as dai
3from pathlib import Path
4from argparse import ArgumentParser
5
6scriptDir = Path(__file__).resolve().parent
7examplesRoot = (scriptDir / Path('../')).resolve()  # This resolves the parent directory correctly
8models = examplesRoot / 'models'
9videoPath = models / 'construction_vest.mp4'
10
11parser = ArgumentParser()
12parser.add_argument("--webSocketPort", type=int, default=8765)
13parser.add_argument("--httpPort", type=int, default=8082)
14parser.add_argument("-i", "--inputVideo", default=videoPath, help="Input video name")
15args = parser.parse_args()
16
17remoteConnector = dai.RemoteConnection(webSocketPort=args.webSocketPort, httpPort=args.httpPort)
18# Create pipeline
19with dai.Pipeline() as pipeline:
20    replay = pipeline.create(dai.node.ReplayVideo)
21    replay.setReplayVideoFile(Path(args.inputVideo))
22    detectionNetwork = pipeline.create(dai.node.DetectionNetwork).build(
23        replay, dai.NNModelDescription("yolov6-nano")
24    )
25
26    remoteConnector.addTopic("detections", detectionNetwork.out, "img")
27    remoteConnector.addTopic("images", replay.out, "img")
28
29    pipeline.start()
30    remoteConnector.registerPipeline(pipeline)
31
32    while pipeline.isRunning():
33        key = remoteConnector.waitKey(1)
34        if key == ord("q"):
35            print("Got q key from the remote connection!")
36            break

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