RGB video

This example shows how to use high resolution video at low latency. Compared to RGB Preview, this demo outputs NV12 frames whereas preview frames are BGR and are not suited for larger resoulution (eg. 1920x1080). Preview is more suitable for either NN or visualization purposes.

Similiar samples:

Demo

Setup

Please run the install script to download all required dependencies. Please note that this script must be ran from git context, so you have to download the depthai-python repository first and then run the script

git clone https://github.com/luxonis/depthai-python.git
cd depthai-python/examples
python3 install_requirements.py

For additional information, please follow installation guide

Source code

Also available on GitHub

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#!/usr/bin/env python3

import cv2
import depthai as dai

# Create pipeline
pipeline = dai.Pipeline()

# Define source and output
camRgb = pipeline.createColorCamera()
xoutVideo = pipeline.createXLinkOut()

xoutVideo.setStreamName("video")

# Properties
camRgb.setBoardSocket(dai.CameraBoardSocket.RGB)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_1080_P)
camRgb.setVideoSize(1920, 1080)

xoutVideo.input.setBlocking(False)
xoutVideo.input.setQueueSize(1)

# Linking
camRgb.video.link(xoutVideo.input)

# Connect to device and start pipeline
with dai.Device(pipeline) as device:

    video = device.getOutputQueue(name="video", maxSize=1, blocking=False)

    while True:
        videoIn = video.get()

        # Get BGR frame from NV12 encoded video frame to show with opencv
        # Visualizing the frame on slower hosts might have overhead
        cv2.imshow("video", videoIn.getCvFrame())

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

Also available on GitHub

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#include <iostream>

// Inludes common necessary includes for development using depthai library
#include "depthai/depthai.hpp"

int main() {
    // Create pipeline
    dai::Pipeline pipeline;

    // Define source and output
    auto camRgb = pipeline.create<dai::node::ColorCamera>();
    auto xoutVideo = pipeline.create<dai::node::XLinkOut>();

    xoutVideo->setStreamName("video");

    // Properties
    camRgb->setBoardSocket(dai::CameraBoardSocket::RGB);
    camRgb->setResolution(dai::ColorCameraProperties::SensorResolution::THE_1080_P);
    camRgb->setVideoSize(1920, 1080);

    xoutVideo->input.setBlocking(false);
    xoutVideo->input.setQueueSize(1);

    // Linking
    camRgb->video.link(xoutVideo->input);

    // Connect to device and start pipeline
    dai::Device device(pipeline);

    auto video = device.getOutputQueue("video");

    while(true) {
        auto videoIn = video->get<dai::ImgFrame>();

        // Get BGR frame from NV12 encoded video frame to show with opencv
        // Visualizing the frame on slower hosts might have overhead
        cv::imshow("video", videoIn->getCvFrame());

        int key = cv::waitKey(1);
        if(key == 'q' || key == 'Q') {
            return 0;
        }
    }
    return 0;
}

Got questions?

We’re always happy to help with code or other questions you might have.