RGB Full Resolution Saver

This example saves full-resolution 3840x2160 .jpeg images when c key is pressed. It serves as an example of recording high resolution frames to disk for the purposes of high-resolution ground-truth data.

Note that each frame consumes above 2MB of storage, so “spamming” capture key could fill up your storage.

Similar samples:

• Mono Full Resolution Saver

Encoded bitstream (either MJPEG, H264, or H265) from the device can also be saved directly into .mp4 container with no computational overhead on the host computer. See demo here for more information.

Matroska

Besides ffmpeg and .mp4 video container (which is patent encumbered), you could also use the mkvmerge (see MKVToolNix for GUI usage) and .mkv video container to mux encoded stream into video file that is supported by all major video players (eg. VLC)

mkvmerge -o vid.mkv video.h265

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

Python

C++

Also available on GitHub

#!/usr/bin/env python3

import time
from pathlib import Path
import cv2
import depthai as dai

# Create pipeline
pipeline = dai.Pipeline()

camRgb = pipeline.create(dai.node.ColorCamera)
camRgb.setBoardSocket(dai.CameraBoardSocket.CAM_A)
camRgb.setResolution(dai.ColorCameraProperties.SensorResolution.THE_4_K)

xoutRgb = pipeline.create(dai.node.XLinkOut)
xoutRgb.setStreamName("rgb")
camRgb.video.link(xoutRgb.input)

xin = pipeline.create(dai.node.XLinkIn)
xin.setStreamName("control")
xin.out.link(camRgb.inputControl)

# Properties
videoEnc = pipeline.create(dai.node.VideoEncoder)
videoEnc.setDefaultProfilePreset(1, dai.VideoEncoderProperties.Profile.MJPEG)
camRgb.still.link(videoEnc.input)

# Linking
xoutStill = pipeline.create(dai.node.XLinkOut)
xoutStill.setStreamName("still")
videoEnc.bitstream.link(xoutStill.input)

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

    # Output queue will be used to get the rgb frames from the output defined above
    qRgb = device.getOutputQueue(name="rgb", maxSize=30, blocking=False)
    qStill = device.getOutputQueue(name="still", maxSize=30, blocking=True)
    qControl = device.getInputQueue(name="control")

    # Make sure the destination path is present before starting to store the examples
    dirName = "rgb_data"
    Path(dirName).mkdir(parents=True, exist_ok=True)

    while True:
        inRgb = qRgb.tryGet()  # Non-blocking call, will return a new data that has arrived or None otherwise
        if inRgb is not None:
            frame = inRgb.getCvFrame()
            # 4k / 4
            frame = cv2.pyrDown(frame)
            frame = cv2.pyrDown(frame)
            cv2.imshow("rgb", frame)

        if qStill.has():
            fName = f"{dirName}/{int(time.time() * 1000)}.jpeg"
            with open(fName, "wb") as f:
                f.write(qStill.get().getData())
                print('Image saved to', fName)

        key = cv2.waitKey(1)
        if key == ord('q'):
            break
        elif key == ord('c'):
            ctrl = dai.CameraControl()
            ctrl.setCaptureStill(True)
            qControl.send(ctrl)
            print("Sent 'still' event to the camera!")

Also available on GitHub

#include <chrono>
#include <iostream>

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

int main() {
    using namespace std::chrono;

    // Create pipeline
    dai::Pipeline pipeline;

    // Define source and outputs
    auto camRgb = pipeline.create<dai::node::ColorCamera>();
    auto videoEnc = pipeline.create<dai::node::VideoEncoder>();
    auto xoutJpeg = pipeline.create<dai::node::XLinkOut>();
    auto xoutRgb = pipeline.create<dai::node::XLinkOut>();

    xoutJpeg->setStreamName("jpeg");
    xoutRgb->setStreamName("rgb");

    // Properties
    camRgb->setBoardSocket(dai::CameraBoardSocket::CAM_A);
    camRgb->setResolution(dai::ColorCameraProperties::SensorResolution::THE_4_K);
    videoEnc->setDefaultProfilePreset(camRgb->getFps(), dai::VideoEncoderProperties::Profile::MJPEG);

    // Linking
    camRgb->video.link(xoutRgb->input);
    camRgb->video.link(videoEnc->input);
    videoEnc->bitstream.link(xoutJpeg->input);

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

    // Queues
    auto qRgb = device.getOutputQueue("rgb", 30, false);
    auto qJpeg = device.getOutputQueue("jpeg", 30, true);

    std::string dirName = "rgb_data";
    createDirectory(dirName);

    while(true) {
        auto inRgb = qRgb->tryGet<dai::ImgFrame>();
        if(inRgb != NULL) {
            cv::imshow("rgb", inRgb->getCvFrame());
        }

        auto encFrames = qJpeg->tryGetAll<dai::ImgFrame>();
        for(const auto& encFrame : encFrames) {
            uint64_t time = duration_cast<milliseconds>(system_clock::now().time_since_epoch()).count();
            std::stringstream videoStr;
            videoStr << dirName << "/" << time << ".jpeg";
            auto videoFile = std::ofstream(videoStr.str(), std::ios::binary);
            videoFile.write((char*)encFrame->getData().data(), encFrame->getData().size());
        }

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

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