Mono Full Resolution Saver

This example does its best to save 1280x720 .png files as fast at it can from the Mono sensor. It serves as an example of recording mono pictures to disk.

Be careful, this example saves pictures to your host storage. So if you leave it running, you could fill up your storage on your host.

Similar 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

Python

C++

Also available on GitHub

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#!/usr/bin/env python3

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

# Create pipeline
pipeline = dai.Pipeline()

# Define source and output
monoRight = pipeline.create(dai.node.MonoCamera)
xoutRight = pipeline.create(dai.node.XLinkOut)

xoutRight.setStreamName("right")

# Properties
monoRight.setBoardSocket(dai.CameraBoardSocket.RIGHT)
monoRight.setResolution(dai.MonoCameraProperties.SensorResolution.THE_720_P)

# Linking
monoRight.out.link(xoutRight.input)

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

    # Output queue will be used to get the grayscale frames from the output defined above
    qRight = device.getOutputQueue(name="right", maxSize=4, blocking=False)

    dirName = "mono_data"
    Path(dirName).mkdir(parents=True, exist_ok=True)

    while True:
        inRight = qRight.get()  # Blocking call, will wait until a new data has arrived
        # Data is originally represented as a flat 1D array, it needs to be converted into HxW form
        # Frame is transformed and ready to be shown
        cv2.imshow("right", inRight.getCvFrame())

        # After showing the frame, it's being stored inside a target directory as a PNG image
        cv2.imwrite(f"{dirName}/{int(time.time() * 1000)}.png", inRight.getFrame())

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

Also available on GitHub

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#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 output
    auto monoRight = pipeline.create<dai::node::MonoCamera>();
    auto xoutRight = pipeline.create<dai::node::XLinkOut>();

    xoutRight->setStreamName("right");

    // Properties
    monoRight->setBoardSocket(dai::CameraBoardSocket::RIGHT);
    monoRight->setResolution(dai::MonoCameraProperties::SensorResolution::THE_720_P);

    // Linking
    monoRight->out.link(xoutRight->input);

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

    // Output queue will be used to get the grayscale frames from the output defined above
    auto qRight = device.getOutputQueue("right", 4, false);

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

    while(true) {
        auto inRight = qRight->get<dai::ImgFrame>();
        // Data is originally represented as a flat 1D array, it needs to be converted into HxW form
        // Frame is transformed and ready to be shown
        cv::imshow("right", inRight->getCvFrame());

        uint64_t time = duration_cast<milliseconds>(system_clock::now().time_since_epoch()).count();
        std::stringstream videoStr;
        videoStr << dirName << "/" << time << ".png";
        // After showing the frame, it's being stored inside a target directory as a PNG image
        cv::imwrite(videoStr.str(), inRight->getCvFrame());

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

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