C++ Demo for Computing Camera Pose Using CCTag and OpenCV

can you generate a complete demo that compute the camera pose in the CCTag coordinate frame in C++? In this demo, includes the section of configurating camera parameters from a config file (e.g. camera_info.yaml). The example can test with a camera (e.g. webcam) and the CCTag has ID no. 5

Sure, I can provide you with a complete C++ demo that computes the camera pose in the CCTag coordinate frame. This example will include reading camera parameters from a configuration file (camera_info.yaml), capturing images from a webcam, detecting a CCTag with ID 5, and computing the camera pose relative to the CCTag.

To achieve this, we will use the OpenCV library for image processing and camera calibration, and the CCTag library for tag detection. Note that you need to have both OpenCV and CCTag libraries installed on your system.

Here is the complete demo:

1. camera_info.yaml:

camera_matrix:
  rows: 3
  cols: 3
  data: [fx, 0, cx, 0, fy, cy, 0, 0, 1]

distortion_coefficients:
  rows: 1
  cols: 5
  data: [k1, k2, p1, p2, k3]

Replace fx, fy, cx, cy, k1, k2, p1, p2, and k3 with your camera's intrinsic parameters.

2. main.cpp:

#include <iostream>
#include <fstream>
#include <opencv2/opencv.hpp>
#include <cctag/CCTag.hpp>

void readCameraParameters(const std::string& filename, cv::Mat& cameraMatrix, cv::Mat& distCoeffs) {
    cv::FileStorage fs(filename, cv::FileStorage::READ);
    if (!fs.isOpened()) {
        std::cerr << "Failed to open " << filename << std::endl;
        return;
    }

    fs["camera_matrix"] >> cameraMatrix;
    fs["distortion_coefficients"] >> distCoeffs;
}

int main() {
    // Load camera parameters
    cv::Mat cameraMatrix, distCoeffs;
    readCameraParameters("camera_info.yaml", cameraMatrix, distCoeffs);

    // Open webcam
    cv::VideoCapture cap(0);
    if (!cap.isOpened()) {
        std::cerr << "Error: Could not open webcam" << std::endl;
        return -1;
    }

    // Initialize CCTag detector
    cctag::CCTag cctagDetector;
    cctagDetector.setTagID(5); // Set the ID of the CCTag to detect

    while (true) {
        cv::Mat frame;
        cap >> frame;
        if (frame.empty()) {
            std::cerr << "Error: Could not capture frame" << std::endl;
            break;
        }

        // Detect CCTag
        std::vector<cctag::Tag> tags = cctagDetector.detect(frame);
        for (const auto& tag : tags) {
            if (tag.id == 5) {
                // Draw the detected tag
                cv::polylines(frame, tag.corners, true, cv::Scalar(0, 255, 0), 2);

                // Compute pose
                std::vector<cv::Point3f> objectPoints = tag.getObjectPoints();
                std::vector<cv::Point2f> imagePoints = tag.getImagePoints();

                cv::Mat rvec, tvec;
                cv::solvePnP(objectPoints, imagePoints, cameraMatrix, distCoeffs, rvec, tvec);

                // Draw the pose
                std::vector<cv::Point3f> axisPoints = {
                    {0, 0, 0},
                    {0.1, 0, 0},
                    {0, 0.1, 0},
                    {0, 0, 0.1}
                };
                std::vector<cv::Point2f> imageAxisPoints;
                cv::projectPoints(axisPoints, rvec, tvec, cameraMatrix, distCoeffs, imageAxisPoints);

                cv::line(frame, imageAxisPoints[0], imageAxisPoints[1], cv::Scalar(0, 0, 255), 2);
                cv::line(frame, imageAxisPoints[0], imageAxisPoints[2], cv::Scalar(0, 255, 0), 2);
                cv::line(frame, imageAxisPoints[0], imageAxisPoints[3], cv::Scalar(255, 0, 0), 2);

                // Print pose
                std::cout << "Rotation Vector: " << rvec.t() << std::endl;
                std::cout << "Translation Vector: " << tvec.t() << std::endl;
            }
        }

        // Display the frame
        cv::imshow("Frame", frame);
        if (cv::waitKey(30) >= 0) break;
    }

    return 0;
}

3. CMakeLists.txt:

cmake_minimum_required(VERSION 3.10)
project(CCTagPoseEstimation)

find_package(OpenCV REQUIRED)
find_package(CCTag REQUIRED)

add_executable(CCTagPoseEstimation main.cpp)
target_link_libraries(CCTagPoseEstimation ${OpenCV_LIBS} CCTag::CCTag)

Instructions to Compile and Run:

1. Install Dependencies:

   • Install OpenCV: Follow the instructions on the OpenCV installation page.
   • Install CCTag: Follow the instructions on the CCTag GitHub repository.

2. Create Project Directory:

   mkdir CCTagPoseEstimation
   cd CCTagPoseEstimation
   

3. Add Files:

   • Create camera_info.yaml and add the content provided above.
   • Create main.cpp and add the content provided above.
   • Create CMakeLists.txt and add the content provided above.

4. Build the Project:

   mkdir build
   cd build
   cmake ..
   make
   

5. Run the Executable:

   ./CCTagPoseEstimation
   

This demo will open the webcam, detect the CCTag with ID 5, compute the camera pose relative to the tag, and display the pose on the screen. The rotation and translation vectors will be printed to the console.