未能检测到Zivid标定板

问题

Zivid SDK在手眼标定或现场标定/验证期间无法检测到棋盘格。

可能原因及解决方法

When using the Zivid calibration board, the fiducial/ArUco marker must be visible in the image. Otherwise, the checkerboard detection will fail when performing infield correction or hand-eye calibration. We recommend using the Zivid calibration board, since it is a qualified product. Support for the older 9x6 grey-white checkerboards, which had no fiducial marker and so had no such requirement, was removed in SDK 2.14.

小技巧

使用Zivid Studio检查捕获结果是否良好

请注意，如果函数无法检测到任何特征点，SDK 不会抛出错误。相反，它会返回一个空列表。原因是在点云中找不到棋盘格被认为是一个普通的操作失败而不是（异常）错误。因此，我们建议使用 valid() 运算符验证捕获后的检测结果。下面的代码说明了如何在程序中实现这一点。

C++

const auto detectionResult = Zivid::Calibration::detectCalibrationBoard(frame);

if(detectionResult.valid())
{
    std::cout << "Calibration board detected " << std::endl;
    handEyeInput.emplace_back(robotPose, detectionResult);
    currentPoseId++;
}
else
{
    std::cout << "Failed to detect calibration board. " << detectionResult.statusDescription() << std::endl;
}

C＃

using (var frame = camera.Capture2D3D(settings))
{
    var detectionResult = Detector.DetectCalibrationBoard(frame);

    if (detectionResult.Valid())
    {
        Console.WriteLine("Calibration board detected");
        handEyeInput.Add(new HandEyeInput(robotPose, detectionResult));
        ++currentPoseId;
    }
    else
    {
        Console.WriteLine("Failed to detect calibration board, ensure that the entire board is in the view of the camera");
    }
}

Python

detection_result = zivid.calibration.detect_calibration_board(frame)

if detection_result.valid():
    print("Calibration board detected")
    hand_eye_input.append(zivid.calibration.HandEyeInput(robot_pose, detection_result))
    current_pose_id += 1
else:
    print(f"Failed to detect calibration board. {detection_result.status_description()}")