aruco | Aruco marker detector and pose estimation | Robotics library
kandi X-RAY | aruco Summary
kandi X-RAY | aruco Summary
Aruco marker detector and pose estimation for AR and Robotics with ROS support
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QUESTION
I have a dual camera hardware module for my raspberry pi zero. It requires some software to get working though. I have cloned the required repo from, as seen here:
...ANSWER
Answered 2022-Apr-15 at 16:36This has nothing to do with make per se. The problem is that your compiler invocation is wrong for the include statement you have.
You can debug this yourself: first, see the command make invoked:
QUESTION
I'm in need of a fiducial marker for a rover project as its primary control is image processing for steering down a driveway and when it gets to the end i need it to go to a precise location.
I was going to use ArUco tags but my version of OpenCV for the OpenVino framework doesn't support it. Then i tried to use AprilTags but i couldn't get it to install on my Windows 10 machine and later discovered its not supported on that OS. While my robot uses RaspPi i absolutely need my desktop environment for development and debugging.
Anyone get AprilTag library compiled for Windows Python 3? If not does anyone know of an alternate tag library (not ArUco) that is similar? I don't need anything fancy here - just something printed on a 4" x 4" (ish) piece of paper that my image processing pipeline can easily pick out of the image and i can then navigate to it. I don't even need to encode data on it - just need something unique to lock into.
Much appreciated!
...ANSWER
Answered 2022-Jan-04 at 07:43Intel® Distribution of OpenVINO™ Toolkit can also be installed through PyPI repository instead of installing the binary package that had compiled OpenCV community version.
- Runtime package with the Inference Engine inside.
- Developer package that includes the runtime package as a dependency, Model Optimizer, Accuracy Checker and Post-Training Optimization Tool.
Next, you can get the ArUco library that included in the opencv-contrib-python package which you can install via:
QUESTION
I want to be able to detect aruco markers on a 3D object and I'm therefore trying to create my own custom aruco board in OpenCV, with the locations of the markers.
I have produced a snippet of the code, to reproduce the error.
...ANSWER
Answered 2022-Feb-28 at 12:16I managed to solve the problem myself. The problem was I was running a too old version of OpenCV. The version needs to be 3.4.x or above since it was a bug that got fixed in 3.4.
QUESTION
I'm trying to find distortion coeffitients using Charuco Board from the Aruco OpenCV library. I'm using Qt and OpenCV libraries compiled for Qt.
First I've needed to do is to create the Charuco Board. I've done it using this:
...ANSWER
Answered 2022-Feb-22 at 07:55The problem was in OpenCV library. Maybe it was badly compiled, or the problem is in the library itself. I have used OpenCV version 4.5.3 before. Then I compiled 4.5.4 version, and the program started to work well.
QUESTION
I'm trying to detect the ArUco markers in this image:
using this code:
...ANSWER
Answered 2022-Feb-16 at 07:56The picture is a mirror image of the markers.
ArUco markers will not be decoded when they're mirrored.
Prevent/undo the mirroring. Find the device/driver setting that does this.
flipped = cv.flip(img, 1)
flips the image around the Y-axis.
QUESTION
I calibrated a camera according to:
...ANSWER
Answered 2022-Feb-01 at 18:37Rt
is just the transformation (rotation, translation) from world to camera frame.
You expected a projection?
If you want to project the point, you still need to apply the camera matrix (and then maybe the distortion coefficients to be precise, but let's not get into that).
QUESTION
I Detected the ArUco marker and estimated the pose. See the image below. However, Xt (X translation) I get is a positive value. According to the drawAxis
function, the positive direction is away from the image center. So I thought it was supposed to be a negative value. Why I am getting positive instead.
My camera is about 120 mm away from the imaging surface. But I am getting Zt (Z translation) in the range of 650 mm. Is pose estimation giving the pose of marker with respect to physical camera or image plane center? I didn't get why the Zt is so high.
I kept measuring Pose while changing Z
, and obtained roll, pitch, yaw. I noticed roll ( rotation w.r.t. cam X-axis) is changing its sign back and forth magnitude change 166-178, but the sign of Xt did not change with the sign change in roll. Any thoughts on why it behaves like that?
Any suggestion to get more consistent data?
ANSWER
Answered 2022-Feb-02 at 14:17Without checking all the code (looks roughly okay), a few basics about OpenCV and aruco:
Both use right-handed coordinate systems. Thumb X, index Y, middle Z.
OpenCV uses X right, Y down, Z far, for screen/camera frames. Origin for screens and pictures is the top left corner. For cameras, the origin is the center of the pinhole model, which would be the center of the aperture. I can't comment on lenses or lens systems. Assume the lens center is the origin. That's probably close enough.
Aruco uses X right, Y far, Z up, if the marker is lying flat on a table. Origin is in the center of the marker. The top left corner of the marker is considered the "first" corner.
The marker can be considered to have its own coordinate system/frame.
The pose given by rvec and tvec is the pose of the marker in the camera frame. That means np.linalg.norm(tvec)
gives you the direct distance from the camera to the marker's center. tvec's Z is just the component parallel to optical axis.
If the marker is in the right half of the picture ("half" defined by camera matrix's cx,cy), you'd expect tvec's X to grow. Lower half, Y positive/growing.
Conversely, that transformation transforms marker-local coordinates to camera-local. Try transforming some marker-local points, such as origin or points on the axes. I believe that cv::transform
can help with that. Using OpenCV's projectPoints
to map 3D space points to 2D image points, you can then draw the marker's axes, or a cube on top of it, or anything you like.
Say the marker sits upright and faces the camera dead-on. When you consider the frame triads of the marker and the camera in space ("world" space), both would be X "right", but one's Y and Z are opposite the other's Y and Z, so you'd expect to see a rotation around the X axis by half a turn (rotating Z and Y).
You could imagine the transformation to happen like this:
- initially the camera looks through the marker, from the marker's back out into the world. The camera would be "upside down". The camera sees marker-space.
- the pose's rotation component rotates the whole marker-local world around the camera's origin. Seen from the world frame (point of reference), the camera rotates, into an attitude you'd find natural.
- the pose's translation moves the marker's world out in front of the camera (Z being positive), or equivalently, the camera backs away from the marker.
If you get implausible values, check aruco_marker_side_length
and camera matrix. f would be around 500-3000 for typical resolutions (VGA-4k) and fields of view (60-80 degrees).
QUESTION
I use this reference https://automaticaddison.com/how-to-perform-pose-estimation-using-an-aruco-marker/ to estimate pose of a marker.
When I obtain cam matrix and distortion matrix I used the full camera resolution.
However, when I change the resolution (image size) before pose estimation, I am getting different results. I am not sure why and which resolution would be correct to use.
Should we always use the same resolution as what was used for camera calibration?
I expected the pose to be somewhat independent from image size other than minor changes. Any thoughts?
...ANSWER
Answered 2022-Feb-01 at 18:51Yes, always use the same resolution.
One could recalculate the camera matrix and distortion coefficients to fit a different resolution but that's a hassle, and requires some knowledge of how the camera made these pictures (binning, cropping). Unless you understand the math behind it, just stick with same resolution.
QUESTION
I try detect Aruco codes on images. I'm working at Jupyter Notebook in Docker, so I working with images, not videos and do not have access to some functions (for example cv2.imshow('QueryImage', QueryImg)
)
Based on code: https://github.com/kyle-bersani/opencv-examples/blob/master/SimpleMarkerDetection/DetectMarkersAndPrint.py
I prepare this script:
...ANSWER
Answered 2021-Dec-22 at 23:27Now everything working, code after improvements:
QUESTION
I am in trouble figuring out why cv2.aruco.detectMarkers() has problems in finding more than just a few markers with my calibration board. Playing around with the paramters didn't essentially improve the quality. The dictionary is correct as I tried it with the digital template before printing. Here is, what I do to detect CHAruco markers from a real image:
...ANSWER
Answered 2021-Nov-10 at 05:59Without looking at your code I may say that the image quality and perspective you selected is a bit poor. You may try to work with more clear view of your markers. For instance, hang the markers on the wall take one or two step back and try to take photo of it with better light and if not necessary do not add extra rotation, and keep the contrast high :). This will probably give better results.
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