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This issue is not a question, bug report, or anything other than a feature request directly related to this project.
Proposal
I am following the example shown in zed-examples/object detection/image viewer at master · stereolabs/zed-examples · GitHub. It uses OpenGL to draw objects on the image. Right now the 3D bounding box coordinates from the ZED SDK are normalized, I think it would be great if ZED provides the feasibility of returning the 3D bounding box coordinates in the pixel space by taking projection matrix and image shape as the input. I am doing like below to get the 3D bounding box coordinates in the image space i.e., pixel coordinates
is the projection matrix I got from the OpenGL code. But objects are not getting aligned properly, I think it would be great if the ZED SDK provides the support for this.
Use-Case
Saving the 3D bounding boxes in the pixel space will help to train any custom 3D object detection network without any associated point clouds.
Anything else?
No response
The text was updated successfully, but these errors were encountered:
@obraun-sl I have tried doing this, but the rotation of the resulted bounding boxes is weird. @harishkool please share if you've found a solution to fix the wonky boxes.
Preliminary Checks
Proposal
I am following the example shown in zed-examples/object detection/image viewer at master · stereolabs/zed-examples · GitHub. It uses OpenGL to draw objects on the image. Right now the 3D bounding box coordinates from the ZED SDK are normalized, I think it would be great if ZED provides the feasibility of returning the 3D bounding box coordinates in the pixel space by taking projection matrix and image shape as the input. I am doing like below to get the 3D bounding box coordinates in the image space i.e., pixel coordinates
where
_cam_mat
is the projection matrix I got from the OpenGL code. But objects are not getting aligned properly, I think it would be great if the ZED SDK provides the support for this.
Use-Case
Saving the 3D bounding boxes in the pixel space will help to train any custom 3D object detection network without any associated point clouds.
Anything else?
No response
The text was updated successfully, but these errors were encountered: