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The origin code in argoverse_map_tutorial shows the prejection result of the centerlines on image. This step includes filtered the centerlines which is occluded. The function "plot_lane_centerlines_in_img2" provides this. But when filtering, the "clip_point_cloud_to_visible_region" is operating on the unsync lidar(ego) frame and camera frame. To correct this:
Origin:
centerline_egovehicle_fr = city_SE3_egovehicle.inverse().transform_point_cloud(centerline_city_fr)
centerline_uv_cam = cam_SE3_egovehicle.transform_point_cloud(centerline_egovehicle_fr)
# can also clip point cloud to nearest LiDAR point depth
centerline_uv_cam = clip_point_cloud_to_visible_region(centerline_uv_cam, lidar_pts) # Wrong!!!
Repair:
centerline_egovehicle_fr = city_SE3_egovehicle.inverse().transform_point_cloud(centerline_city_fr)
# can also clip point cloud to nearest LiDAR point depth centerline_egovehicle_fr = clip_point_cloud_to_visible_region(centerline_egovehicle_fr, lidar_pts)
centerline_uv_cam = cam_SE3_egovehicle.transform_point_cloud(centerline_egovehicle_fr)
This visualization image result shows correctly.
The text was updated successfully, but these errors were encountered:
The origin code in argoverse_map_tutorial shows the prejection result of the centerlines on image. This step includes filtered the centerlines which is occluded. The function "plot_lane_centerlines_in_img2" provides this. But when filtering, the "clip_point_cloud_to_visible_region" is operating on the unsync lidar(ego) frame and camera frame. To correct this:
Origin:
centerline_egovehicle_fr = city_SE3_egovehicle.inverse().transform_point_cloud(centerline_city_fr)
centerline_uv_cam = cam_SE3_egovehicle.transform_point_cloud(centerline_egovehicle_fr)
# can also clip point cloud to nearest LiDAR point depth
centerline_uv_cam = clip_point_cloud_to_visible_region(centerline_uv_cam, lidar_pts) # Wrong!!!
Repair:
centerline_egovehicle_fr = city_SE3_egovehicle.inverse().transform_point_cloud(centerline_city_fr)
# can also clip point cloud to nearest LiDAR point depth
centerline_egovehicle_fr = clip_point_cloud_to_visible_region(centerline_egovehicle_fr, lidar_pts)
centerline_uv_cam = cam_SE3_egovehicle.transform_point_cloud(centerline_egovehicle_fr)
This visualization image result shows correctly.
The text was updated successfully, but these errors were encountered: