range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f), scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size); range_image.integrateFarRanges (far_ranges); if (setUnseenToMaxRange) range_image.setUnseenToMaxRange ...
/data/pointcloud_alg/mmdeploy/mmdeploy/codebase/mmdet3d/models/pillar_encode.py:41: TracerWarning: torch.tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same ...
]test_pipeline=[dict(type='LoadPointsFromFile',coord_type='LIDAR',load_dim=4,# replace with your point cloud data dimensionuse_dim=4),dict(type='Pack3DDetInputs',keys=['points']) ]# construct a pipeline for data and gt loading in show functioneval_pipeline=[dict(type='LoadPointsFrom...
Algorithm 4. Step 3: extract point cloud of the substrate from toolpath. cloud. This process was repeated until every moving line in every print layer of the hand glove toolpath had been processed. All the processed lines were stored and eventually output as a toolpath in the ...
Around the ground truth object point cloud at time t, we crop a set of C candidate BBs in order to create the candidate shapes {xtc}c∈[1,..,C]. The candidate BBs are sampled from a multivariate Gaussian distribution for the three planar degrees of freedom (tX , tY , α...
We create each testing example by cropping the 3D point cloud from the 3D bounding boxes. The segmentation mask is used to remove outlier depth in the bounding box. Then we directly apply our model trained on CAD models to NYU dataset. This is absolutely non-trivial because the statistics ...
point_cloud_range=point_cloud_range, norm_cfg=dict(type='BN1d', eps=1e-3, momentum=0.01)), pts_middle_encoder=dict( type='PointPillarsScatter', in_channels=32, output_shape=[256, 256]), pts_backbone=dict( type='SECOND', in_channels=32, ...
print("points shape: "+str(points.shape)+" coors: "+str(coors.shape)+" voxel size: "+str(voxel_size)+" coors_range: "+str(coors_range))results=dynamic_point_to_voxel_forward(points,coors,voxel_size,coors_range) the output when it fails (the same error as before) ...