Afterward, the border of the mask was manually defined on the facial profile and was subsequently used to create a customized face mask model which followed the pre-defined border. Eventually, the designed face mask model was output in the format of STL, which was imported into Fusion 360 ...
/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 ...
importnumpyasnpfrompypcdimportpypcdpcd_data=pypcd.PointCloud.from_path('point_cloud_data.pcd')points=np.zeros([pcd_data.width,4],dtype=np.float32)points[:,0]=pcd_data.pc_data['x'].copy()points[:,1]=pcd_data.pc_data['y'].copy()points[:,2]=pcd_data.pc_data['z'].copy()points...
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 ...
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) ...
Yes, but there is also a minor bug in your config. Since you change the voxel size and point cloud range, you need to modify theoutput_shapeinpts_middle_encode, which is very likely to lead to yourCUDA error: an illegal memory access was encountered. In your case, it should be [20...