Lidar_AI_Solution
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A project demonstrating Lidar related AI solutions, including three GPU accelerated Lidar/camera DL networks (PointPillars, CenterPoint, BEVFusion) and the related libs (cuPCL, 3D SparseConvolution, Y...
when I try to inference bevfusion model on more than 800000 points, an error occurred and core dumped: CUDA Runtime error cudaStreamSynchronize(stream) # an illegal memory access was encountered, code...
Dear author: I use your CUDA_BEVFusion to perform inference on my device, but the output results obtained are all NAN. Do you know why this is? I even changed devices...
Hi, Does this project work on the H100? It seems that libspconv.so does not support sm_90. Is it possible to get a binary that supports it? ``` $ cuobjdump --list-elf...
Hi, Thanks for the great work. When I tried to deploy libspconv in a real-time autonomous driving system, I had to constantly copy the sparse network's inference output into a...
Hi, When I use `point_cloud_range=[-54, -100, -5 54, 100, 3]`, the prediction results are quite reasonable. - `point_cloud_range=[-54, -100, -5 54, 100, 3]` - `voxel_size=[0.075, 0.1389, 0.2]` However, in the...
Hi @hopef ! I found a huge gap of inference latency on orin of BEVFusion's lidar-scn backbone, between using **the engine returned by spconv::load_engine_from_onnx(30ms)** and using **the original pytorch implementation(100ms)**....
when I inference the same Bin file, The number of voxels not equal! while I use Centerpoint , I got 87081 voxels after voxel_generator, and 111576 voxels in CUDA-Centerpoint after...
Hi, @hopef This program requires both point cloud and images. Is it possible to have only point cloud or images, so that the program's robustness may be better?
I want to use custom data, two ways. First one, transfer kitti type data to nuscenes, I dont find correct way, failed. Second one, train centerpoint with kitti, I get...
i am working on CUDA_Bevfusion and i am getting error regarding cuda, cuDNN and Tensorrt, So please can anyone provide dockerfile ??? Thanks in Advance...