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FangGet / BundleFusion_Ubuntu_Pangolin

a porting for BundleFusion working on ubuntu, with Pangolin as visualizer
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Segmentation fault (core dumped) #1

Closed zhanghua7099 closed 4 years ago

zhanghua7099 commented 4 years ago

Hi! I have built this project successfully. When I run it, sometimes it goes well. But it may output segmentation fault after processing about 200 frames. The error message is that: terminate called after throwing an instance of 'ml::MLibException' what(): copyCacheFrameFrom:26: invalid argument:copyCacheFrameFrom Segmentation fault (core dumped) How to fix this bug?

zhanghua7099 commented 4 years ago

The non-GUI version is OK, but the GUI version may have this problem.

FangGet commented 4 years ago

sorry for late reply, I will check this later.

FangGet commented 4 years ago

@zhanghua7099 I double checked my code and found no issues related to your problem, I guess its due to gpu memory, please check gpu memory usage when segmentation fault occurs.

zhanghua7099 commented 4 years ago

GPU memory causes this error. I rerun this code in RTX 2080TI GPU, and it performs well.

zhanxiaopan commented 1 year ago

@zhanghua7099 I double checked my code and found no issues related to your problem, I guess its due to gpu memory, please check gpu memory usage when segmentation fault occurs.

@FangGet Thanks for your great work, I have meet the same issue with @zhanghua7099. However, my GPU is RTX3090(24GB RAM), the segmentation fault occurs after processing 1830 frames（1.21Million triangles）. It seems reasonable, but how can we iterator the whole 3499 frames for office2 dataset?

1: Disable the gui?

2: Modify some parameters to reduce the GPU memory?

FangGet commented 1 year ago

@zhanxiaopan the real-time visualization needs to ray-trace the whole scenes to output what Pangolin need, and I did this part use GPU, that's why the memory occupancy keeps increasing. By 1) disable the gui, or 2) increase the voxel size, or 3) enable the streaming mode(which only shows the sphere range of scenes) or 4)change the visualization to cpu may help(which may not be real-time).