I run the TUM whith commad "./build/mono_tum Vocabulary/ORBvoc.txt configs/Monocular/TUM/freiburg3_office.yaml ./rgbd_dataset_freiburg3_long_office_household/ "on docker with GPU GTX1660 and I get the error
I
Copliot give the following advice:
"Reduce the n_neurons parameter in FullyFusedMLP model configuration. This will decrease the memory requirement of the model.
Alternatively, use CutlassMLP, which might offer better compatibility but could be slower."
I woner if these two can work. And I noticed the gpu memory usage is about 6GB. But the GPU memory usage in the paper and other people is about 9GB. Can I work with my GPU or I have to change one.
I run the TUM whith commad "./build/mono_tum Vocabulary/ORBvoc.txt configs/Monocular/TUM/freiburg3_office.yaml ./rgbd_dataset_freiburg3_long_office_household/ "on docker with GPU GTX1660 and I get the error I
Copliot give the following advice: "Reduce the n_neurons parameter in
FullyFusedMLPmodel configuration. This will decrease the memory requirement of the model. Alternatively, use CutlassMLP, which might offer better compatibility but could be slower."I woner if these two can work. And I noticed the gpu memory usage is about 6GB. But the GPU memory usage in the paper and other people is about 9GB. Can I work with my GPU or I have to change one.