Hi
I was trying the vertebrae segmentation pipeline sample-app and I runned out of memory on a small CT
Does it make sense to spend time trying to reconfigure it to get it working? Will the quality of the modified algorithm be too low?
Could you give pointers/recommendations on cloud options?
Thanks a lot
I was having a similar problem running out of GPU memory. I created a new conda environment and explicitly installed the CPU version of pytorch (using their install wizard: Start Locally | PyTorch). Running monailabel server in this environment bypassed the GPU. Inference runs multithreaded is still pretty quick.
I was trying to keep it very simple by using the Docker monai-label server because I just want to test one CT currently.
I guess I’ll have to take more time than I initially planned to deploy anaconda, pytorch and monai-label
It’s really pretty straightforward to install miniconda and then install torch and monai label. It really shouldn’t take more than a few minutes. Let us know how it goes.