Open code4indo opened 1 year ago
The SAM itself is not heavy. But semantic segment anything requires four large model which is very memory consuming. At now, simply use --semantic_segment_device as 'CPU' to run. We are working on make this model lightweight now.
Hi, we have implement a light version.
Can be run on 8G GPU less than 20s.
Why is it that when working on semantic segmentation, I constantly encounter out of memory errors, even though I have two GPUs with 15GB each? Is it possible to distribute the model workload across the GPUs in parallel?