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Hi. I am trying to apply reranking on the MSMT17 dataset, which is one of the largest datasets for person reid. However, when I apply rerank it consumes way too much memory space and RAM gets exceeded due to many images in both query and gallery sets. I don't have extremely powerful resources with plenty of RAM space. The highest space I have right now is 25GB. Is there a way to make adjustments in the rerank.py file so that memory does not get exceeded to that much extent? Need help and guidance in this regard.
Basically, I need an algorithm for reranking that is space-efficient.
The text was updated successfully, but these errors were encountered:
Hi. I am trying to apply reranking on the MSMT17 dataset, which is one of the largest datasets for person reid. However, when I apply rerank it consumes way too much memory space and RAM gets exceeded due to many images in both query and gallery sets. I don't have extremely powerful resources with plenty of RAM space. The highest space I have right now is 25GB. Is there a way to make adjustments in the rerank.py file so that memory does not get exceeded to that much extent? Need help and guidance in this regard.
Basically, I need an algorithm for reranking that is space-efficient.
The text was updated successfully, but these errors were encountered: