Running HICO Evaluation about spatially-conditioned-graphs HOT 3 CLOSED

Hi, @vjsrinivas

I did not run the test in the known object (ko) setting. But from the default setting (def), the performance 0.608 looks like it's using a randomly initialised model, instead of our trained model.

So just to make sure, have you downloaded the checkpoint of our trained model? And when generating the .mat files, have you correctly specified the path to the checkpoint?

1. Download the checkpoint

cd /path/to/spatio-attentive-graphs/download
bash download_checkpoint.sh

The checkpoint should have been downloaded to /path/to/spatio-attentive-graphs/checkpoints/spatio-attentive-graph-hicodet-e11.pt

2. Run the caching script

cd /path/to/spatio-attentive-graphs
CUDA_VISIBLE_DEVICES=0 python cache.py --model-path checkpoints/spatio-attentive-graph-hicodet-e11.pt

When running this script, you should see a printed message that says Loading model from checkpoints/spatio-attentive-graphs-hicodet-e11.pt

Let me know if this resolves the issue.

Cheers,
Fred

from spatially-conditioned-graphs.

Ahh, I did not check if the file path was correct! It should be checkpoints/spatio-attentive-graphs-hicodet-e11.pt.
I ran it with the right name and was able to match the reported stats:

Also, is there a reason why the program doesn't just error out if the weight path doesn't exist?

from spatially-conditioned-graphs.

Glad it resolved your issue. When the given path is empty or non-existent, a randomly initialised model will be used. I guess I could add some warnings when the given path is not empty but incorrect. Will do that later.

Cheers,
Fred

from spatially-conditioned-graphs.