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Thank you very much for a very interesting paper.
I have run the PENet pre-trained model you've provided in evaluation mode on the cropped image.
in the results the code provided (val.csv under results) I got RMSE=757.197 MAE=209.001, compared to RMSE=730.08 MAE=210.55 as it appears in the Kitti benchmark page.
IIs there a different PENet model that matches the submitted results? or there is something in the parameters that I put wrong (I kept the parameters as is in this repository).
Thanks a lot,
Mani
The text was updated successfully, but these errors were encountered:
how to use penet pre-trained model,why it name is end with .tar
it seems cant be loaded by "checkpoint = torch.load(args.evaluate, map_location=device)"
how to use penet pre-trained model,why it name is end with .tar it seems cant be loaded by "checkpoint = torch.load(args.evaluate, map_location=device)"
Thanks for your interest! I am afraid taht it is an inherited bug and you can fix it yourself.
Thank you very much for a very interesting paper.
I have run the PENet pre-trained model you've provided in evaluation mode on the cropped image.
in the results the code provided (val.csv under results) I got RMSE=757.197 MAE=209.001, compared to RMSE=730.08 MAE=210.55 as it appears in the Kitti benchmark page.
IIs there a different PENet model that matches the submitted results? or there is something in the parameters that I put wrong (I kept the parameters as is in this repository).
Thanks a lot,
Mani
The text was updated successfully, but these errors were encountered: