You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello, thanks for sharing this amazing work with all the codes and weights !
I created my own RGB-D dataset with custom dataloaders following #105 and ran a finetuning
My finetuning results are not very good with base KITTI parameters, so I want to better understand them :
I added encoder freeze, is it a good idea ?
how should I choose crop_size values in data_basic ? I set it to my image size
the optimizer and lr hyperparameters in ..kitti.py configs are set for finetuning, right ?
should we change the Normalize values in the pipeline for custom data ?
is there a special way to handle the sky region in GT depth ? I set it to 0 to ignore it
Sorry for my many questions, I hope you can help me. Thank you !
The text was updated successfully, but these errors were encountered:
Hello, thanks for sharing this amazing work with all the codes and weights ! I created my own RGB-D dataset with custom dataloaders following #105 and ran a finetuning
My finetuning results are not very good with base KITTI parameters, so I want to better understand them :
I added encoder freeze, is it a good idea ?
how should I choose crop_size values in data_basic ? I set it to my image size
the optimizer and lr hyperparameters in ..kitti.py configs are set for finetuning, right ?
should we change the Normalize values in the pipeline for custom data ?
is there a special way to handle the sky region in GT depth ? I set it to 0 to ignore it
Sorry for my many questions, I hope you can help me. Thank you !
Thanks for your questions and I hope these may help:
It will impair some performance. (The performance gain will shrink for fine-tuning.)
I think we have provided a json file to train KITTI and you do not need to change or choose it.
No, this file is not correctly configured. I think the settings have been correctly overridden here.
Not likely.
If you have a well segmented map, you can set the sky groundtruth to 200. Ignoring them is another alternative and the confidence map will help to filter them out.
In general, I think we should use this script. Not need to change any settings additionally.
Hello, thanks for sharing this amazing work with all the codes and weights !
I created my own RGB-D dataset with custom dataloaders following #105 and ran a finetuning
My finetuning results are not very good with base KITTI parameters, so I want to better understand them :
I added encoder freeze, is it a good idea ?
how should I choose crop_size values in data_basic ? I set it to my image size
the optimizer and lr hyperparameters in ..kitti.py configs are set for finetuning, right ?
should we change the Normalize values in the pipeline for custom data ?
is there a special way to handle the sky region in GT depth ? I set it to 0 to ignore it
Sorry for my many questions, I hope you can help me. Thank you !
The text was updated successfully, but these errors were encountered: