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Hi, I'm going to train Adabins to my custom dataset.
At first, there is a part where the maximum and minimum values are specified in the part where the model is loaded, does this have an effect on training? model = UnetAdaptiveBins.build(n_bins=256, min_val=0, max_val=2.5, norm='linear').to(device)
And is it a problem if I use these values differently when I load the weights later?
Thank you for providing your work.
It is very helpful for studying.
The text was updated successfully, but these errors were encountered:
Thanks for your interest in our work.
I hypothesize that changing min_val and max_val on pretrained model would just change units the output depth map uses. By default, the units are meters but if you change the max_val to new_max_val, then output units would be scaled by (new_max_val - new_min_val) / (max_val - min_val).
I'm curious if you experimented with this and your concluding insights about this situation.
Hi, I'm going to train Adabins to my custom dataset.
At first, there is a part where the maximum and minimum values are specified in the part where the model is loaded, does this have an effect on training?
model = UnetAdaptiveBins.build(n_bins=256, min_val=0, max_val=2.5, norm='linear').to(device)
And is it a problem if I use these values differently when I load the weights later?
Thank you for providing your work.
It is very helpful for studying.
The text was updated successfully, but these errors were encountered: