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Hello
How are you?
Thanks for contribution to this project.
I'm NOT sure if this RMI loss would work well in case that we resize the image & mask to input size(NxN in pixels) without keeping width-height ratio in the data augmentation step.
I am working on image segmentation project.
There are many images & masks with different sizes in my dataset.
The data by dataloader are resized to input size(ex: 256x256) and feed into the model.
So the original width-height ratio of image & mask are NOT kept.
Even in such case, does this RMI loss work well?
The text was updated successfully, but these errors were encountered:
Hello
How are you?
Thanks for contribution to this project.
I'm NOT sure if this RMI loss would work well in case that we resize the image & mask to input size(NxN in pixels) without keeping width-height ratio in the data augmentation step.
I am working on image segmentation project.
There are many images & masks with different sizes in my dataset.
The data by dataloader are resized to input size(ex: 256x256) and feed into the model.
So the original width-height ratio of image & mask are NOT kept.
Even in such case, does this RMI loss work well?
The text was updated successfully, but these errors were encountered: