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I have a small question: when working with FCN-32s model, the input should be of multiple of 32.
When the input is not, the resizing to the closest multiple of 32 is performed and nearest neighbor
interpolation of predicted labels is performed to get the predictions of the same size as the input.
This is my understanding of what is performed in your code here: https://github.com/vlfeat/matconvnet-fcn/blob/master/fcnTest.m#L143
Is it correct?
what are the pros and cons compared to the approach of implementation of FCN-32s in Caffe where they use padding to tackle this problem?
The text was updated successfully, but these errors were encountered:
Hello,
Thank you for your repository!
I have a small question: when working with FCN-32s model, the input should be of multiple of 32.
When the input is not, the resizing to the closest multiple of 32 is performed and nearest neighbor
interpolation of predicted labels is performed to get the predictions of the same size as the input.
This is my understanding of what is performed in your code here:
https://github.com/vlfeat/matconvnet-fcn/blob/master/fcnTest.m#L143
Is it correct?
what are the pros and cons compared to the approach of implementation of FCN-32s in Caffe where they use padding to tackle this problem?
The text was updated successfully, but these errors were encountered: