Update inference.py #42
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@DarthThomas why using nearest resize? |
Because it's resizing a predicted 0-1 mask. |
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@YuxinZou Here is an example case: original image size: (506, 675, 3) you get output mask shape: (class_number, 1153, 1345) after 'transpose' and this 'inverse_resize', you get: (578, 674, 2) after 'inverse_pad', you get: (506, 674, 2) which is not the same as the original input and will invoke an error in function 'result' when generating 'cover' |
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I'm closing this PR since @YuxinZou is working on it |
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Bugfix: inconsistent naming & hw mismatch
(Note that this inverse_resize does not always work due to the use of int(): it's possible to generate a one-pixel difference between inversed prediction and the original image emerges)