I am using Deeplabv3+ to perform semantic segmentation in an image but the result shows strong discontinuities due to patch-wise predictions. Is there a way of using overlapping patches that are aggregated (or averaged) to produce the output? I tried to use a code showed in this example. However the output has still the patchy pattern. Any sollutions?

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Hi
Can you specify the input which you are passing? I think the network give the pixel wise output, how it became discontinuous?
Because I am working with remote sensing images I should pass image tiles that are merged together after prediction. I could solve the problem using 'blockproc' and defining the 'BorderSize' parameter according to the amount of overlap desired.

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Mahesh Taparia
Mahesh Taparia 2021년 10월 13일

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Hi
In this case, you can use 'blockproc' function. Create the image block and pass it to network. For more information, you can refer this documentation.

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