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Published 20 hours ago • verified publisher icon Lydorn

Polygonise mask on custom dataset

Open yeshwanth95 opened this issue 3 years ago • 1 comments

Hi @Lydorn ! I've been finding this repo really useful in my research and have a certain issue with one of the experiments I'm running using your method. I am trying to use your frame field learning approach on a custom version of the INRIA dataset where each image tile has been spit into a hundred 500x500 patches. When I try to run the polygonize_mask.py script on this dataset using one of your pretrained runs, I get the following error:

RuntimeError: The size of tensor a (1024) must match the size of tensor b (500) at non-singleton dimension 3

I am using the 'inria_dataset_osm_mask_only.unet16' run for this. Do you have any suggestions on how I could resolve this? Or would I need to train a different model from scratch to allow processing my modified patch size? Looking forward to your reply. Thank you.

yeshwanth95 avatar Jun 09 '21 13:06 yeshwanth95

The size of the image must be large. I think atleast larger than 1024x1024. I tried with big TIF image file- it works !!

vishwa15 avatar Feb 24 '22 15:02 vishwa15