Deep learning - invalid argument 0: Sizes of tensors must match except in dimension 0

Question

Dear all,

I have issue with deep learning tools. I exported 12 000 training chips from Esri Imagery basemap to TIFF - see settings.png

The TIFFs looks fine as well as the labels file.

On calling data = prepare_data(data_path, class_mapping={1:'Pool'}, batch_size=64) I am getting error - UserWarning: It's not possible to collate samples of your dataset together in a batch.
 warn(message)

For data.show_batch() -  now I am getting result - RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 0. Got 19 and 10 in dimension 3 at ..\aten\src\TH/generic/THTensor.cpp:711

I am not sure what does it mean? Does the Export training data tool corrupt some chips? Is there a way how to find out which chips are corrupted? Or how to fix it?

The chips were created in PRO by Export training data tool, so these could be fine.

Thank you for any idea.

Vladimir

000000002.xml.zip

settings.PNG

arcnews-banner-caribbeangeoportal-wide.jpg

Screenshot (523).png

Anonymous User · Answer

There is no limit on the chip number, but with a greater chip size you would require more memory to handle it. the show batch looks reasonable to me, to get a little bit zoomed in chips you can try reducing the cell size to 0.3 or 0.4.

VHolubec · Answer

Dear Sandeep Kumar, with this settings it works. The problem is, that it seems to me so coarse (in comparision to previous settings) - see

and the batch looks like this - no so ideal - no on every chips the pools is highlighted.

Please could you explain, why the ptevious settings did not work? Is there any limit to chip size and number of chips, which Python API could handle?

Thank you,

Vladimir

Anonymous User · Answer

You can try a bigger chip size like 256px and for pools i would suggest a cell size of around 50cm (.5 in webmercetor) so that the model can learn the surrounding context too.