Okunator

Hello, Those results are very odd indeed. Did you use some specific normalization during training? When you run inference with the Inferer-classes, you should also pass the same normalization method...

Hello, Those results are very odd indeed. Did you use some specific normalization during training? When you run inference with the Inferer-classes, you should also pass the same normalization method...

Also, I noticed that you were using some parameters that don't exist like 'overlap' and 'patch'. Use 'stride' and 'patch_size' instead.

You're right, ResizeInferer does not use stride and patch_size parameters. My bad.

Hi, thanks for the heads up. I'll check the issue.

I uploaded 1000x1000 images and the crop size was 256x256 when I worked on the annotations. Could it be that the annotator assigns a negative or nan value for the...

Sorry for the delay. Here is a screenshot. After clicking the 'Training' or 'Testing' button the same error occurs. Switching to 'Fill with unknown' or turning off the superpixels does...

I'm running in linux ubuntu 18.04.1 system. Python version is 3.6.9. Here is the 'pip freeze' of the virtual environment I created for QuickAnnotator: ``` albumentations==0.4.3 argon2-cffi==20.1.0 astroid==2.4.2 async-generator==1.10 attrs==20.3.0...

Also, I did not use the patching script that was provided for the initial patching of wsi files. I had patched the wsi images beforehand to .png files.

I'm not too comfortable on sending the .png files. However, I tried to reproduce the error with the Kumar dataset (monuseg) and Consep dataset (hover-net) downloaded from their corresponding websites...