Comments (5)
I am seeing now that it is a napari thing.
I will keep an update here
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Hi
this is open for too long.
And your suggestion was indeed the way.
Thanks again for this great tool
i will close this comment
:)
from apoc.
Hi @piango ,
great to see you here! Would you mind printing out the shape
s of all images you pass to clf.train
? labelX
and rawX
are supposed to have the same shape...
Best,
Robert
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... another difference to the continue-training notebook is that you are handing over continue_training=True
also at the first training step. Could this be a problem?
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yeah the shapes are different but the labels and raws are matching when i open them in napari (which is where i created the labels). This is weird. Maybe it is the way I am saving them
For your second comment.
The console spits out == warnings.warn("Cannot continue training if it wasn't trained before. Will train from scratch instead.")
Im running apoc on 2 different machines. :)
And this is the first time I run on the second machine.
:)
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Related Issues (18)
- SimpleITK-based object classifier? HOT 1
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- Question about the ObjectClassifer._select_features() docstring HOT 2
- pytest-fy tests HOT 3
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- Remove dual feature specification in TableRowClassifier
- Explicitly compare given feature list and specified feature list in TableRowClassifier HOT 1
- Remove 'return_numpy' from TableRowClassifier API HOT 1
- Feature request: Print classifier info HOT 8
- Feature request: Classifier uncertainty HOT 14
- File not found error if folder path does not end with `\\` HOT 2
- if there are subfolder in the image folder, train on folders failed
- missing documentation on python interface for pixel classification HOT 1
- make ObjectMerger train on folders work
- Documentation? HOT 2
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