Comments (11)
Thanks. It's mostly so I can make sure the baselines are identical.
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looks like shapely
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the polygon is too big and the recognizer wasn't trained on lines where the letters are only a quarter of the line height.
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Here is on kraken 4.x, same model.
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The models I used in this test:
mcdonald.zip
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It isn't a model issue but the polygonization is wrong. I'll have a look. The rotation code changed between 4.x and 5.x so it's either that or other shapely shenanigans.
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Could you also send me the image file and any ALTO/PageXML you've got? It's difficult to debug without being able to run a test case.
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export_doc23_memar_marqah_mcdonald_alto_202405131147.zip
Sure, here it is the image with ALTO (from 4.x)
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Any update on this matter?
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Apparently, the error persists on some other image data.
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Nope, not true after all. Just crappy output of the polygonizer.
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Related Issues (20)
- Neural network has been trained on mode 1 images (not really an issue) HOT 2
- set `torch.set_float32_matmul_precision('medium' | 'high')` HOT 2
- Segment command fails when trying to output as PageXML/ALTO HOT 2
- Bug: The use of self.hparams.batch_size in the validation_step function. HOT 1
- KeyError: 'completed_epochs' error during segtrain HOT 2
- Upgrade to shapely 2.0 HOT 5
- GPU parallelisation? HOT 1
- Training on kraken 5.2.2 visual issue HOT 1
- lift pytorch restrictive version constraints HOT 7
- Recognition aborts at "baselines" which are only a point HOT 6
- Line detection does not work with version 5.0.0 HOT 1
- Quality of kraken confidence measures HOT 1
- problem with old Alto files HOT 4
- Training a models throws "could not create a primitive descriptor for an LSTM forward propagation primitive" HOT 1
- Region without bounds crashes at serialization
- Support for Python 3.12 HOT 3
- Optimized distribution of packet for inference only HOT 3
- It there a way to simply call kraken recognizer from code? HOT 1
- finetune error on altos containing > or < as txt HOT 7
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