Out of bounds error

[jwang281]

Hi, we are getting this exception after running for a couple of days -- any idea why?

Caused by: java.lang.ArrayIndexOutOfBoundsException: -1
        at edu.berkeley.cs.nlp.ocular.preprocessing.VerticalModel.minSize(VerticalModel.java:202)
        at edu.berkeley.cs.nlp.ocular.preprocessing.VerticalProfile.decode(VerticalProfile.java:171)
        at edu.berkeley.cs.nlp.ocular.preprocessing.LineExtractor.extractLines(LineExtractor.java:23)
        at edu.berkeley.cs.nlp.ocular.data.LazyRawImageDocument.doLoadObservationsFromFile(LazyRawImageDocument.java:86)
        at edu.berkeley.cs.nlp.ocular.data.LazyRawImageDocument.loadLineImages(LazyRawImageDocument.java:64)
        at edu.berkeley.cs.nlp.ocular.model.DecoderEM.computeEStep(DecoderEM.java:64)
        at edu.berkeley.cs.nlp.ocular.train.FontTrainer.doFontTrainPass(FontTrainer.java:185)
        at edu.berkeley.cs.nlp.ocular.train.FontTrainer.trainFont(FontTrainer.java:95)
        at edu.berkeley.cs.nlp.ocular.main.TrainFont.run(TrainFont.java:76)
        at edu.berkeley.cs.nlp.ocular.main.OcularRunnable.doMain(OcularRunnable.java:25)
        at edu.berkeley.cs.nlp.ocular.main.TrainFont.main(TrainFont.java:41)

[halperta]

Was it trying to decode a blank page? Sometimes that causes the error.

On Wed, Feb 21, 2018 at 9:38 AM, jwang281 notifications@github.com wrote:

Hi, we are getting this exception after running for a couple of days -- any idea why?

Caused by: java.lang.ArrayIndexOutOfBoundsException: -1 at edu.berkeley.cs.nlp.ocular.preprocessing.VerticalModel.minSize(VerticalModel.java:202) at edu.berkeley.cs.nlp.ocular.preprocessing.VerticalProfile.decode(VerticalProfile.java:171) at edu.berkeley.cs.nlp.ocular.preprocessing.LineExtractor.extractLines(LineExtractor.java:23) at edu.berkeley.cs.nlp.ocular.data.LazyRawImageDocument.doLoadObservationsFromFile(LazyRawImageDocument.java:86) at edu.berkeley.cs.nlp.ocular.data.LazyRawImageDocument.loadLineImages(LazyRawImageDocument.java:64) at edu.berkeley.cs.nlp.ocular.model.DecoderEM.computeEStep(DecoderEM.java:64) at edu.berkeley.cs.nlp.ocular.train.FontTrainer.doFontTrainPass(FontTrainer.java:185) at edu.berkeley.cs.nlp.ocular.train.FontTrainer.trainFont(FontTrainer.java:95) at edu.berkeley.cs.nlp.ocular.main.TrainFont.run(TrainFont.java:76) at edu.berkeley.cs.nlp.ocular.main.OcularRunnable.doMain(OcularRunnable.java:25) at edu.berkeley.cs.nlp.ocular.main.TrainFont.main(TrainFont.java:41)

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[jwang281]

The page is not blank but I did get the output that says "no evaluation diplomatic text found at the image".

[halperta]

The other thing that has caused that error for me is when the image is very low quality. But if it's not blank pages or image quality, I don't know what it would be! I'm just a user, not a developer.

On Sun, Feb 25, 2018 at 3:12 PM, jwang281 notifications@github.com wrote:

The page is not blank but I did get the output that says "no evaluation diplomatic text found at the image".

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[jwang281]

Thanks anyway!

[davidweichiang]

Hi @tberg12, it would be great if you know how to fix this quickly....we can look at it, but it will probably take us a lot longer...thanks!

[davidweichiang]

I attempted a fix: ndnlp/ocular@00f8db0. @jwang281, can you test it on the file that was causing the problem?

[tberg12]

Sorry for the lag, I'm currently traveling. I'll take a look soon. Hopefully David's fix worked. Also, let me know if any of you want to be added as contributors. The more the merrier!

On Fri, Mar 2, 2018 at 6:52 AM, David Chiang notifications@github.com wrote:

I attempted a fix: ndnlp/ocular@00f8db0 https://github.com/ndnlp/ocular/commit/00f8db0. @jwang281 https://github.com/jwang281, can you test it on the file that was causing the problem?

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[davidweichiang]

It fixed the symptom but perhaps not the problem. I was expecting it to skip those pages and then on later iterations to not skip them. But it sounds like it just keeps skipping them on every iteration. Do you have any idea why the vertical segmentation would fail?

[tberg12]

The vertical segmentation system is an unsupervised semi-markov model. We run a bunch of random restarts and the top scoring one is a good segmentation most of the time... but sometimes for no apparent reason a page will cause trouble. We’ve got a better segmentation method in the pipeline, but it’s not in ocular yet.

On Fri, Mar 2, 2018 at 1:32 PM David Chiang notifications@github.com wrote:

It fixed the symptom but perhaps not the problem. I was expecting it to skip those pages and then on later iterations to not skip them. But it sounds like it just keeps skipping them on every iteration. Do you have any idea why the vertical segmentation would fail?

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