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add 1st draft line GT/training specs #105

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add 1st draft line GT/training specs #105

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kba
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@kba kba commented Jan 29, 2019

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wrznr
wrznr previously requested changes Jan 29, 2019
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I strongly recommend the introduction of a third GT subset devel.

In addition, some minor comments.

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kba commented Jan 31, 2019

I strongly recommend the introduction of a third GT subset devel.

@wrznr Can you elaborate?

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wrznr commented Mar 19, 2019

@kba

Can you elaborate?

Most training procedures allow for the application of three different sets of GT: train, eval and devel. While the purpose for the first two is supposedly clear, the latter is used during training for parameter fixing and error estimation. E.g. ocropus-rtrain has the parameter --tests for this purpose. Note that strictly speaking you may not abuse your evaluation data as development data.

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wrznr commented Mar 19, 2019

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cneud commented May 21, 2019

@wrznr So far I mainly applied k-fold_cross-validation, would you still see added benefits over this by partitioning into three sets?

- groundTruthBag
- model
properties:
engineName:
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delete .Derived from model

- kraken
- tesseract
- calamari
engineVersion:
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delete .Derived from model

required: false
default: 'image/png'
values:
- 'image/png'
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Would a differentiation between Tiff compressed or JPEG2000 make more sense?

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You mean additionally allow image/jp2? Do engines allow JPEG2000 input for training?

BagIt-Profile-Info:
BagIt-Profile-Identifier: https://ocr-d.github.io/gt-profile.json
BagIt-Profile-Version: '1.2.0'
Source-Organization: OCR-D
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What about information about the origin of the digitized lines?

  • minimal bibliographic record based on DC?
  • and artificially generated lines (+ degeneration)
  • what about the degeneration algorithm?

I think that comment may be in the wrong place here. It should probably be placed in this place ## Line metadata##.

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See https://github.com/OCR-D/spec/pull/105/files/6827085d051e945062203b82ef921e54025cfbda#diff-ee256e83a17cfe309565c88ab376091a That is the definition of what's currently supposed to be in there. Bibliographic metadata would be in the METS referred to by metsUrl. How to encode provenance on a line-level I am not sure though. @VolkerHartmann?

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cneud commented Aug 8, 2019

@wrznr Do your remaining @wrznr requested changes relate to this comment only or is there other stuff that needs changing (for the time being)?

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kba commented Aug 8, 2019

@Doreenruirui's work on okralact has diverged significantly from these specs. It makes little sense to publish these specs with the only implementation implementing it differently.

@Doreenruirui can you compare your schemas and documentation with this so we can integrate that part of okralact into the specs?

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@Doreenruirui's work on okralact has diverged significantly from these specs. It makes little sense to publish these specs with the only implementation implementing it differently.

@Doreenruirui can you compare your schemas and documentation with this so we can integrate that part of okralact into the specs?

@kba I am sorry that I am not very familiar with github. Can you point me to the document I should compare with my schemas?

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kba commented Aug 8, 2019

@Doreenruirui We're discussing these changes/new files: https://github.com/OCR-D/spec/pull/105/files.

In particular I would like to harmonize the proposal here (https://github.com/OCR-D/spec/pull/105/files?file-filters%5B%5D=.md#diff-2ae93b1f468c44b9f7e195133a0fb539) of using BagIt for the line GT with your approach in okralact wrt to input format.

Also interesting would be to compare okralact's engine schemas with the schema proposed here https://github.com/OCR-D/spec/pull/105/files?file-filters%5B%5D=.md&file-filters%5B%5D=.yml#diff-690d5874f98dfbd6737bc0168b6084d8 and https://github.com/OCR-D/spec/pull/105/files?file-filters%5B%5D=.md&file-filters%5B%5D=.yml#diff-a1f62fd4dd219fc5c5d5f0ccb419c88b

@wrznr wrznr dismissed their stale review August 9, 2019 08:08

My original review does not relate to the current state very much.

@cneud cneud removed the request for review from VolkerHartmann August 15, 2022 19:20
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7 participants