I've given up on retraining tesseract. I can't get the same accuracy
as the default training data with the sample box data.

But I solved my problem of app size by unpacking the training data,
deleting the bits I don't need and then packaging it back up.

combine_tessdata -u eng.traineddata eng.

delete the bits you don't need - in my case I don't need any of the
dawg files as I'm just recognising single chars

then do:

combine_tessdata eng.



On Feb 12, 2:59 pm, Chris <[email protected]> wrote:
> I think you are right - I don't think the sample box data provided for
> download can be the same data that is used by google to create the
> trained data.
>
> On Feb 12, 12:42 pm, Zdenko Podobný <[email protected]> wrote:
>
>
>
>
>
>
>
> > Hi Chris,
>
> > I have the same experience - that leads me to conclusion it does not
> > make sense to train "common" fonts...
> > I think google use different process  (more detailed; more/other tools?)
> > comparing to information available on wiki... IMHO situation is
> > improving with each release, so I wait for additional information
> > regarding 3.02 training.
>
> > On other hand there is place for community to train "non-standard" fonts
> > (e.g. in my case fraktur). I planned to write blog about my experience
> > when I helped to Slovak version of project Gutenberg, but there is
> > always something more urgent... ;-)
>
> > Zdenko
>
> > Dn(a 11.02.2012 14:47, Chris  wrote / nap�sal(a):
>
> > > I also tried training with all the data. I seem to have the same
> > > problem with accuracy being much less than what you get with the
> > > default one.
>
> > > One thing that looks a bit off is my unicharset file contains lots of
> > > NULLS and contents doesn't seem to match the documentation on doing
> > > training:
>
> > > 108
> > > NULL 0 NULL 0
> > > t 3 0,255,0,255 NULL 41 # t [74 ]a
> > > h 3 0,255,0,255 NULL 81 # h [68 ]a
> > > a 3 0,255,0,255 NULL 57 # a [61 ]a
> > > n 3 0,255,0,255 NULL 14 # n [6e ]a
> > > P 5 0,255,0,255 NULL 30 # P [50 ]A
> > > o 3 0,255,0,255 NULL 25 # o [6f ]a
> > > e 3 0,255,0,255 NULL 58 # e [65 ]a
> > > : 10 0,255,0,255 NULL 8 # : [3a ]p
> > > r 3 0,255,0,255 NULL 52 # r [72 ]a
> > > etc...
>
> > > Also when combining the files I get this output:
>
> > > Combining tessdata files
> > > TessdataManager combined tesseract data files.
> > > Offset for type 0 is -1
> > > Offset for type 1 is 108
> > > Offset for type 2 is -1
> > > Offset for type 3 is 3961
> > > Offset for type 4 is 701702
> > > Offset for type 5 is 702267
> > > Offset for type 6 is -1
> > > Offset for type 7 is 716918
> > > Offset for type 8 is -1
> > > Offset for type 9 is 717216
> > > Offset for type 10 is -1
> > > Offset for type 11 is -1
> > > Offset for type 12 is -1
>
> > > So I obviously don't have all the necessary files. Would this effect
> > > accuracy when recognising single characters?
>
> > > On Feb 11, 10:17 am, Chris<[email protected]>  wrote:
> > >> Hi All,
>
> > >> I'm using tesseract quite successfully in my code. I have a
> > >> preprocessing step that locate the characters I need to recognise and
> > >> then I feed them into tesseract using the PSM_SINGLE_CHAR mode.
>
> > >> This works great with the default eng.traineddata
>
> > >> I'm also constraining the tessedit_char_whitelist to just have numbers
> > >> and upper case letters as that is the only thing I have in my
> > >> character set.
>
> > >> I want to reduce the size of my app and the traineddata is by far the
> > >> largest chunk of data at the moment.
>
> > >> What I've tried to do is retrain tesseract so that it only has the
> > >> characters I need in the training data. I've done this successfully,
> > >> but when I use my newly created eng.traineddata the accuracy is much
> > >> worse than if I use the default eng.traineddata.
>
> > >> Any ideas why this should be? I thought if anything that accuracy
> > >> would improve if I'd removed all the unnecessary characters from the
> > >> data.
>
> > >> I'm doing my training by taking the box files and stripping out all
> > >> the characters I don't need and then running through the training
> > >> instructions.
>
> > >> I'm using tesseract3.01
>
> > >> Any thoughts?
>
> > >> Cheers
> > >> Chris.

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