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. -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/tesseract-ocr?hl=en
