This looks for one of the header files which are included by Tesseract.
It currently uses a hard coded path which works for Debian / Ubuntu.
Simplify also the rules for linking Tensorflow.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
It expects include files in /usr/include/tensorflow.
* Add configure option --with-tensorflow (disabled by default)
* Fix data type tensorflow::int64
* Remove "third_party/" in include statements
* Add dummy implementations for Backward and DebugWeights in TFNetwork
* Add files generated with protoc from tfnetwork.proto
(so the Tensorflow sources are not needed for the build)
* Update Makefiles
Signed-off-by: Stefan Weil <sw@weilnetz.de>
That debugging code uses very much memory and is no longer useful.
text data bss dec hex filename
815 0 262144 262959 4032f src/ccutil/globaloc.o
Remove also the function err_exit which was only used in ccmain/reject.cpp.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
It is defined for all platforms when math.h or cmath is included
after defining the macro _USE_MATH_DEFINES.
Define _USE_MATH_DEFINES before any include statement to make sure
that M_PI gets defined. It is not necessary to define it conditionally
only for Windows.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
The latest code passed all unittests with locale de_DE.UTF-8
and has fixed the locale issues which were reported on GitHub.
Therefore the assertions can be removed.
Any remaining locale issue will be fixed when it is identified.
To help finding such remaining isses, debug code now uses the
user's locale settings instead of the default "C" locale for all
executables which use TessBaseAPI.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
Using std::stringstream allows conversion of float to string
independent of the current locale setting.
Some snprintf statements are not needed at all because a constant string
can be appended directly.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
Using std::stringstream simplifies the code and allows conversion of
double to string independent of the current locale setting.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
The modifications were done using this command:
run-clang-tidy-8.py -header-filter='.*' -checks='-*,modernize-use-auto' -fix
Signed-off-by: Stefan Weil <sw@weilnetz.de>
The modifications were done using this command:
run-clang-tidy-8.py -header-filter='.*' -checks='-*,modernize-use-override' -fix
Signed-off-by: Stefan Weil <sw@weilnetz.de>
This requires libarchive-dev.
Tesseract can now load traineddata files in any of the archive formats
which are supported by libarchive. Example of a zipped BagIt archive:
$ unzip -l /usr/local/share/tessdata/zip.traineddata
Archive: /usr/local/share/tessdata/zip.traineddata
Length Date Time Name
--------- ---------- ----- ----
55 2019-03-05 15:27 bagit.txt
0 2019-03-05 15:25 data/
1557 2019-03-05 15:28 manifest-sha256.txt
1082890 2019-03-05 15:25 data/eng.word-dawg
1487588 2019-03-05 15:25 data/eng.lstm
7477 2019-03-05 15:25 data/eng.unicharset
63346 2019-03-05 15:25 data/eng.shapetable
976552 2019-03-05 15:25 data/eng.inttemp
13408 2019-03-05 15:25 data/eng.normproto
4322 2019-03-05 15:25 data/eng.punc-dawg
4738 2019-03-05 15:25 data/eng.lstm-number-dawg
1410 2019-03-05 15:25 data/eng.freq-dawg
844 2019-03-05 15:25 data/eng.pffmtable
6360 2019-03-05 15:25 data/eng.lstm-unicharset
1012 2019-03-05 15:25 data/eng.lstm-recoder
1047 2019-03-05 15:25 data/eng.unicharambigs
4322 2019-03-05 15:25 data/eng.lstm-punc-dawg
16109842 2019-03-05 15:25 data/eng.bigram-dawg
80 2019-03-05 15:25 data/eng.version
6426 2019-03-05 15:25 data/eng.number-dawg
3694794 2019-03-05 15:25 data/eng.lstm-word-dawg
--------- -------
23468070 21 files
`combine_tessdata -d` and `combine_tessdata -u` also work.
The traineddata files in the new format can be generated with
standard tools like zip or tar.
More work is needed for other training tools and big endian support.
Signed-off-by: Stefan Weil <sw@weilnetz.de>
