Python-based OCR package using recurrent neural networks.

To install, use:

$ sudo apt-get install $(cat PACKAGES)
$ wget -nd http://www.tmbdev.net/en-default.pyrnn.gz
$ mv en-default.pyrnn.gz models/
$ sudo python setup.py install

To test the recognizer, run:

$ ./run-test

OCRopus is really a collection of document analysis programs, not a turn-key OCR system.

In addition to the recognition scripts themselves, there are a number of scripts for ground truth editing and correction, measuring error rates, determining confusion matrices, etc. OCRopus commands will generally print a stack trace along with an error message; this is not generally indicative of a problem (in a future release, we'll suppress the stack trace by default since it seems to confuse too many users).

To recognize pages of text, you need to run separate commands: binarization, page layout analysis, and text line recognition.

# perform binarization
./ocropus-nlbin tests/ersch.png -o book

# perform page layout analysis
./ocropus-gpageseg 'book/????.bin.png'

# perform text line recognition (on four cores, with a fraktur model)
./ocropus-rpred -Q 4 -m models/fraktur.pyrnn.gz 'book/????/??????.bin.png'

# generate HTML output
./ocropus-hocr 'book/????.bin.png' -o ersch.html

# display the output
firefox ersch.html

There are some things the currently trained models for ocropus-rpred will not handle well, largely because they are nearly absent in the current training data. That includes all-caps text, some special symbols (including "?"), typewriter fonts, and subscripts/superscripts. This will be addressed in a future release, and, of course, you are welcome to contribute new, trained models.

You can also generate training data using ocropus-linegen:

ocropus-linegen -t tests/tomsawyer.txt -f tests/DejaVuSans.ttf

This will create a directory "linegen/..." containing training data suitable for training OCRopus with synthetic data.