OCR engine compatible with ocropus
Project description
Description
kraken is a fork of ocropus intended to rectify a number of issues while preserving (mostly) functional equivalence. Its main goals are:
Explicit input/output handling ✓
Clean public API
Word and character bounding boxes in hOCR ✓
Tests
Removal of runtime dependency on gcc ✓
Removal of unused spaghetti code ✓
clstm compatibility ✓
Ticked of goals have been realized while some others still require further work. Pull requests and code contributions are always welcome.
Installation
While kraken does not require a working C compiler on run-time anymore numpy and scipy compilation still requires build-essential or your distributions equivalent. Because the build behavior of pip versions older than 6.1.0 interferes with the scipy build process numpy has to be installed before doing the actual install:
# pip install numpy
If clstm support is desired (highly recommended) the associated python extension has to be build and installed.
Install kraken either from pypi:
$ pip install kraken
or by running pip in the git repository:
$ pip install .
Finally you’ll have to scrounge up an RNN to do the actual recognition of characters. To download ocropus’ default RNN and place it in the kraken directory for the current user:
$ kraken download
Quickstart
Recognizing text on an image using the default parameters including the prerequisite steps of binarization and page segmentation:
$ kraken -i image.tif image.txt
To binarize a single image using the nlbin algorithm:
$ kraken -i image.tif bw.tif binarize
To segment a binarized image into reading-order sorted lines:
$ kraken -i bw.tif lines.txt segment bw.png
To OCR a binarized image using the default RNN and the previously generated page segmentation:
$ kraken -i bw.tif image.txt ocr --lines lines.txt
Documentation
Have a look at the documentation
