kraken is a turn-key OCR system optimized for historical and non-Latin script material.

kraken's main features are:

  • Fully trainable layout analysis and character recognition
  • Right-to-Left, BiDi, and Top-to-Bottom script support
  • ALTO, PageXML, abbyXML, and hOCR output
  • Word bounding boxes and character cuts
  • Multi-script recognition support
  • Public repository of model files
  • Lightweight model files
  • Variable recognition network architectures


When using a recent version of pip all dependencies will be installed from binary wheel packages, so installing build-essential or your distributions equivalent is often unnecessary. kraken only runs on Linux or Mac OS X. Windows is not supported.

Install the latest development version through conda:

$ wget
$ conda env create -f environment.yml


$ wget
$ conda env create -f environment_cuda.yml

for CUDA acceleration with the appropriate hardware.

It is also possible to install the latest stable release from pypi:

$ pip install kraken

Finally you'll have to scrounge up a model to do the actual recognition of characters. To download the default model for printed English text and place it in the kraken directory for the current user:

$ kraken get 10.5281/zenodo.2577813

A list of libre models available in the central repository can be retrieved by running:

$ kraken list


Recognizing text on an image using the default parameters including the prerequisite steps of binarization and page segmentation:

$ kraken -i image.tif image.txt binarize segment ocr

To binarize a single image using the nlbin algorithm:

$ kraken -i image.tif bw.png binarize

To segment an image (binarized or not) with the new baseline segmenter:

$ kraken -i image.tif lines.json segment -bl

To segment and OCR an image using the default model(s):

$ kraken -i image.tif image.txt segment -bl ocr

All subcommands and options are documented. Use the help option to get more information.