dondrews / pyocr

A Python wrapper for Tesseract and Cuneiform

PyOCR

PyOCR is an optical character recognition (OCR) tool wrapper for python. That is, it helps using OCR tools from a Python program.

It has been tested only on GNU/Linux systems. It should also work on similar systems (*BSD, etc). It may or may not work on Windows, MacOSX, etc.

PyOCR can be used as a wrapper for google's Tesseract-OCR or Cuneiform. It can read all image types supported by Pillow, including jpeg, png, gif, bmp, tiff, and others. It also support bounding box data.

Supported OCR tools

• Libtesseract (C API)
• Tesseract (fork + exec)
• Cuneiform (fork + exec)

Features

• Support all the image formats supported by Pillow
• As output, can provide a simple string or boxes (position + string for each word and line)
• Can focus on digits only (Tesseract only)
• Can save and reload boxes in hOCR format

Limitations

• hOCR: Only a subset of the specification is supported. For instance, pages and paragraph positions are not stored.

Usage

Initialization

from PIL import Image
import sys

import pyocr
import pyocr.builders

tools = pyocr.get_available_tools()
if len(tools) == 0:
    print("No OCR tool found")
    sys.exit(1)
# The tools are returned in the recommended order of usage
tool = tools[0]
print("Will use tool '%s'" % (tool.get_name()))
# Ex: Will use tool 'libtesseract'

langs = tool.get_available_languages()
print("Available languages: %s" % ", ".join(langs))
lang = langs[0]
print("Will use lang '%s'" % (lang))
# Ex: Will use lang 'fra'
# Note that languages are NOT sorted in any way. Please refer
# to the system locale settings for the default language
# to use.

Image to text

txt = tool.image_to_string(
    Image.open('test.png'),
    lang=lang,
    builder=pyocr.builders.TextBuilder()
)

word_boxes = tool.image_to_string(
    Image.open('test.png'),
    lang="eng",
    builder=pyocr.builders.WordBoxBuilder()
)

line_and_word_boxes = tool.image_to_string(
    Image.open('test.png'), lang="fra",
    builder=pyocr.builders.LineBoxBuilder()
)

# Digits - Only Tesseract (not 'libtesseract' yet !)
digits = tool.image_to_string(
    Image.open('test-digits.png'),
    lang=lang,
    builder=pyocr.tesseract.DigitBuilder()
)

Argument 'lang' is optionnal. The default value depends of the tool used.

Argument 'builder' is optionnal. Default value is builders.TextBuilder().

Orientation detection

Currently only available with Tesseract or Libtesseract.

if tool.can_detect_orientation():
    orientation = tool.detect_orientation(
        Image.open('test.png'),
        lang='fra'
    )
    pprint("Orientation: {}".format(orientation))
# Ex: Orientation: {
#   'angle': 90,
#   'confidence': 123.4,
# }

Angles are given in degrees (range: [0-360[). Exact possible values depend of the tool used. Tesseract only returns angles = 0, 90, 180, 270.

Confidence is a score arbitrarily defined by the tool. It MAY not be returned.

detect_orientation() MAY raise an exception if there is no text detected in the image.

Dependencies

• PyOCR requires python 2.7 or later. Python 3 is supported.
• You will need Pillow or Python Imaging Library (PIL). Under Debian/Ubuntu, PIL is in the package "python-imaging".
• Install an OCR:
  • libtesseract ('libtesseract3' + 'tesseract-ocr-<lang>' in Debian).
  • or tesseract-ocr ('tesseract-ocr' + 'tesseract-ocr-<lang>' in Debian). You must be able to invoke the tesseract command as "tesseract". PyOCR is tested with Tesseract >= 3.01 only.
  • or cuneiform

Installation

$ sudo python ./setup.py install

Tests

$ python ./run_tests.py

Tests are made to be run with the latest versions of Tesseract and Cuneiform. the first tests verify that you're using the expected version.

To run the tesseract tests, you will need the following lang data files:

• English (tesseract-ocr-eng)
• French (tesseract-ocr-fra)
• Japanese (tesseract-ocr-jpn)

OCR on natural scenes

If you want to run OCR on natural scenes (photos, etc), you will have to filter the image first. There are many algorithms possible to do that. One of those who gives the best results is Stroke Width Transform.

Copyright

PyOCR is released under the GPL v3+.

tesseract.py:

• Copyright (c) Samuel Hoffstaetter, 2009
• Copyright (c) Jerome Flesch, 2011-2016

other files:

• Copyright (c) Jerome Flesch, 2011-2016

https://github.com/jflesch/pyocr