pytesseract 0.3.0

Python-tesseract is a python wrapper for Google's Tesseract-OCR

Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images.

Python-tesseract is a wrapper for Google’s Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Pillow and Leptonica imaging libraries, including jpeg, png, gif, bmp, tiff, and others. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.

USAGE

Quickstart

Note: Test images are located in the tests/data folder of the Git repo.

try:
    from PIL import Image
except ImportError:
    import Image
import pytesseract

# If you don't have tesseract executable in your PATH, include the following:
pytesseract.pytesseract.tesseract_cmd = r'<full_path_to_your_tesseract_executable>'
# Example tesseract_cmd = r'C:\Program Files (x86)\Tesseract-OCR\tesseract'

# Simple image to string
print(pytesseract.image_to_string(Image.open('test.png')))

# French text image to string
print(pytesseract.image_to_string(Image.open('test-european.jpg'), lang='fra'))

# In order to bypass the image conversions of pytesseract, just use relative or absolute image path
# NOTE: In this case you should provide tesseract supported images or tesseract will return error
print(pytesseract.image_to_string('test.png'))

# Batch processing with a single file containing the list of multiple image file paths
print(pytesseract.image_to_string('images.txt'))

# Get bounding box estimates
print(pytesseract.image_to_boxes(Image.open('test.png')))

# Get verbose data including boxes, confidences, line and page numbers
print(pytesseract.image_to_data(Image.open('test.png')))

# Get information about orientation and script detection
print(pytesseract.image_to_osd(Image.open('test.png')))

# Get a searchable PDF
pdf = pytesseract.image_to_pdf_or_hocr('test.png', extension='pdf')

# Get HOCR output
hocr = pytesseract.image_to_pdf_or_hocr('test.png', extension='hocr')

Support for OpenCV image/NumPy array objects

import cv2

img = cv2.imread(r'/<path_to_image>/digits.png')
print(pytesseract.image_to_string(img))
# OR explicit beforehand converting
print(pytesseract.image_to_string(Image.fromarray(img))

If you need custom configuration like oem/psm, use the config keyword.

# Example of adding any additional options.
custom_oem_psm_config = r'--oem 3 --psm 6'
pytesseract.image_to_string(image, config=custom_oem_psm_config)

Add the following config, if you have tessdata error like: “Error opening data file…”

# Example config: r'--tessdata-dir "C:\Program Files (x86)\Tesseract-OCR\tessdata"'
# It's important to add double quotes around the dir path.
tessdata_dir_config = r'--tessdata-dir "<replace_with_your_tessdata_dir_path>"'
pytesseract.image_to_string(image, lang='chi_sim', config=tessdata_dir_config)

Functions

• get_tesseract_version Returns the Tesseract version installed in the system.

• image_to_string Returns the result of a Tesseract OCR run on the image to string

• image_to_boxes Returns result containing recognized characters and their box boundaries

• image_to_data Returns result containing box boundaries, confidences, and other information. Requires Tesseract 3.05+. For more information, please check the Tesseract TSV documentation

• image_to_osd Returns result containing information about orientation and script detection.

• run_and_get_output Returns the raw output from Tesseract OCR. Gives a bit more control over the parameters that are sent to tesseract.

Parameters

image_to_data(image, lang=None, config='', nice=0, output_type=Output.STRING, timeout=0)

• image Object, PIL Image/NumPy array of the image to be processed by Tesseract

• lang String, Tesseract language code string

• config String, Any additional configurations as a string, ex: config='--psm 6'

• nice Integer, modifies the processor priority for the Tesseract run. Not supported on Windows. Nice adjusts the niceness of unix-like processes.

• output_type Class attribute, specifies the type of the output, defaults to string. For the full list of all supported types, please check the definition of pytesseract.Output class.

• timeout Integer or Float, duration in seconds for the OCR processing, after which, pytesseract will terminate and raise RuntimeError.

INSTALLATION

Prerequisites:

• Python-tesseract requires Python 2.7 or Python 3.5+

• You will need the Python Imaging Library (PIL) (or the Pillow fork). Under Debian/Ubuntu, this is the package python-imaging or python3-imaging.

• Install Google Tesseract OCR (additional info how to install the engine on Linux, Mac OSX and Windows). You must be able to invoke the tesseract command as tesseract. If this isn’t the case, for example because tesseract isn’t in your PATH, you will have to change the “tesseract_cmd” variable pytesseract.pytesseract.tesseract_cmd. Under Debian/Ubuntu you can use the package tesseract-ocr. For Mac OS users. please install homebrew package tesseract.

Installing via pip:

Check the pytesseract package page for more information.

$ (env)> pip install pytesseract

Or if you have git installed:

$ (env)> pip install -U git+https://github.com/madmaze/pytesseract.git

Installing from source:

$> git clone https://github.com/madmaze/pytesseract.git
$ (env)> cd pytesseract && pip install -U .

Install with conda (via conda-forge):

$> conda install -c conda-forge pytesseract

TESTING

To run this project’s test suite, install and run tox. Ensure that you have tesseract installed and in your PATH.

$ (env)> pip install tox
$ (env)> tox

LICENSE

Python-tesseract is released under the GPL v3.

CONTRIBUTORS

• Originally written by Samuel Hoffstaetter

• Juarez Bochi

• Matthias Lee

• Lars Kistner

• Ryan Mitchell

• Emilio Cecchini

• John Hagen

• Darius Morawiec

• Eddie Bedada