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.
Quickstart
Note: Test images are located in the tests/data folder of the Git repo.
Library usage:
from PIL 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')))
# 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'))
# List of available languages
print(pytesseract.get_languages(config=''))
# French text image to string
print(pytesseract.image_to_string(Image.open('test-european.jpg'), lang='fra'))
# Batch processing with a single file containing the list of multiple image file paths
print(pytesseract.image_to_string('images.txt'))
# Timeout/terminate the tesseract job after a period of time
try:
print(pytesseract.image_to_string('test.jpg', timeout=2)) # Timeout after 2 seconds
print(pytesseract.image_to_string('test.jpg', timeout=0.5)) # Timeout after half a second
except RuntimeError as timeout_error:
# Tesseract processing is terminated
pass
# 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')
with open('test.pdf', 'w+b') as f:
f.write(pdf) # pdf type is bytes by default
# Get HOCR output
hocr = pytesseract.image_to_pdf_or_hocr('test.png', extension='hocr')
# Get ALTO XML output
xml = pytesseract.image_to_alto_xml('test.png')
# getting multiple types of output with one call to save compute time
# currently supports mix and match of the following: txt, pdf, hocr, box, tsv
text, boxes = pytesseract.run_and_get_multiple_output('test.png', extensions=['txt', 'box'])
Support for OpenCV image/NumPy array objects
import cv2
img_cv = cv2.imread(r'/<path_to_image>/digits.png')
# By default OpenCV stores images in BGR format and since pytesseract assumes RGB format,
# we need to convert from BGR to RGB format/mode:
img_rgb = cv2.cvtColor(img_cv, cv2.COLOR_BGR2RGB)
print(pytesseract.image_to_string(img_rgb))
# OR
img_rgb = Image.frombytes('RGB', img_cv.shape[:2], img_cv, 'raw', 'BGR', 0, 0)
print(pytesseract.image_to_string(img_rgb))
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) # Example of using pre-defined tesseract config file with options cfg_filename = 'words' pytesseract.run_and_get_output(image, extension='txt', config=cfg_filename)
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
Parameters
image_to_data(image, lang=None, config='', nice=0, output_type=Output.STRING, timeout=0, pandas_config=None)
eng if not specified! Example for multiple languages: lang='eng+fra'config='--psm 6'string. For the full list of all supported types, please check the definition of pytesseract.Output class.CLI usage:
pytesseract [-l lang] image_file
Prerequisites:
Python-tesseract requires Python 3.6+
You will need the Python Imaging Library (PIL) (or the Pillow fork). Please check the Pillow documentation to know the basic Pillow installation.
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.
Note: In some rare cases, you might need to additionally install tessconfigs and configs from tesseract-ocr/tessconfigs if the OS specific package doesn't include them.
Check the pytesseract package page for more information.
Or if you have git installed:
pip install -U git+https://github.com/madmaze/pytesseract.git
git clone https://github.com/madmaze/pytesseract.git cd pytesseract && pip install -U .
conda install -c conda-forge pytesseract
To run this project's test suite, install and run tox. Ensure that you have tesseract installed and in your PATH.
Check the LICENSE file included in the Python-tesseract repository/distribution. As of Python-tesseract 0.3.1 the license is Apache License Version 2.0
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4