robotframework-ocrlibrary 1.2.0

A robot framework library that utilizes OpenCV image processing and pytesseract OCR.

Robot Framework OCR Library

A robot framework library that is capable of processing images, validating text, and locating specified text by coordinates within images.

Keyword Documentation

You can find the keyword documentation here.

Installation and Usage

• OCRLibrary can be run on Python 3.6, 3.7, 3.8, and 3.9.
• To install, run pip install robotframework-OCRLibrary

Dependencies

OCRLibrary uses two dependencies, opencv-python and pytesseract. Pytesseract has more dependencies. Depending on your OS and current packages, this may not work after a pip install.

OpenCV Python

To install opencv-python, run pip install opencv-python. Please see opencv-python's installation and usage section if this does not work.

Pytesseract

To install pytesseract, run pip install pytesseract. Please see pytesseracts installation section if this does not work.

Pytesseract requires Google's Tesseract OCR software. For installation of tesseract for Linux, MacOS or Windows please see the following installation guide.

Usage

Once OCRLibrary is installed, along with its dependencies, add Library OCRLibrary to your robot file to use.

Custom configurations for reading images.

You can add any combination of the following to the pyt_conf string argument.

Page segmentation modes

Page segmentation modes provide different ways a poage of text can be analyzed. Here is a list of supported page segmentation modes:

• 0 Origentation and script detection only.
• 1 Automatic page segmentation with OSD.
• 2 Automatic page segmentation, but no OSD, or OCR.
• 3 Fully automatic page segmentation, but no OSD. (Default)
• 4 Assume a single column o ftext of variable sizes.
• 5 Assume a single uniform block of vertically aligned text.
• 6 Assume a single uniform block of text.
• 7 Treat the image as a single text line.
• 8 Treat the image as a single word.
• 9 Treat the image as a single word in a circle.
• 10 Treat the image as a single character.
• 11 Sparse text. Find as muuch text as possible in no particular order.
• 12 Sparse text with OSD.
• 13 Raw line. Treat the image as a single text line, by passing hacks that are Tesseract-specific.

To change your page segmentation mode, add --psm <mode> to your custom configuration string.

OCR Engine Modes

Select the OCR engine modes to be used by pytesseract:

• 0 Legacy engine only.
• 1 Neural nets LSTM engine only.
• 2 Legacy + LSTM engines.
• 3 Default, based on what is available.

To change your ocr engine mode, add --oem <mode> to your custom configuration string.

Whitelisting Characters

This configuration specifies which characters to detect. Add the characters you want to detect to the string: c- tessedit_char_whitelist=. An example to only detect lowercase letters: c- tessedit_char_whitelist=abcdefghijklmnopqrstuvwxyz

Blacklisting Characters

Opposite to whitelisting characters, this configurations lets you specify which characters to not detect. Add the characters you want to not detect to the string: c- tessedit_char_blacklist= An example to not detect special characters: c- tessedit_char_whitelist=!@#$%^&*()

Image Processing in OpenCV

Please see any of the following links for more information on image processing using OpenCV:

• Changing Colour Spaces
• Thresholding
• Smoothing Images
• Morphological Transformations

Contributing

When contributing please adhere to the following.

To start off, if you find a bug, please submit an issue. If you want to fix something or improve upon something, fork the repo, and create a new branch. Once you have made the changes and have written unit tests or updated the regression tests (please use pythons Unittest when testing), make a pull request.