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Atoms of elements in Group 1 have electronic structures that end with 1. Li (2.1), Na (2.8.1), K (2.8.8.1) etc. The easiest way to achieve this is to lose an electron. Hence Group 1 elements only ever form 1+ cations. In the same way, all Group 2 elements will form 2+ ions. The OCR Level 2 Nationals in ICT have been developed to recognise learners' skills, knowledge and understanding of Information and Communication Technology functions, environments and operations. The learners carry out a range of tasks that have been designed to recognise their achievements in a modern, practical way that is relevant to the.

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Pdf squeezer 3 10 52. Python wrapper for Tesseract OCR and Google Vision OCR

Project description

Python wrapper for Tesseract OCR and Google Vision OCR to perform OCR on images and get a confidence value of the results.

Both OCR engines are Google’s products. Tesseract is an open source software that needs some tweaks to get good results, especially if performed on images with poorly defined text. Google Vision OCR engine is a commercial product with much better performance, allowing you to skip the pre-processing jobs on the images.

Only Python >= 3.6 is supported.

Usage

The gpyocr module have two main functions:

• tesseract_ocr(image, lang=', psm=None, config='): it returns a tuple(text, confidence) obtained with Tesseract. The parameters are the same ofthe command-line Tesseract toolexcept for the output file.
• google_vision_ocr(image, langs=None): it returns a tuple(text, confidence) obtained with Google Vision API. The langs parameteris a list of languages to look for during the OCR process. More informationabout the supported languages are described onthis page

The parameter image could be:

• a string containing the path to the image file
• a numpy object (OpenCV)
• an Image object (Pillow/PIL)

It is possible to get some information about the Tesseract and Google Visionversions found in the system with get_tesseract_version() andget_google_vision_version() respectively.

The installation of the package also provides a command-line tool, please run

Ocr Butler 1 2 1/2

for more information.

Examples

Examples to read the text in the image tests/resources/european-test.pngon this repository.

Please see the unit tests for more examples.

Installation

gpyocr is a pip package available in the Python Package Index.To install it in your Python environment run:

If you want to run Tesseract with gpyocr you have to install it in yoursystem. In order to get the confidence value, gpyocr needs Tesseract >= 3.05.You could install Tesseract with the bash script tesseract_installer.sh thatyou find in the repository. If you want Tesseract 3.05 (the suggested version)then run:

If you want to try Tesseract 4.1.0 then run:

Note: this bash script is tested in Ubuntu 18.04 and CentOS 7; if youdon’t have these systems, there may be problems installing some dependencies.You could install all the dependencies by your self and then run:

To use Google Cloud Vision API, you have to authenticate with

Please refer totheir documentation formore information about installing and using Google Cloud Vision services.

Testing

First, install pytest, pytest-cov and pytest-mock. You couldinstall them with pip install -r requirements.txt.

Go to the root directory of this repository.

To run unit tests without using the OCR libraries run:

Debookee 7 4 1000. To run unit tests using the OCR libraries run:

To get a coverage report, run Bartender 3 0 64 iso.

To test only the Tesseract functions run:

To test only the Google Cloud Vision functions run:

How to contribute

This project is developed to be used by a specific application, so it is notvery versatile. If you wish to have new features or if you have any kind ofproblems, please feel free to contact me via e-mail or open an issue here onGitHub.

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