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     <img src="Resources/Banner.png" width="890" alt="Logo"/>
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-[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0) [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-v1.4%20adopted-ff69b4.svg)](CODE_OF_CONDUCT.md) ![semver](https://img.shields.io/badge/semver-2.0.0-blue)
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+[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0) [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-v1.4%20adopted-ff69b4.svg)](CODE_OF_CONDUCT.md) ![semver](https://img.shields.io/badge/semver-2.0.0-blue) [![codebeat badge](https://codebeat.co/badges/b2812d59-2a46-4ccd-b6c8-d3e909742c08)](https://codebeat.co/projects/github-com-marcoistasy-imagineocr-master)
 
 ImagineOCR represents a fundamental restructuring of image-to-text software. Abandoning previous principles emphasising static models of orthography, imagine OCR approaches OCR as the province of object detection. Accordingly, it views each character on a page as a discrete object and allows training of a custom faster-rcnn implementation given as little as a single instance of the objects (read: characters) to be detected.