Open Source JavaScript OCR Software for Mac

javafx-desktop-apps pdf image ocr icc barcode color-palette text bytes markdown html archive compress digest video audio editor converter media https://github.com/Mararsh/MyBox Self-contain packages need not java env nor installation. Jar packages need Java 16 or higher.

Optical Character Recognition in JS for Browser is based on ocrad.js. OCR for Browser is a free extension and You can use this application to extract text from any image you supply. Just upload your image files. OCR for Browser takes either a JPG, GIF, TIFF, BMP, PNG. ========= Get OCR for Android (Beta release) - https://play.google.com/store/apps/details?id=com.ulm.ocr ========= Add-on for Opera: http://bit.ly/1F0E0wP ========= Release 1.0.1 For safety reasons, I disabled the possibility to import an image from url. Finally, I wish to inform you that you can write or draw directly on the canvas to get the subsequent character recognition and text extraction

Socr3 is a plugin-oriented, open source platform upon which I'm building an OCR suite. The name Socr3 stands for "Open Source Optical Character Recognition, Reading, Rendering, and Exporting", and is subject to change in the future.

WebDjVuTextEd allows to edit the text layer of OCR'ed DjVu documents in a web browser. You can modify the structure (paragraphs, lines, words...) create, delete, edit text nodes, modify their container box by mouse, and run a spellchecker. The program does not directly read the DjVu files, it requires exported XML text data and images. When using without a webserver, you can open and save local files, but cannot take advantages of auto-save and spell checking. Note that current SVN version has much more features than V1.0!

Captcha Intruder is an automatic pentesting tool to bypass captchas. -> CIntruder-v0.4 (.zip) -> md5 = 6326ab514e329e4ccd5e1533d5d53967 -> CIntruder-v0.4 (.tar.gz) ->md5 = 2256fccac505064f3b84ee2c43921a68 --------------------------------------------