Open Source Mac QR Code Scanners

Open QR Code is an open-source cross-platform application developed using Flutter as main framework used to build the application, in common C, C++, Dart, Skia (a 2D rendering engine), and Impeller (the default rendering engine on iOS), Java, Kotlin. Open QR Code allows users to generate and scan QR codes effortlessly. The app is available on Android, Windows, and the Web. Users can generate QR codes from any text input, save them to their gallery, share them directly from the app, and scan QR codes to retrieve encoded information. Whether you're on Android, Windows, or the Web, you can create and share QR codes or scan them with a single click.

This is a plugin to KeePass <http://www.KeePass.info> to easily create the two-factor authentication parameters used by the KeePass placeholders {HMACOTP} and {TIMEOTP} from QR codes shown on screen.

= INTRO = I Was Here is an open-source PHP Student Attendance Management System. Featuring NFC and passwordless login, also allows students to take attendance by scanning a QR code. = DOCUMENTATION = https://code-boxx.com/i-was-here-php-attendance-system/ = SYSTEM REQUIREMENTS = * LAMP/WAMP/MAMP/XAMPP * Apache Mod Rewrite * PHP MySQL PDO Extension * At least PHP 8.0 = INSTALL = Just access http://YOUR-SITE.com in your browser to launch the installer. = LICENSE = I Was Here is released under the MIT License.

SlowQR allows to scan QR codes from images. Some manual interaction for distorted codes is possible. Due to missing hardware-accelerated drawing support, automatic recognition may be slow, hence the name. New features: - creation/editing of QR codes. - support of images with perspective - optional experimental offscreen hardware acceleration (via openGL 2-FBOs)

This is yet another QR code reader. It grabs code from a screen, decodes it and copies content into clipboard. Decoded text can be formated before being copied, so it can be easily pasted to i.e. spreadsheet application.

Applications of Quick Response (QR) codes enable rich context interaction through creation of links between physical objects and internet resources. In spite of the widespread use of this kind of barcode, applications for visually impaired people and robots are not common because existing decoders assume that the symbol is properly framed during image acquisition. This project implements a two-stage component-based approach to perform accurate detection of QR code symbols in arbitrarily acquired images. In the first stage a cascade classifier to detect parts of the symbol is trained using the rapid object detection framework proposed by Viola-Jones. In the second stage, detected patterns are aggregated in order to evaluate if they are spatially arranged in a way that is geometrically consistent with the components of a QR code symbol. OpenCV 2.2+ is required.

An easy-to-use PHP QrCode generator with first-party support for Laravel.