This project is a cross-platform mobile camera library used to embed live camera feeds and capture photos or videos within mobile applications. It provides a unified interface for integrating mobile image capture and camera functionality across different platforms. The library includes specialized tools for reading and decoding barcode data from a live camera stream and a system for locating and identifying human faces in real-time.
This repository is a comprehensive collection of reference implementations and sample libraries for the Universal Windows Platform. It provides practical examples of how to use Windows Runtime APIs to build cross-device applications, including detailed guidance on XAML-based declarative user interfaces and DirectX-integrated rendering. The project distinguishes itself by providing a wide array of hardware integration suites, covering low-level communication with USB, Serial, I2C, SPI, and GPIO peripherals. It includes specialized implementations for mixed reality holographic rendering, advanc
html5-qrcode is a client-side JavaScript library that enables QR code and barcode scanning directly in a web browser, processing live video from a device camera or decoding codes from uploaded image files without any server-side involvement. The library handles real-time scanning from continuous camera feeds with adjustable frame rates and scanning regions, while also supporting file-based decoding for static images. The scanner offers configurable behavior through runtime settings, allowing developers to adjust scanning speed, viewfinder region, aspect ratio, and restrict decoding to specifi
A collection of reference implementations and code samples for integrating Android camera hardware and software APIs. The project provides demonstrations for using both the Jetpack CameraX library and the low-level Camera2 API to implement photo and video capture features. The repository includes specialized implementations for high-performance recording, such as high-frame-rate slow motion and high-dynamic-range video. It also features examples of machine learning vision, demonstrating how to analyze live camera frames for object detection and QR code scanning. The project covers broad imag