🎬 ScreenToGif allows you to record a selected area of your screen, edit and save it as a gif or video.

Capture Screen, Audio, Cursor, Mouse Clicks and Keystrokes

📷 git-based selfies for software developers

A PyTorch Implementation of Single Shot MultiBox Detector

Run GUI applications and desktops in docker. Focus on security.

HTML5 QR code scanner using your webcam

The goal of this project is to allow integrated or USB-connected webcams to be accessed directly from Java. Using provided libraries users are able to read camera images and detect motion. Main project consist of several sub projects - the root one, which contains required classes, build-in webcam driver compatible with Windows, Linux and Mac OS, which can stream images as fast as your camera can serve them (up to 50 FPS). Main project can be used standalone, but user is able to replace build-in driver with different one - such as OpenIMAJ, GStreamer, V4L4j, JMF, LTI-CIVIL, FMJ, etc.

Webcamoid is a full featured and multiplatform webcam suite.

video.js plugin for recording audio/video/image files

Webcam component

JavaScript/WebGL real-time face tracking and expression detection library. Build your own emoticons animated in real time in the browser! SVG and THREE.js integration demos are provided.

Winner of Mozilla's $50,000 prize for art and advocacy exploring AI

React component for reading QR codes from webcam.

Automation to configure a Raspberry Pi as a USB OTG webcam

Turn any webcam into an IP camera

A C daemon that turns your webcam into a light sensor. It will adjust screen backlight based on ambient brightness.

Golang webcam library for Linux

Raspberry Pi 0 + High Quality Camera = High-quality USB Webcam!

Angularjs directive to access the webcam

Webcam component for VueJs.

Simple Unity Barcode Scanner

An OpenCV/Qt based realtime application for Eulerian Video Magnification / Motion Magnification. Works with multiple videos and cameras at the same time and let's you export the magnified videos.

Windows Remote Administration Tool via Telegram. Written in Python

WebRTC for Jupyter notebook/lab

We present MocapNET2, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance (70 fps in CPU-only execution).

Access and stream web camera in nodejs using opencv and websockets.

Virtual walks in Google Street View using PoseNet and applying Deep Learning models to recognize actions.

A simple Angular webcam component / pure & minimal, no flash-fallback

scan for webcams on the internet