Search Results for "open source kms"

Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision.

Show Facebook Computer Vision Tags is a Chrome (and Firefox) browser extension created to expose and overlay the automatically generated image tags that Facebook applies to photos in users’ feeds. Since Facebook uses a computer-vision model to analyse user-uploaded images and generate alt-text tags for accessibility (e.g., “Image may contain: golf, grass, outdoor and nature”), this extension surfaces those hidden tags directly in the UI—revealing what kind of information Facebook infers...

The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The...

Proposed is an algorithm that uses computer vision, combined with a modified Rubine classifier, to allow arbitrary N-sided polygons as accepted sketches in real-time.

Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms