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This project is a plugin for OBS Studio that uses neural networks to isolate subjects from backgrounds in real-time video streams. It functions as an AI video segmentation tool that predicts portrait masks to create virtual green-screen effects without the need for physical hardware. The software includes a real-time depth estimation filter that identifies scene depth to produce a blurred background while keeping the foreground subject in focus. It also provides low-light video enhancement to improve visibility and visual quality for portrait video captured in poorly lit environments. The pl
Backgroundremover is an AI-powered tool that removes backgrounds from both images and videos, accessible through a command-line interface and a Python API. At its core, it uses a pre-trained deep learning model to classify each pixel as foreground or background, producing a binary mask for removal. The tool distinguishes itself through multiple integration methods and output capabilities. It can process images and videos via Unix pipeline data streams, operate as an HTTP API server, or be called programmatically within Python scripts. Users can choose among different AI models to balance proc
This software is a computer vision utility designed for automated subject isolation and background removal. It provides a graphical desktop interface that allows users to extract foreground subjects from static images, video files, and live webcam streams without requiring command-line interaction. The application leverages deep learning models to generate high-fidelity alpha masks, enabling the creation of transparent backgrounds or the application of custom replacements. By utilizing hardware-accelerated tensor processing, the system performs real-time segmentation on live camera feeds and
This project is a deep learning image matting framework and computer vision tool designed to separate people from their backgrounds. It functions as a real-time video matting engine and a trainable foreground isolation model that generates per-pixel alpha mattes to isolate subjects from photos and videos. The system utilizes reference-based alpha matting, incorporating a specific background image to simulate green screen effects without a physical screen. This approach allows for the removal and replacement of backgrounds in high-resolution footage, including live video streams. The framewor
Perfect Green Screen Keys
The main features of nikopueringer/corridorkey are: AI Background Removal Tools, Video Frame Decoders, Background Removal Tools, Batch Video Processing, Background Removal Pipelines, Video Keying Interfaces, AI Frame Keying, Virtual Green Screens.
Open-source alternatives to nikopueringer/corridorkey include: nadermx/backgroundremover — Backgroundremover is an AI-powered tool that removes backgrounds from both images and videos, accessible through a… royshil/obs-backgroundremoval — This project is a plugin for OBS Studio that uses neural networks to isolate subjects from backgrounds in real-time… plemeri/transparent-background — This software is a computer vision utility designed for automated subject isolation and background removal. It… senguptaumd/background-matting — This project is a deep learning image matting framework and computer vision tool designed to separate people from… steveseguin/vdo.ninja — VDO.Ninja is a low-latency peer-to-peer media routing service and video streaming platform designed to integrate… danielgatis/rembg — Rembg is a machine learning-based toolkit designed for automated image background removal and subject segmentation. It…