Zarxrax/Sammie-Roto-2

A GUI for masking/rotoscoping video using AI models

What it solves

Sammie-Roto 2 is a desktop application designed to simplify the tedious process of masking video clips. It provides an AI-assisted workflow for segmenting objects, creating high-quality mattes, and removing objects from video footage.

Related

  • Project
    pq-yang/MatAnyone2

    A human video matting framework that preserves fine details and avoids coarse boundaries to extract people from videos with high robustness in real-world conditions.

  • Project
    1038lab/ComfyUI-RMBG

    A comprehensive ComfyUI custom node suite for advanced image background removal and object segmentation using a wide variety of state-of-the-art AI models.

  • Project
    D-Ogi/WatermarkRemover-AI

    An AI-powered tool that uses Florence-2 and LaMA models to detect and seamlessly remove watermarks from images and AI-generated videos.

  • Project
    opengeos/segment-geospatial

    A Python package that adapts the Segment Anything Model (SAM) for geospatial data, enabling easy segmentation of satellite imagery using text, points, or boxes.

  • Project
    pangxiaobin/image-matting

    A desktop application that uses the RMBG-1.4 model to provide local AI-powered background removal, batch processing, and image editing tools.