SAM 2 is the first unified model for segmenting objects across images and videos. You can use a click, box, or mask as the input to select an object on any image or frame of video. Using SAM 2, you can select one or multiple objects in a video frame. …

Segment Anything Model (SAM): a new AI model from Meta AI that can "cut out" any object, in any image, with a single click SAM is a promptable segmentation system with zero-shot generalization to unfamiliar objects and images, without the need for additional training.

Sam is a very small Text-To-Speech (TTS) program written in Javascript, that runs on most popular platforms. It is an adaption to Javascript of the speech software SAM (Software Automatic Mouth) for the Commodore C64 published in the year 1982 by …

Segment Anything Model 2 (SAM 2) is a foundation model towards solving promptable visual segmentation in images and videos. We extend SAM to video by considering images as a video with a single frame. The model design is a simple transformer architecture with streaming memory for real-time video processing.

The Segment Anything Model (SAM) produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image. It has been trained on a dataset of 11 million images and 1.1 billion masks, and has strong zero-shot performance on a variety of segmentation tasks.

2024年1月29日 · 本篇博客介绍了Segment Anything Model (SAM)，这 是Meta AI团队于2023年提出的通用图像分割基础模型，旨在通过用户提供的交互式提示（如点、框、文本等）实现任意目标的零样本分割。

This repository is the official implementation of SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory. All rights are reserved to the copyright owners (TM & © Universal (2019)). This clip is not intended for commercial use and is solely for academic demonstration in a research paper.

将基于提示的分割一切基础模型 (sam) 升级为标记一切基础模型 (tap)，高效地在单一视觉模型中实现对任意区域的空间理解和语义理解。 相关的模型、代码均已开源，并提供了 Demo 试用，更多技术细节请参考 TAP 论文。

2023年12月21日 · 本文介绍了Meta的SegmentAnythingModel(SAM)，一种先进的图像分割模型，基于NLP基础模型，能通过提示工程适应各种任务。文章详细阐述了SAM的优势、网络架构、与传统模型的对比，以及在AI辅助打标领域的潜力，特别是在大规模数据集SA-1B的支持下。

SAM 2.1（全称Segment Anything Model 2.1）是Meta（Facebook的母公司）推出的先进视觉分割模型，用于图像和视频。 基于简单的Transformer架构和流式记忆设计，实现实时视频处理。 SAM 2.1在前代基础上引入数据增强技术，改善对视觉相似物体和小物体的识别，提升遮挡处理能力。 此外Meta开源了SAM 2的开发者套件，包括训练代码和网络演示的前后端代码，方便用户使用和微调模型。 图像和视频分割：对图像和视频进行视觉分割，识别和分离出不同的对象和元素。 …