Meta Segment Anything Model 2

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Introduction:
Object segmentation in videos and images
Added on:
Jul 31 2024
Monthly Visitors:
1.5M
Social & Email:
Meta Segment Anything Model 2 Product Information

What is Meta Segment Anything Model 2?

Meta Segment Anything Model 2, also known as SAM 2, is an advanced segmentation model that allows for fast and precise selection of objects in videos and images. It enables users to segment any object using clicks, boxes, or masks as inputs.

How to use Meta Segment Anything Model 2?

To use Meta Segment Anything Model 2, simply access the provided demo or download the model. Select an object on an image or video frame using clicks, boxes, or masks. Refine the model predictions and enjoy real-time interactive results.

Meta Segment Anything Model 2's Core Features

Fast and precise object segmentation

Supports segmentation in videos and images

Real-time interactive applications

Meta Segment Anything Model 2's Use Cases

#1

Quickly select and segment objects in videos or images

#2

Track objects across video frames interactively with minimal user input

FAQ from Meta Segment Anything Model 2

What input methods are supported for object selection in Meta Segment Anything Model 2?

Does Meta Segment Anything Model 2 support real-time video processing?

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Analytic of Meta Segment Anything Model 2

Meta Segment Anything Model 2 Website Traffic Analysis

Visit Over Time

Monthly Visits
1.5M
Avg.Visit Duration
00:01:31
Page per Visit
1.68
Bounce Rate
63.20%
May 2024 - Dec 2024 All Traffic

Geography

Top 5 Regions

United States
38.47%
India
8.57%
Canada
3.87%
China
2.70%
United Kingdom
2.66%
May 2024 - Dec 2024 Desktop Only

Traffic Sources

Search
52.73%
Direct
32.37%
Referrals
10.19%
Social
4.50%
Display Ads
0.17%
Mail
0.05%
May 2024 - Dec 2024 Worldwide Desktop Only

Top Keywords

Keyword
Traffic
Cost Per Click
meta ai
869.5K
$ 0.47
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3.3M
$ 0.90
llama 3.2
38.7K
$ 1.32
llama 3.1
99.4K
$ 1.44
meta movie gen
12.3K
$ 1.04

Social Listening

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Meta Segment Anything Model 2: Object segmentation in videos and images
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