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More incredible work from Qiusheng Wu. This is SamGeo which segments remote sensing imagery using the Segment Anything Model 2 (SAM2).

But what is SAM2?

Here is a simple explanation:

The Segment Anything Model (SAM) is an advanced tool created by Meta Research that can identify and outline different objects in images. Here’s a simple breakdown of what SAM does:
𝐖𝐡𝐚𝐭 𝐈𝐭 𝐃𝐨𝐞𝐬: SAM can quickly find and highlight any object in a picture based on different types of hints you give it, like points, boxes, or even text descriptions.
𝐇𝐨𝐰 𝐈𝐭 𝐖𝐨𝐫𝐤𝐬: SAM has three main parts:
An image encoder that processes the picture to understand its content.
A prompt encoder that takes your hints and turns them into a format the model can use.
A mask decoder that combines the information from the picture and your hints to create outlines around the objects.
𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: SAM learned from a huge collection of 11 million images and over a billion outlines, which helps it recognize and segment objects effectively.
𝐙𝐞𝐫𝐨-𝐬𝐡𝐨𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: This means SAM can work with new images without needing specific training for each type of object, making it very flexible.
𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧: You can use SAM to get instant results, allowing you to interact with it as you work.
𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐌𝐨𝐝𝐞𝐥: SAM is designed to be a basic model for image segmentation, similar to how large language models work for text, making it useful for many different tasks.

Overall, SAM is a powerful tool that can help in various fields like content creation, research, and augmented reality by accurately identifying and outlining objects in images.

Have you begun using GeoAI? If you have I'd love to know more. Ping me

GeoAI is one of the cornerstones of Geospatial 2.0.

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