Annotation tool for Semantic Segmentation using Segment Anything Model(SAM)

<p>Exploring the functionalities, capabilities, and potential applications of two cutting-edge tools in the field of computer vision and geospatial analysis: the Segment Anything Model and the Segment Geospatial Library. The Segment Anything Model, developed by Meta AI, offers state-of-the-art capabilities for semantic segmentation of various types of images, including satellite imagery. Trained on an extensive dataset, it automates object identification and generates precise segmentation masks, reducing manual effort and ensuring consistency. The Segment Geospatial Library, developed by Aliaksandr Hancharenka, complements the Segment Anything Model by enabling advanced geospatial analysis on annotated satellite images. The objectives were to gain an in-depth understanding of these tools and their potential use in semantic segmentation and geospatial analysis tasks. The methodology involved thorough research, analysis of research papers and Python code, and hands-on experimentation to gain practical knowledge and insights into the tools&rsquo; functionalities.</p> <h1>1. Introduction</h1> <h2>1.1 Background</h2> <p>The field of computer vision and geospatial analysis has seen remarkable advancements due to the increasing availability of satellite imagery and the need for accurate analysis. Tools like Segment Anything Model (Developed by Meta AI) and the Segment Geospatial Library (Developed by Aliaksandr Hancharenka) have emerged as valuable resources for semantic segmentation and geospatial analysis.</p> <p>Semantic segmentation is crucial for identifying objects and regions within satellite images, and the Segment Anything tool offers state-of-the-art capabilities for this task. Sam was trained on the largest segmentation dataset to date, with over 1 billion masks on 11M licensed and privacy respecting images. It automates object identification and generates precise segmentation masks, reducing manual effort and ensuring consistency.</p> <p><a href="https://medium.com/@yashrathee3333/annotation-tool-for-semantic-segmentation-using-segment-anything-model-sam-22c24b3b280">Website</a></p>