Facebook parent Meta on April 5 released a paper detailing its latest A.I. model that can segment different items within photographs. The company’s research division said it released the Segment Anything Model (SAM), and the corresponding dataset to foster research into foundation models for computer vision.
Meta said SAM is capable of identifying objects within images and videos – even in cases where it had not encountered those items in its training. Users can select objects by clicking on them or by using text prompts, such as the word 'cat' or 'chair' and so on. In a demonstration, SAM was able to draw boxes around multiple cats in a photo accurately in response to the written prompt.
SAM is trained on a massive dataset of 11 million images and 1.1 billion masks, which is the largest segmentation dataset to date. This dataset covers a wide range of objects and categories, such as animals, plants, vehicles, furniture, food, and more.
SAM is developed by Meta AI Research (formerly Facebook AI Research), and it is publicly available on GitHub. You can also try SAM online with a demo or download the dataset (SA-1B) of 1 billion masks and 11 million images.
Steps to use SAM:
Download the demo or go to the Segment Anything Model demo.
Upload an image or choose one in the gallery.
Add and subject areas
Mask areas by adding points. Select Add Area, then select the object. Refine the mask by selecting
Remove Area, then select the area.
Meta has been experimenting with generative AI, which creates new content rather than simply identifying or categorising data. CEO Mark Zuckerberg has said that incorporating such technology into Meta’s apps is a priority this year. Examples of generative AI tools that the company is developing include one that creates surreal videos from text prompts and another that generates children’s book illustrations from prose.
