Advanced image segmentation for research & editing.
Meta AI's "Segment Anything" is a remarkable AI model that offers users the ability to effortlessly segment objects within any image. With its promptable segmentation system, zero-shot generalization to unfamiliar objects, and images without requiring additional training, it's the perfect tool for computer vision research. This versatile system can accept a wide range of input prompts, such as interactive points and boxes, and can generate multiple valid masks for ambiguous prompts.
Furthermore, the output masks produced by this system can be used as inputs to other AI systems, including those used for image editing applications or lifted to 3D for creative tasks. This model is designed to be incredibly efficient, requiring only a one-time image encoder and a lightweight mask decoder that can run in a web browser in just a few milliseconds per prompt.
The image encoder necessitates a GPU for efficient inference, but the prompt encoder and mask decoder can run directly with PyTorch or be converted to ONNX and run efficiently on CPU or GPU across a variety of platforms that support ONNX runtime. The model was trained on the SA-1B dataset, which consists of over 11 million licensed and privacy-preserving images resulting in over 1.1 billion segmentation masks collected. Overall, Meta AI's "Segment Anything" is an indispensable tool for anyone in the field of computer vision research.
