Segment Anything by Meta
Segment Anything by Meta AI is an AI model designed for computer vision research that allows users to segment objects in any image with a single click. The model utilizes a promptable segmentation system with zero-shot generalization, enabling it to handle unfamiliar objects and images without the need for additional training. Users can provide a variety of input prompts, such as interactive points and boxes, to specify what should be segmented in an image. The model can even generate multiple valid masks for ambiguous prompts.
The output masks generated by Segment Anything can be used as inputs for other AI systems, tracked in videos, utilized in image editing applications, or lifted to 3D for creative tasks. The model is designed to be efficient, featuring 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 requires a GPU for efficient inference, while the prompt encoder and mask decoder can be directly run with PyTorch or converted to ONNX for efficient execution on CPU or GPU across various platforms supporting ONNX runtime.
To train the model, the SA-1B dataset was used, which consists of over 11 million licensed and privacy-preserving images. This extensive dataset resulted in the collection of over 1.1 billion segmentation masks. With its user-friendly interface and powerful capabilities, Segment Anything by Meta AI offers a versatile solution for efficient and accurate object segmentation in computer vision tasks.
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