Segment Anything by Meta AI is an AI model designed for computer vision research that enables users to segment objects in any image with a single click. The model uses a promptable segmentation system with zero-shot generalization to unfamiliar objects and images without requiring additional training.
The model is designed to be efficient enough to power the data engine, with 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 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.
More details about Segment Anything by Meta
What are the system requirements for deploying Segment Anything?
For deploying Segment Anything, a platform that supports PyTorch or ONNX runtime is needed. Additionally, the image encoder requires a GPU for efficient inference, whereas the prompt encoder and mask decoder can run efficiently on CPU or GPU.
Is Segment Anything used for 3D modeling?
Segment Anything can be used to ‘lift’ the output masks to 3D. The segmented objects can be transformed or projected into 3D space, enabling uses for 3D modeling, although detailed specifics of this functionality aren’t provided.
How is PyTorch used in applying Segment Anything?
PyTorch is used in Segment Anything for running the image encoder, prompt encoder, and mask decoder. These elements can run directly with PyTorch, or be converted to ONNX for efficient running on the CPU or GPU.
How does the mask decoder in Segment Anything contribute to its efficiency?
The mask decoder in Segment Anything contributes to its efficiency by being a lightweight transformer that predicts object masks from the image embedding and prompt embeddings.
