segment anything

What is the structure of the model?

• A ViT-H image encoder that runs once per image and outputs an image embedding
• A prompt encoder that embeds input prompts such as clicks or boxes
• A lightweight transformer based mask decoder that predicts object masks from the image embedding and prompt embeddings

　　

How big is the model?

• The image encoder has 632M parameters.
• The prompt encoder and mask decoder have 4M parameters.

How long does inference take?

• The image encoder takes ~0.15 seconds on an NVIDIA A100 GPU.
• The prompt encoder and mask decoder take ~50ms on CPU in the browser using multithreaded SIMD execution.

How long does it take to train the model?

• The model was trained for 3-5 days on 256 A100 GPUs.