segment-anything-model

Zero-shot image segmentation generates object masks from prompts without task-specific training. Segment Anything Model accepts interactive point, box, or mask prompts to isolate objects across diverse images instantly.

Automated dataset generation uses automatic mask generation to extract multiple object masks from a single image. This creates annotated datasets rapidly, supporting pipelines for annotation tools and research.

Yes, running Segment Anything Model requires dependencies including torch>=1.7.0 and transformers>=4.30.0. You also need to install the segment-anything package to execute the segmentation workflows.

Yes, Segment Anything Model supports export options for deployment including ONNX. It offers ViT-H, ViT-L, and ViT-B model variants to balance performance and resource constraints during inference.

Zero-shot image segmentation applies to medical imaging and satellite imagery. The model segments unfamiliar visual data without task-specific training, enabling rapid prototyping across computer vision tasks.