segment-anything-model

Zero-shot image segmentation generates accurate object masks from new domains without fine-tuning. You can produce masks by providing prompt inputs like points or bounding boxes to guide the segmentation of your target objects.

Zero-shot image segmentation extracts accurate object masks from images without requiring task-specific training data. You need it to quickly segment any object for annotation assistance, training data generation, or extracting regions of interest.

Yes, prompt flexibility allows you to use point prompts, bounding boxes, or even previous masks for interactive image segmentation. This enables prompt refinement loops to accurately extract and adjust object boundaries.

You can achieve deployment-ready faster inference by exporting image segmentation models via ONNX. This allows broader integration into image segmentation pipelines and accelerates mask generation across different platforms.

Automatic mask generation produces candidate masks for all objects in an image simultaneously. You can then filter these generated masks by their usable scoring and quality outputs to retain the most accurate segmentations.