The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
The Segment Anything project provides a state-of-the-art image segmentation model (SAM) that can generate high-quality object masks from input prompts like points or boxes, or automatically detect all objects in an image. It's designed for developers and researchers working on computer vision tasks who need a powerful, zero-shot segmentation tool. The project includes pre-trained model checkpoints, example notebooks, and code for running inference with SAM.
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