Casia-iva-lab

fastsam

FastSAM is a fast and efficient model for segmenting objects in images. It is designed to segment any type of object quickly and accurately, making it suitable for a variety of applications such as autonomous driving, object recognition, and image editing. The model achieves its speed by using a lightweight architecture and parallel processing techniques. It is trained on a large dataset of annotated images to learn the features that distinguish different objects. FastSAM can efficiently process high-resolution images and can generate segmentations in real-time. It has been shown to achieve state-of-the-art performance on several benchmark datasets.

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