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The main features of casia-iva-lab/fastsam are: Image segmentation.
Projects with overlapping indexed features include: chongzhou96/edgesam — Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM". davidtvs/pytorch-enet. facebookresearch/segment-anything — This project provides a deep learning architecture designed to identify and isolate distinct objects within images by… facebookresearch/segment-anything-2. hrnet/hrnet-semantic-segmentation — This is the implementation for PyTroch 0.4.1. - The HRNet + OCR version ia available here. - The PyTroch 1.1 version… chaoningzhang/mobilesam — MobileSAM is a lightweight image segmenter and promptable vision model designed for fast object isolation on…
Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"
This project provides a deep learning architecture designed to identify and isolate distinct objects within images by generating precise pixel-level masks. It functions as a browser-based inference engine, enabling the execution of complex machine learning models directly within web environments without requiring server-side processing. The system distinguishes itself by utilizing hardware-accelerated execution and parallel processing to achieve real-time segmentation speeds. It supports prompt-based mask decoding, allowing users to generate spatial masks by providing specific points or boxes
MobileSAM is a lightweight image segmenter and promptable vision model designed for fast object isolation on resource-constrained hardware. It functions as an automatic image masking tool capable of detecting and isolating distinct objects across an entire image without manual input. The system enables prompt-based object masking using coordinate points or bounding boxes to generate precise masks. It also supports all-object image segmentation through object-aware prompt sampling to identify every distinct object in a scene. To facilitate mobile and edge deployment, the model is compatible w