Meta Segment Anything Model 2 Howto
WebsiteAI Image Segmentation
Meta Segment Anything Model 2 (SAM 2) is a powerful AI model that enables real-time, promptable object segmentation across both images and videos with zero-shot generalization capabilities.
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Install dependencies: Install PyTorch and other required libraries.
Download the model checkpoint: Download the SAM 2 model checkpoint from the provided GitHub repository.
Import necessary modules: Import torch and the required SAM 2 modules.
Load the SAM 2 model: Use the build_sam2() function to load the SAM 2 model with the downloaded checkpoint.
Prepare your input: Load your image or video that you want to segment.
Create a predictor: For images, create a SAM2ImagePredictor. For videos, use build_sam2_video_predictor().
Set the image/video: Use the predictor's set_image() method for images or init_state() for videos.
Provide prompts: Specify points, boxes, or masks as prompts to indicate the objects you want to segment.
Generate masks: Call the predictor's predict() method for images or add_new_points() and propagate_in_video() for videos to generate segmentation masks.
Process the results: The model will return segmentation masks which you can then use or visualize as needed.
Meta Segment Anything Model 2 FAQs
SAM 2 is an advanced AI model developed by Meta that can segment objects in both images and videos. It builds on the original SAM model, adding video segmentation capabilities and improved performance for real-time, interactive applications.
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Segment Anything
Segment Anything is a promptable AI model developed by Meta AI that can segment any object in any image with zero-shot generalization capabilities.
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