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README.md

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+** 💛💛💛 南無阿彌陀佛 💛 ** <br/>
+** 💛💛💛 NamoAhmituofo 💛 **
+> 讓我們以慈心善待一切衆生，拒絕肉食、喫素放生，阿彌陀佛 💛 <br/>
+> Let's be kind to all sentinent beings, being vegetarians and stop eatting meats, away from all sufferrings, Ahmituofo 💛. <br/>
+> 如此，我們將獲得無量無邊利益，因爲衆生一體，因果相續。
+> By doing so, we shall gain immeasurable benefits and peace for ourselves and all beings. For we are ONE, you get what you pay.
+
 SAM 3 is a unified foundation model for promptable segmentation in images and videos. It can detect, segment, and track objects using text or visual prompts such as points, boxes, and masks. Compared to its predecessor [SAM 2](https://github.com/facebookresearch/sam2), SAM 3 introduces the ability to exhaustively segment all instances of an open-vocabulary concept specified by a short text phrase or exemplars. Unlike prior work, SAM 3 can handle a vastly larger set of open-vocabulary prompts. It achieves 75-80% of human performance on our new [SA-CO benchmark](https://github.com/facebookresearch/sam3/edit/main_readme/README.md#sa-co-dataset) which contains 270K unique concepts, over 50 times more than existing benchmarks.
 
 [Hugging Face 🤗  app](https://huggingface.co/spaces/akhaliq/sam3)