Duplicate from AllanVester/SAM3.1-CoreML

Co-authored-by: Allan Vester <AllanVester@users.noreply.huggingface.co>

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README.md

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+---
+license: other
+language:
+- en
+pipeline_tag: mask-generation
+base_model: facebook/sam3.1
+library_name: coreml
+tags:
+- coreml
+- sam3
+- sam3.1
+- segmentation
+- detection
+- tracking
+- object-multiplex
+- fp32
+- float32
+---
+
+# SAM 3.1 Core ML
+
+[SAM 3](https://github.com/facebookresearch/sam3) (Segment Anything with Concepts) is a unified foundation model from Meta for promptable segmentation in images and videos. It detects, segments, and tracks 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 which contains 270K unique concepts, over 50 times more than existing benchmarks. SAM 3.1 builds on this with Object Multiplex, a shared-memory approach for joint multi-object tracking that delivers ~7x faster inference at 128 objects on a single H100 GPU without sacrificing accuracy, along with improved VOS performance on 6 out of 7 benchmarks.
+
+This is the Core ML version of [SAM 3.1](https://huggingface.co/facebook/sam3.1) · [Code](https://github.com/facebookresearch/sam3).
+
+## Download
+
+Install `huggingface-cli`
+
+```bash
+brew install huggingface-cli
+```
+
+```bash
+huggingface-cli download --local-dir models AllanVester/SAM3.1-CoreML
+```
+
+## Citation
+
+If you use SAM 3 in your research, please use the following BibTeX entry:
+```
+@misc{carion2025sam3segmentconcepts,
+      title={SAM 3: Segment Anything with Concepts},
+      author={Nicolas Carion and Laura Gustafson and Yuan-Ting Hu and Shoubhik Debnath and Ronghang Hu and Didac Suris and Chaitanya Ryali and Kalyan Vasudev Alwala and Haitham Khedr and Andrew Huang and Jie Lei and Tengyu Ma and Baishan Guo and Arpit Kalla and Markus Marks and Joseph Greer and Meng Wang and Peize Sun and Roman Rädle and Triantafyllos Afouras and Effrosyni Mavroudi and Katherine Xu and Tsung-Han Wu and Yu Zhou and Liliane Momeni and Rishi Hazra and Shuangrui Ding and Sagar Vaze and Francois Porcher and Feng Li and Siyuan Li and Aishwarya Kamath and Ho Kei Cheng and Piotr Dollár and Nikhila Ravi and Kate Saenko and Pengchuan Zhang and Christoph Feichtenhofer},
+      year={2025},
+      eprint={2511.16719},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2511.16719},
+}
+```
+
+## License
+
+The original SAM 3.1 model weights are released by Meta under the [SAM License](https://huggingface.co/facebook/sam3.1/blob/main/LICENSE), a custom permissive license for commercial and research use.

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