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README.md

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-# YOLO-World + EfficientViT SAM
-
-🤗 [HuggingFace Space](https://huggingface.co/spaces/curt-park/yolo-world-with-efficientvit-sam)
-
-![example_0](https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/326bde19-d535-4be5-829e-782fce0c1d00)
-
-## Prerequisites
-This project is developed and tested on Python3.10.
-
-```bash
-# Create and activate a python 3.10 environment.
-conda create -n yolo-world-with-efficientvit-sam python=3.10 -y
-conda activate yolo-world-with-efficientvit-sam
-# Setup packages.
-make setup
-```
-
-## How to Run
-```bash
-python app.py
-```
-
-Open http://127.0.0.1:7860/ on your web browser.
-
-![example_1](https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/9388e4ee-6f71-4428-b17c-d218fd059949)
-
-## Core Components
-
-### YOLO-World
-[YOLO-World](https://github.com/AILab-CVC/YOLO-World) is an open-vocabulary object detection model with high efficiency.
-On the challenging LVIS dataset, YOLO-World achieves 35.4 AP with 52.0 FPS on V100,
-which outperforms many state-of-the-art methods in terms of both accuracy and speed.
-![image](https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/8a4a17bd-918d-478a-8451-f58e4a2dce79)
-<img width="1024" src="https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/fce57405-e18d-45f3-bea8-fc3971faf975">
-
-### EfficientViT SAM
-[EfficientViT SAM](https://github.com/mit-han-lab/efficientvit) is a new family of accelerated segment anything models.
-Thanks to the lightweight and hardware-efficient core building block,
-it delivers 48.9× measured TensorRT speedup on A100 GPU over SAM-ViT-H without sacrificing performance.
-
-<img width="1024" src="https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/9eec003f-47c9-43a5-86b0-82d6689e1bf9">
-<img width="1024" src="https://github.com/Curt-Park/yolo-world-with-efficientvit-sam/assets/14961526/d79973bb-0d80-4b64-a175-252de56d0d09">
-
-## Powered By
-```
-@misc{zhang2024efficientvitsam,
-  title={EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss},
-  author={Zhuoyang Zhang and Han Cai and Song Han},
-  year={2024},
-  eprint={2402.05008},
-  archivePrefix={arXiv},
-  primaryClass={cs.CV}
-}
-
-@article{cheng2024yolow,
-  title={YOLO-World: Real-Time Open-Vocabulary Object Detection},
-  author={Cheng, Tianheng and Song, Lin and Ge, Yixiao and Liu, Wenyu and Wang, Xinggang and Shan, Ying},
-  journal={arXiv preprint arXiv:2401.17270},
-  year={2024}
-}
-
-@article{cai2022efficientvit,
-  title={Efficientvit: Enhanced linear attention for high-resolution low-computation visual recognition},
-  author={Cai, Han and Gan, Chuang and Han, Song},
-  journal={arXiv preprint arXiv:2205.14756},
-  year={2022}
-}
-```