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Model: IDEA-Research/Rex-Omni
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IDEA License 1.0
This License Agreement (as may be amended in accordance with this License Agreement, “License”), between you, or your employer or other entity (if you are entering into this agreement on behalf of your employer or other entity) (“Licensee” or “you”) and the International Digital Economy Academy (“IDEA” or “we”) applies to your use of any computer program, algorithm, source code, object code, or software that is made available by IDEA under this License (“Software”) and any specifications, manuals, documentation, and other written information provided by IDEA related to the Software (“Documentation”).
By downloading the Software or by using the Software, you agree to the terms of this License. If you do not agree to this License, then you do not have any rights to use the Software or Documentation (collectively, the “Software Products”), and you must immediately cease using the Software Products. If you are agreeing to be bound by the terms of this License on behalf of your employer or other entity, you represent and warrant to IDEA that you have full legal authority to bind your employer or such entity to this License. If you do not have the requisite authority, you may not accept the License or access the Software Products on behalf of your employer or other entity.
1. LICENSE GRANT
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b. The grant of rights expressly set forth in this Section 1 (License Grant) are the complete grant of rights to you in the Software Products, and no other licenses are granted, whether by waiver, estoppel, implication, equity or otherwise. IDEA and its licensors reserve all rights not expressly granted by this License.
c. If you intend to use the Software Products for any commercial purposes, you must request a license from IDEA, which IDEA may grant to you in its sole discretion.
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a. If you distribute or make the Software Products, or any derivative works thereof, available to a third party, you shall provide a copy of this Agreement to such third party.
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d. Your use of the Software Products must comply with applicable laws and regulations (including trade compliance laws and regulations).
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6. TERMINATION; SURVIVAL
a. This License will automatically terminate upon any breach by you of the terms of this License.
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8. APPLICABLE LAW; DISPUTE RESOLUTION
This License will be governed and construed under the laws of the Peoples Republic of China without regard to conflicts of law provisions. The parties expressly agree that the United Nations Convention on Contracts for the International Sale of Goods will not apply. Any suit or proceeding arising out of or relating to this License will be brought in the courts, as applicable, in Shenzhen, Guangdong, and each party irrevocably submits to the jurisdiction and venue of such courts.

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---
base_model:
- Qwen/Qwen2.5-VL-3B-Instruct
language:
- en
pipeline_tag: image-text-to-text
tags:
- vision
- object-detection
- multimodal
- ocr
- keypoint-detection
- visual-prompting
- open-set-detection
- object-pointing
library_name: transformers
license: other
---
This model is **Rex-Omni**, a 3B-parameter Multimodal Large Language Model (MLLM) presented in the paper "[Detect Anything via Next Point Prediction](https://huggingface.co/papers/2510.12798)". It is compatible with the Hugging Face `transformers` library and is licensed under the [IDEA License 1.0](https://github.com/IDEA-Research/Rex-Omni/blob/main/LICENSE).
<div align=center>
<img src="assets/logo.png" width=600 >
</div>
<h1 align="center">Detect Anything via Next Point Prediction</h1>
<div align=center>
<p align="center">
<a href="https://rex-omni.github.io/">
<img
src="https://img.shields.io/badge/RexOmni-Website-BADFDB?style=flat-square&logo=deno&logoColor=violet&color=BADFDB"
alt="RexThinker Website"
/>
</a>
<a href="https://arxiv.org/abs/2510.12798">
<img
src="https://img.shields.io/badge/RexOmni-Paper-Red%25red?logo=arxiv&logoColor=red&color=yellow"
alt="RexThinker Paper on arXiv"
/>
</a>
<a href="https://huggingface.co/IDEA-Research/Rex-Omni">
<img
src="https://img.shields.io/badge/RexOmni-Weight-orange?logo=huggingface&logoColor=yellow"
alt="RexThinker weight on Hugging Face"
/>
</a>
<a href="https://huggingface.co/spaces/Mountchicken/Rex-Omni">
<img
src="https://img.shields.io/badge/RexOmni-Demo-orange?logo=huggingface&logoColor=yellow"
alt="RexThinker Demo on Hugging Face"
/>
</a>
<a href="https://github.com/IDEA-Research/Rex-Omni">
<img
src="https://img.shields.io/badge/GitHub-Code-blue?logo=github&logoColor=white"
alt="GitHub Code"
/>
</a>
</p>
</div>
> Rex-Omni is a 3B-parameter Multimodal Large Language Model (MLLM) that redefines object detection and a wide range of other visual perception tasks as a simple next-token prediction problem.
<p align="center"><img src="assets/teaser.png" width="95%"></p>
## 🚀 Quick Start
### Installation
```bash
conda create -n rexomni -m python=3.10
pip install torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cu124
git clone https://github.com/IDEA-Research/Rex-Omni.git
cd Rex-Omni
pip install -v -e .
```
## 2. Quick Start: Using Rex-Omni for Detection
```python
from PIL import Image
from rex_omni import RexOmniWrapper, RexOmniVisualize
# Initialize model
model = RexOmniWrapper(
model_path="IDEA-Research/Rex-Omni",
backend="transformers" # or "vllm"
)
# Load image
image = Image.open("your_image.jpg")
# Object Detection
results = model.inference(
images=image,
task="detection",
categories=["person", "car", "dog"]
)
result = results[0]
# 4) Visualize
vis = RexOmniVisualize(
image=image,
predictions=result["extracted_predictions"],
font_size=20,
draw_width=5,
show_labels=True,
)
vis.save("visualize.jpg")
```
## 3. Tutorials
We provide a series of tutorials to help you get started with Rex-Omni.
- [Detection Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/detection_example/_full_notebook.ipynb)
- [Pointing Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/pointing_example/_full_tutorial.ipynb)
- [OCR Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/ocr_example/_full_tutorial.ipynb)
- [Keypointing Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/keypointing_example/_full_tutorial.ipynb)
- [Visual Prompting Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/visual_prompting_example/_full_tutorial.ipynb)
- [Batch Inference Example](https://github.com/IDEA-Research/Rex-Omni/blob/master/tutorials/other_example/batch_inference.py)
## 📄 License
Rex-Omni is licensed under the [IDEA License 1.0](LICENSE), Copyright (c) IDEA. All Rights Reserved. This model is based on Qwen, which is licensed under the [Qwen RESEARCH LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct/blob/main/LICENSE), Copyright (c) Alibaba Cloud. All Rights Reserved.
## 🔗 Links
- 🏠 [Homepage](https://rex-omni.github.io/)
- 🎮 [Demo](https://huggingface.co/spaces/Mountchicken/Rex-Omni)
## 📧 Contact
For questions and feedback, please contact us at:
- Email: jiangqing@idea.edu.cn
- GitHub Issues: [IDEA-Research/Rex-Omni](https://github.com/IDEA-Research/Rex-Omni/issues)
## 7. Citation
Rex-Omni comes from a series of prior works. If youre interested, you can take a look.
- [RexThinker](https://arxiv.org/abs/2506.04034)
- [RexSeek](https://arxiv.org/abs/2503.08507)
- [ChatRex](https://arxiv.org/abs/2411.18363)
- [DINO-X](https://arxiv.org/abs/2411.14347)
- [Grounidng DINO 1.5](https://arxiv.org/abs/2405.10300)
- [T-Rex2](https://link.springer.com/chapter/10.1007/978-3-031-73414-4_3)
- [T-Rex](https://arxiv.org/abs/2311.13596)
```bibtex
@misc{jiang2025detectpointprediction,
title={Detect Anything via Next Point Prediction},
author={Qing Jiang and Junan Huo and Xingyu Chen and Yuda Xiong and Zhaoyang Zeng and Yihao Chen and Tianhe Ren and Junzhi Yu and Lei Zhang},
year={2025},
eprint={2510.12798},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2510.12798},
}
```

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preprocessor_config.json Normal file
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{
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}

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