COCO-Caption2017

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# Large-scale Multi-modality Models Evaluation Suite

> Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval`

🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab)

# This Dataset

This is a formatted version of [COCO-Caption-2017-version](https://cocodataset.org/#home). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models.

```
@misc{lin2015microsoft,
title={Microsoft COCO: Common Objects in Context},
author={Tsung-Yi Lin and Michael Maire and Serge Belongie and Lubomir Bourdev and Ross Girshick and James Hays and Pietro Perona and Deva Ramanan and C. Lawrence Zitnick and Piotr Dollár},
year={2015},
eprint={1405.0312},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```

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<img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%">
</p>

# 大规模多模态模型评测套件

> 借助`lmms-eval`加速大规模多模态模型（Large-scale Multi-modality Models, LMMs）的研发

🏠 [主页](https://lmms-lab.github.io/) | 📚 [文档](docs/README.md) | 🤗 [Huggingface数据集仓库](https://huggingface.co/lmms-lab)

## 本数据集
本数据集为[COCO-Caption-2017版本](https://cocodataset.org/#home)的格式化版本，被集成至我们的`lmms-eval`评测流水线中，可实现大规模多模态模型的一键评测。

@misc{lin2015microsoft,
title={Microsoft COCO: Common Objects in Context},
author={Tsung-Yi Lin and Michael Maire and Serge Belongie and Lubomir Bourdev and Ross Girshick and James Hays and Pietro Perona and Deva Ramanan and C. Lawrence Zitnick and Piotr Dollár},
year={2015},
eprint={1405.0312},
archivePrefix={arXiv},
primaryClass={cs.CV}
}

搜集汇总

背景与挑战

背景概述

COCO-Caption2017是COCO-Caption-2017-version的格式化版本，专为评估大型多模态模型而设计，基于Microsoft COCO数据集构建，适用于计算机视觉领域的研究。