COCO-Caption2017

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