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README.md
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# BriVL
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BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果,超过了同期其他常见的多模态预训练模型(例如UNITER、CLIP)。
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BriVL论文:[WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training](https://arxiv.org/abs/2103.06561)
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# 适用场景
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适用场景示例:图像检索文本、文本检索图像、图像标注、图像零样本分类、作为其他下游多模态任务的输入特征等。
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# 技术特色
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1. BriVL使用对比学习算法将图像和文本映射到了同一特征空间,可用于弥补图像特征和文本特征之间存在的隔阂。
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2. 基于视觉-语言弱相关的假设,除了能理解对图像的描述性文本外,也可以捕捉图像和文本之间存在的抽象联系。
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3. 图像编码器和文本编码器可分别独立运行,有利于实际生产环境中的部署。
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# 下载专区
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| 模型 | 语言 | 参数量(单位:亿) | 文件(file) |
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| --------- | ---- | ------------------ | --------------------------- |
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| BriVL-1.0 | 中文 | 10亿 | BriVL-1.0-5500w.tar|
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# 使用BriVL
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### 搭建环境
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```
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# 环境要求
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lmdb==0.99
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timm==0.4.12
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easydict==1.9
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pandas==1.2.4
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jsonlines==2.0.0
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tqdm==4.60.0
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torchvision==0.9.1
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numpy==1.20.2
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torch==1.8.1
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transformers==4.5.1
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msgpack_numpy==0.4.7.1
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msgpack_python==0.5.6
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Pillow==8.3.1
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PyYAML==5.4.1
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```
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配置要求在requirements.txt中,可使用下面的命令:
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```
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pip install -r requirements.txt
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```
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### 特征提取与计算检索结果
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```
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cd evaluation/
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bash test_xyb.sh
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```
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### 数据解释
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现已放入3个图文对示例:
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```
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./data/imgs # 放入图像
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./data/jsonls # 放入图文对描述
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```
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# 引用BriVL
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```
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@article{DBLP:journals/corr/abs-2103-06561,
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author = {Yuqi Huo and
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Manli Zhang and
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Guangzhen Liu and
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Haoyu Lu and
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| 81 |
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Yizhao Gao and
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Guoxing Yang and
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Jingyuan Wen and
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Heng Zhang and
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Baogui Xu and
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Weihao Zheng and
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Zongzheng Xi and
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Yueqian Yang and
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| 89 |
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Anwen Hu and
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Jinming Zhao and
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Ruichen Li and
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Yida Zhao and
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| 93 |
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Liang Zhang and
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| 94 |
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Yuqing Song and
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Xin Hong and
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| 96 |
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Wanqing Cui and
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| 97 |
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Dan Yang Hou and
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Yingyan Li and
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Junyi Li and
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Peiyu Liu and
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Zheng Gong and
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Chuhao Jin and
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Yuchong Sun and
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Shizhe Chen and
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Zhiwu Lu and
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Zhicheng Dou and
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Qin Jin and
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Yanyan Lan and
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Wayne Xin Zhao and
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| 110 |
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Ruihua Song and
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Ji{-}Rong Wen},
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title = {WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training},
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journal = {CoRR},
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volume = {abs/2103.06561},
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year = {2021},
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url = {https://arxiv.org/abs/2103.06561},
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archivePrefix = {arXiv},
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eprint = {2103.06561},
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timestamp = {Tue, 03 Aug 2021 12:35:30 +0200},
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biburl = {https://dblp.org/rec/journals/corr/abs-2103-06561.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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