论文标题
MMFashion：一个开源工具箱，用于视觉时尚分析
MMFashion: An Open-Source Toolbox for Visual Fashion Analysis
论文作者
论文摘要
我们提出MMFashion，这是一种基于Pytorch的综合，灵活和用户友好的开源视觉时尚分析工具箱。该工具箱支持各种各样的时尚分析任务，包括时尚属性预测，时尚识别和检索，时尚地标检测，时尚解析和细分以及时尚兼容性和建议。它涵盖了时尚分析社区中几乎所有主流任务。 MmFashion拥有几个吸引人的属性。首先，mmFashion遵循模块化设计的原理。该框架分解为不同的组件，因此对于不同的定制模块，它易于扩展。此外，还提供了详细的文档，演示脚本和现成的模型，从而减轻了外行用户的负担，以利用基于深度学习的时尚分析的最新进展。我们提出的MMFashion目前是深度学习时代视觉时尚分析的最完整平台，还需要添加更多功能。该工具箱和基准可以通过提供灵活的工具包来部署现有模型并开发新的想法和方法来为蓬勃发展的研究社区提供服务。我们欢迎对这项对开放科学的不断发展的努力的所有贡献：https：//github.com/open-mmlab/mmfashion。
We present MMFashion, a comprehensive, flexible and user-friendly open-source visual fashion analysis toolbox based on PyTorch. This toolbox supports a wide spectrum of fashion analysis tasks, including Fashion Attribute Prediction, Fashion Recognition and Retrieval, Fashion Landmark Detection, Fashion Parsing and Segmentation and Fashion Compatibility and Recommendation. It covers almost all the mainstream tasks in fashion analysis community. MMFashion has several appealing properties. Firstly, MMFashion follows the principle of modular design. The framework is decomposed into different components so that it is easily extensible for diverse customized modules. In addition, detailed documentations, demo scripts and off-the-shelf models are available, which ease the burden of layman users to leverage the recent advances in deep learning-based fashion analysis. Our proposed MMFashion is currently the most complete platform for visual fashion analysis in deep learning era, with more functionalities to be added. This toolbox and the benchmark could serve the flourishing research community by providing a flexible toolkit to deploy existing models and develop new ideas and approaches. We welcome all contributions to this still-growing efforts towards open science: https://github.com/open-mmlab/mmfashion.
