MMFashion is an open source visual fashion analysis toolbox based on PyTorch. It is a part of the open-mmlab project developed by Multimedia Lab, CUHK.
[2019-11-01] MMFashion v0.1 is released.
[2020-02-14] MMFashion v0.2 is released, adding consumer-to-shop retrieval module.
[2020-04-27] MMFashion v0.3 is released, adding fashion segmentation and parsing module.
[2020-05-04] MMFashion v0.4 is released, adding fashion compatibility and recommendation module.
[2020-12-08] MMFashion v0.5 is released, adding virtual try-on module.
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Flexible: modular design and easy to extend
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Friendly: off-the-shelf models for layman users
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Comprehensive: support a wide spectrum of fashion analysis tasks
- Fashion Attribute Prediction
- Fashion Recognition and Retrieval
- Fashion Landmark Detection
- Fashion Parsing and Segmentation
- Fashion Compatibility and Recommendation
- Fashion Virtual Try-On
git clone --recursive https://github.com/open-mmlab/mmfashion.git
cd mmfashion
python setup.py installWe provide a Dockerfile to build an image.
# build an image with PyTorch 1.5, CUDA 10.1
docker build -t mmfashion docker/Run it with
docker run --gpus all --shm-size=8g -it mmfashionPlease refer to GETTING_STARTED.md for the basic usage of MMFashion.
Please refer to DATA_PREPARATION.md for the dataset specifics of MMFashion.
Please refer to MODEL_ZOO.md for a comprehensive set of pre-trained models in MMFashion.
We appreciate all contributions to improve MMFashion. Please refer to CONTRIBUTING.md for the contributing guideline.
This project is released under the Apache 2.0 license.
- Xin Liu (veralauee)
- Jiancheng Li (lijiancheng0614)
- Jiaqi Wang (myownskyW7)
- Ziwei Liu (liuziwei7)
@inproceedings{mmfashion,
title={MMFashion: An Open-Source Toolbox for Visual Fashion Analysis},
author={Liu, Xin and Li, Jiancheng and Wang, Jiaqi and Liu, Ziwei},
booktitle={{ACM Multimedia 2021, Open Source Software Competition},
year={2021}
}