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.
-
Flexible: modular design and easy to extend
-
Friendly: off-the-shelf models for layman users
-
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 install
We 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 mmfashion
Please 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)
@article{mmfashion,
title={MMFashion: An Open-Source Toolbox for Visual Fashion Analysis},
author={Liu, Xin and Li, Jiancheng and Wang, Jiaqi and Liu, Ziwei},
journal= {arXiv preprint arXiv:2005.08847},
year={2020}
}