Implement of Deep Multi-attribute Recognition model under ResNet50 backbone network

Preparation

1. Install Pytorch

2. Download and prepare the dataset as follow:

   a. PETA Baidu Yun, passwd: 5vep, or Google Drive.

   ./dataset/peta/images/*.png
   ./dataset/peta/PETA.mat
   ./dataset/peta/README

   python script/dataset/transform_peta.py 

   b. RAP Google Drive.

   ./dataset/rap/RAP_dataset/*.png
   ./dataset/rap/RAP_annotation/RAP_annotation.mat

   python script/dataset/transform_rap.py

   c. PA100K Links

   ./dataset/pa100k/data/*.png
   ./dataset/pa100k/annotation.mat

   python script/dataset/transform_pa100k.py 

   d. RAP(v2) Links.

   ./dataset/rap2/RAP_dataset/*.png
   ./dataset/rap2/RAP_annotation/RAP_annotation.mat

   python script/dataset/transform_rap2.py

Train the model

   sh script/experiment/train.sh

Test the model

   sh script/experiment/test.sh

Demo

   python script/experiment/demo.py

Citation

Please cite this paper in your publications if it helps your research:

@inproceedings{li2015deepmar,
    author = {Dangwei Li and Xiaotang Chen and Kaiqi Huang},
    title = {Multi-attribute Learning for Pedestrian Attribute Recognition in Surveillance Scenarios},
    booktitle = {ACPR},
    pages={111--115},
    year = {2015}
}

Thanks