ViswanathaReddyGajjala / Person-Attribute-Recognition-MarketDuke

A baseline model ( pytorch implementation ) for person attribute recognition task, training and testing on Market1501-attribute and DukeMTMC-reID-attribute dataset.

Person-Attribute-Recognition-MarketDuke

A baseline model ( pytorch implementation ) for person attribute recognition task, training and testing on Market1501-attribute and DukeMTMC-reID-attribute dataset.

Dataset

You can get Market1501-attribute and DukeMTMC-reID-attribute annotations from here. Also you need to download Market-1501 and DukeMTMC-reID dataset.
Then, create a folder named 'attribute' under your dataset path, and put corresponding annotations into the folder.

For example,

├── dataset
│   ├── DukeMTMC-reID
│       ├── bounding_box_test
│       ├── bounding_box_train
│       ├── query
│       ├── attribute
│           ├── duke_attribute.mat  

Model

Trained model are provided. You may download it from Google Drive or Baidu Drive (提取码：jpks). You may download it and move checkpoints folder to your project's root directory.

Usage

python3 train.py --data-path ~/dataset --dataset [market | duke] --model resnet50
python3 test.py --data-path ~/dataset --dataset [market | duke] --model resnet50

Result (binary classification)

Market-1501 gallery:
average accuracy: 0.9024

DukeMTMC-reID gallery:
average accuracy: 0.8800

Update

19-08-23: Released trained models.

19-01-09: Fixed the error caused by an update of market and duke attribute dataset.