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FastAttr in FastReID

This project provides a strong baseline for pedestrian attribute recognition.

Datasets Preparation

We use PA100k to evaluate the model's performance. You can do download dataset from HydraPlus-Net.

Usage

The training config file can be found in projects/FastAttr/config, which you can use to reproduce the results of the repo.

For example

python3 projects/FastAttr/train_net.py --config-file projects/FastAttr/configs/pa100.yml --num-gpus 4

Experiment Results

We refer to A Strong Baseline of Pedestrian Attribute Recognition as our baseline methods and conduct the experiment with 4 GPUs. More details can be found in the config file and code.

PA100k

Method Pretrained mA Accu Prec Recall F1
attribute baseline ImageNet 80.50 78.84 87.24 87.12 86.78
FastAttr ImageNet 77.57 78.03 88.39 84.98 86.65