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car_reid's Introduction

Vehicle Re-identification base on multi-scale methods

Project Struction

Preprocess Dataset

  • 生成推理pkl文件时选择inference为True, 则不会检索gallery图像
python generate_pkl.py veri776 --input-path ../my_veri776 --output-path ./outputs/my_veri776.pkl --inference 1

Feature Metrics fusion

  • plot_rank.py中的

Reid Process

  • 该车辆重识别网络主要由车辆解析网络, 和颜色车型识别网络组成
  • Run
python inference.py --reid-pkl-path './outputs/xxx.pkl' --ouput-path './outputs' --config './configs/my.yml'
  • 推理过程中的详细配置可参照default_config.py中的参数配置自定义的my.yml文件(建议不要修改default_config.py)
  • 得到的特征矩阵示例 image

Visualization

  • 运行plot_rank.py脚本
  • PS: 目前只是根据distmat(PVEN 全局特征加局部特征)进行排序预测
python plot_rank.py --pkl-path ./outputs/my_outputs/test_output.pkl --rank-num 5 --plot 1

image

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