Code for our paper A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization,

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Deep Learning FSRA
Overview

FSRA

This repository contains the dataset link and the code for our paper A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization, IEEE Transactions on Circuits and Systems for Video Technology. Thank you for your kindly attention.

requirement

  1. Download the University-1652 dataset
  2. Configuring the environment
    • First you need to configure the torch and torchision from the pytorch website
    • pip install -r requirement.txt

Download pre-training weights

You can download the pre-training weight from the following link and put them in the pretrain_model folder

  1. Baidu Driver code: 52n2

  2. Google Driver

Train and Test

We provide scripts to complete FSRA training and testing

  • Change the data_dir and test_dir paths in train_test_local.sh and then run:
bash train_test_local.sh
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Comments
  • About the dataset samper

    About the dataset samper

    Hi! Amazing work! In Dataloader_University.py transform_train_list ={"satellite": transforms.Compose(transform_train_list), "train":transforms.Compose(transform_train_list)} datasets = Dataloader_University(root="/home/wang_tuo/graduate/University-Release/train",transforms=transform_train_list,names=['satellite','drone']) samper = Sampler_University(datasets,8) ValueError: sampler should be an instance of torch.utils.data.Sampler, but got sampler=<main.Sampler_University object at 0x7f16a2d8b6d8>

    I can't use the class

    opened by Acmenwangtuo 0
Owner
Dmmm
Dmmm
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