A Method for Fine-Grained Aircraft Recognition Base on Web-Supervised Network

Introduction

This is the source code for our paper A Method for Fine-Grained Aircraft Recognition Base on Web-Supervised Network

After creating a virtual environment of python 3.7, run pip install -r requirements.txt to install all dependencies

The code is currently tested only on GPU

Data Preparation

Download data into project root directory and uncompress them using

wget https://wsnfg-sh.oss-cn-shanghai.aliyuncs.com/web-aircraft.tar.gz
tar -xvf web-aircraft.tar.gz

Source Code
- If you want to train the whole network from begining using source code on the web fine-grained dataset, please follow subsequent steps
  - Choose a dataset, create soft link to dataset by
```
ln -s web-aircraft aircraft
```
  - Modify CUDA_VISIBLE_DEVICES to proper cuda device id in run_train_resnet.sh
  - Modify data to the dataset you want to use in run_train_resnet.sh
  - Activate virtual environment(e.g. conda) and then run the script
```
bash run_train_resnet.sh
```
- We recommend you use Resnet-50 model, because it has better performance.