Mcships database in Pascal-VOC

The code was written by Yitong-Zheng

If you use this code for your research, please cite:

Y. Zheng and S. Zhang, "Mcships: A Large-Scale Ship Dataset For Detection And Fine-Grained Categorization In The Wild," 2020 IEEE International Conference on Multimedia and Expo (ICME), London, United Kingdom, 2020, pp. 1-6, doi: 10.1109/ICME46284.2020.9102907.

Prerequisites

Linux or macOS
Python 3
CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

Install CUDA and CUDNN
Download Yolov5
Download Mcships_database_lite password: dqwu

Mcship train/test

Download a Mcship dataset (e.g. maps):
Trans the dataset into yolo format:

python voc2yolo.py

Mcships_database_lite contains 9000 imgs/annotations in Pascal-VOC
Mcships_satellite_database_lite contains 800 imgs/annotations in Pascal-VOC
Train/Val/Test/Trainval imgs are listed in .ImageSet/Main/*

Citation

If you use this code for your research, please cite our papers.

@INPROCEEDINGS{Mcships2020 ,
  author={Y. {Zheng} and S. {Zhang}},
  booktitle={2020 IEEE International Conference on Multimedia and Expo (ICME)}, 
  title={Mcships: A Large-Scale Ship Dataset For Detection And Fine-Grained Categorization In The Wild}, 
  year={2020},
  volume={},
  number={},
  pages={1-6},
  doi={10.1109/ICME46284.2020.9102907}
}

wenjuntan / Mcships