#### NOTE
This is a **Hugging Face dataset**. For large datasets, ensure `huggingface_hub>=1.1.3` to avoid rate limits. Learn more in the <a href="https://docs.voxel51.com/integrations/huggingface.html#loading-datasets-from-the-hub" target="_blank">Hugging Face integration docs</a>.

<a href="https://huggingface.co/datasets/Voxel51/OpenSARWake" target="_blank">![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-yellow)</a>

# Dataset Card for OpenSARWake

OpenSARWake is a benchmark dataset built for ship wake detection. This collection provides 3,973 images containing two polarization modes and 4,096 instances. Most importantly, it encompasses SAR images in the L-, C-, and X-bands, which have not been provided by previous datasets. The images in the dataset have spatial resolutions of 1.25 m to 12.5 m. The image size is 1024× 1024 pixels.

![preview](https://huggingface.co/datasets/Voxel51/OpenSARWake/resolve/main/./preview.png)

This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2383 samples.

## Installation

If you haven’t already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("dgural/OpenSARWake")

# Launch the App
session = fo.launch_app(dataset)
```

## Dataset Details

### Dataset Sources

- **Repository:** https://github.com/libzzluo/OpenSARWake?tab=readme-ov-file

## Dataset Structure

The dataset includes `ground_truth` field as well as clip embeddings for visualization

### Source Data

[Google Drive Link](https://drive.google.com/file/d/14VkPYnb1BsmOvw_JTwtVFM-_qVpc4Udu/view?usp=sharing)

#### Who are the source data producers?

Xu, Chengji and Wang, Xiaoqing

## Citation [optional]

@ARTICLE{10507047,
author={Xu, Chengji and Wang, Xiaoqing},
journal={IEEE Geoscience and Remote Sensing Letters},
title={OpenSARWake: A Large-Scale SAR Dataset for Ship Wake Recognition with a Feature Refinement Oriented Detector},
year={2024},
doi={10.1109/LGRS.2024.3392681}}