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Satellite Imagery for Search And Rescue Dataset - ArXiv
This is a single class dataset consisting of tiles of satellite imagery labeled with potential 'targets'. Labelers were instructed to draw boxes around anything they suspect may a paraglider wing, missing in a remote area of Nevada. Volunteers were shown examples of similar objects already in the environment for comparison. The missing wing, as it was found after 3 weeks, is shown below.
The dataset contains the following:
Set | Images | Annotations |
---|---|---|
Train | 1808 | 3048 |
Validate | 490 | 747 |
Test | 254 | 411 |
Total | 2552 | 4206 |
The data is in the COCO format, and is directly compatible with faster r-cnn as implemented in Facebook's Detectron2.
Getting hold of the Data
Download the data here: sarnet.zip
Or follow these steps
# download the dataset
wget https://michaeltpublic.s3.amazonaws.com/sarnet.zip
# extract the files
unzip sarnet.zip
Getting started
Get started with a Faster R-CNN model pretrained on SaRNet: SaRNet_Demo.ipynb
Source Code for Paper
Source code for the paper is located here: SaRNet_train_test.ipynb
Cite this dataset
@misc{thoreau2021sarnet,
title={SaRNet: A Dataset for Deep Learning Assisted Search and Rescue with Satellite Imagery},
author={Michael Thoreau and Frazer Wilson},
year={2021},
eprint={2107.12469},
archivePrefix={arXiv},
primaryClass={eess.IV}
}
Acknowledgment
The source data was generously provided by Planet Labs, Airbus Defence and Space, and Maxar Technologies.