SearchAndRescueNet

KO | EN

gitlite — search

#javascript #python #llm #go #android #linux #macos #java #awesome #cli #pytorch #mcp #ios #open-source

SearchAndRescueNet

(★ 63)

No description available.

File Explorer

Download Latest Version (.zip)

- 011490.jpg
- 015300.jpg
- 017562.jpg
- 022460.jpg
- 026094.jpg
- 032776.jpg
- 034121.jpg
- 041238.jpg
- 045442.jpg
- 046762.jpg
README.md
SaRNet_Demo.ipynb
SaRNet_train_test.ipynb

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Satellite Imagery for Search And Rescue Dataset - [ArXiv](https://arxiv.org/pdf/2107.12469.pdf)

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.

![anomaly](https://michaeltpublic.s3.amazonaws.com/images/anomaly_small.jpg)

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](https://www.immersivelimit.com/tutorials/create-coco-annotations-from-scratch), and is directly compatible with faster r-cnn as implemented in Facebook's [Detectron2](https://github.com/facebookresearch/detectron2).

## Getting hold of the Data

Download the data here: [sarnet.zip](https://michaeltpublic.s3.amazonaws.com/sarnet.zip)

Or follow these steps

```shell
# 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](https://github.com/michaelthoreau/SearchAndRescueNet/blob/master/SaRNet_Demo.ipynb)

## Source Code for Paper
Source code for the paper is located here: [SaRNet_train_test.ipynb](https://github.com/michaelthoreau/SearchAndRescueNet/blob/master/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.

SearchAndRescueNet

File Explorer

Today's picks

Was this content helpful?

Recent Feedback

SearchAndRescueNet

File Explorer

Today's picks

Was this content helpful?

Recent Feedback

Download README