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---
license: mit
task_categories:
- depth-estimation
- keypoint-detection
- image-feature-extraction
pretty_name: AerialExtreMatch Train
viewer: false
tags:
- image
---
# AerialExtreMatch — Train Dataset
[Code](https://github.com/Xecades/AerialExtreMatch) | [Project Page](https://xecades.github.io/AerialExtreMatch/) | Paper (WIP)
This repo contains the **training** set for our paper *AerialExtreMatch: A Benchmark for Extreme-View Image Matching and Localization*. We also provide [**benchmark**](https://huggingface.co/datasets/Xecades/AerialExtreMatch-Benchmark) and [**localization**](https://huggingface.co/datasets/Xecades/AerialExtreMatch-Localization) datasets.
## Usage
Simply clone this repository and unzip the dataset files.
```bash
git clone git@hf.co:datasets/Xecades/AerialExtreMatch-Train
cd AerialExtreMatch-Train
unzip "*.zip"
rm -rf *.zip
rm -rf .git
```
## Dataset Structure
After unpacking each .zip file:
<pre>
.
├── scene_info: *.npz <i>(e.g. Tokyo3_100@-98@-185@67@0@90.npz)</i>
├── geo_info: *.txt <i>(e.g. Tokyo_3.txt, see below)</i>
└── [city_id] <i>(e.g. Tokyo3)</i>
├── computed_pairs.txt
├── overlap_5_30.txt
├── overlap_30_50.txt
├── overlap_50_plus.txt
├── query
│ ├── intrinsic.txt <i>(see below)</i>
│ ├── poses.txt <i>(see below)</i>
│ ├── depth: *.exr
│ └── rgb: *.jpg
└── reference
├── intrinsic.txt <i>(see below)</i>
├── poses.txt <i>(see below)</i>
├── depth: *.exr
└── rgb: *.jpg
</pre>
- Keys of `.npz` files in `scene_info`: `['poses', 'intrinsics', 'depth', 'rgb', 'overlap', 'pair']`.
- Format of `.txt` files in `geo_info`: `name lat1 lon1 lat2 lon2 alt`.
- Format of `intrinsic.txt`: `name PINHOLE w h fx fy cx cy`.
- Format of `poses.txt`: `name qw qx qy qz x y z`. (w2c) |