--- 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:
. ├── scene_info: *.npz (e.g. Tokyo3_100@-98@-185@67@0@90.npz) ├── geo_info: *.txt (e.g. Tokyo_3.txt, see below) └── [city_id] (e.g. Tokyo3) ├── computed_pairs.txt ├── overlap_5_30.txt ├── overlap_30_50.txt ├── overlap_50_plus.txt ├── query │ ├── intrinsic.txt (see below) │ ├── poses.txt (see below) │ ├── depth: *.exr │ └── rgb: *.jpg └── reference ├── intrinsic.txt (see below) ├── poses.txt (see below) ├── depth: *.exr └── rgb: *.jpg- 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)