Homography patches dataset

This repository contains the code for evaluating feature descriptors on the HPatches dataset. For more information on the methods and the evaluation protocols please check [1].

Benchmark implementations

We provide two implementations for computing results on the HPatches dataset, one in python and one in matlab.

python	matlab
details	details

Benchmark Tasks

Details about the benchmarking tasks can he found here.
For a more in-depth description, please see the CVPR 2017 paper [1].

Benchmark Data

The data required for the benchmarks are saved in the ./data folder, and are shared between the two implementations.

To download the HPatches image dataset, run the provided shell script with the hpatches argument.

sh download.sh hpatches

To download the pre-computed files of a baseline descriptor X on the HPatches dataset, run the provided download.sh script with the descr X argument.

To see a list of all the currently available descriptor file results, run scipt with only the descr argument.

sh download.sh descr       # prints all the currently available baseline pre-computed descriptors
sh download.sh descr sift  # downloads the pre-computed descriptors for sift

The HPatches dataset is saved on ./data/hpatches-release and the pre-computed descriptor files are saved on ./data/descriptors.

References

[1] HPatches: A benchmark and evaluation of handcrafted and learned local descriptors, Vassileios Balntas*, Karel Lenc*, Andrea Vedaldi and Krystian Mikolajczyk, CVPR 2017. *Authors contributed equally.