This is W1BS descriptors benchmark from paper WxBS: Wide Baseline Stereo Generalizations .

Dataset format:

data/W1BS/ - directories with subsets. G - geometry, A - appearance, S - sensor, map2photo - map vs. photo
Each directory contains: 1: regerence image dir, 2 - "noised" image dir, h - homography 1to2 dir
each image dir contains several images, e.g. dir (data/W1BS/G/1) = 
[arch.keys  obama.keys  vprice0.keys  vprice1.keys  vprice2.keys  yosemite.keys
arch.png   obama.png   vprice0.png   vprice1.png   vprice2.png   yosemite.png]
*.png = image, *.keys = text file with affine keypoints in format: 
    npoints
    x y 5.192*s a11 a12 a21 a22
*.bmp - hpatches-style column image with pre-extracted patches

How to get example results (for now, SIFT, BRIEF and ResizeTo11x11 descriptors are available ):

cd data
./download_W1BS_dataset.sh
cd ../code
./do_everything.sh

To add your descriptor to benchmark, please add corresponding script to code/descriptors directory.

The provided file should take two arguments: path to input image input_img.bmp and path to output text file with descriptors.

Output file: one space separated line for one descriptor. Please, see example in code/descriptors/Pixels11.py or code/descriptors/SIFT.py

Citation

Please cite us if you use this code:

@InProceedings{Mishkin2015WXBS,
 author = {{Mishkin}, D. and {Matas}, J. and {Perdoch}, M. and {Lenc}, K. },
 Booktitle = {Proceedings of the British Machine Vision Conference},
 Publisher                = {BMVA},
 title = "{WxBS: Wide Baseline Stereo Generalizations}",
 year = 2015,
 month = sep,}