User’s Guide¶
Setting up the Dataset¶
Download the HRF dataset, take note of it’s root directory and configure the
data access using the bob
command-line configuration utility. For example:
$ conda activate your-bob-env
(your-bob-env) $ bob config set bob.db.hrf.datadir /path/to/root/of/hrf
(your-bob-env) $ bob config show #to check
You can than check if your local version of the dataset is compatible with this interface and has the standard directory tree:
$ conda activate your-bob-env
(your-bob-env) $ bob_dbmanage.py hrf checkfiles
checkfiles completed sucessfully
Protocols¶
This packages provides a default protocol that uses the train/test split as proposed by:
@ARTICLE{7420682,
author={J. I. {Orlando} and E. {Prokofyeva} and M. B. {Blaschko}},
journal={IEEE Transactions on Biomedical Engineering},
title={A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images},
year={2017},
volume={64},
number={1},
pages={16-27},
doi={10.1109/TBME.2016.2535311},
ISSN={0018-9294},
month={Jan}
}
The first five images of each category (healthy, diabtic retinopathy and glaucoma) are used for training and the remaining 30 for testing.