hasy 0.1.1

Martins Python Utilities

Please refer to the HASY paper for details about the dataset. If you want to report problems of the HASY dataset, please send an email to [e-mail] or file an issue at https://github.com/MartinThoma/HASY

Errata are listed in the git repository as well as the latest supplementary files like hasy_tools.py.

Contents

The contents of the HASYv2 dataset are:

• hasy-data: 168236 png images, each 32px x 32px
• hasy-data-labels.csv: Labels for all images.
• classification-task: 10 folders (fold-1, fold-2, ..., fold-10) which contain a train.csv and a test.csv each. Every line of the csv files points to one of the png images (relative to itself). If those files are used, then the hasy-data-labels.csv is not necessary.
• verification-task: A train.csv and three different test files. All files should be used in exactly the same way, but the accuracy should be reported for each one. The task is to decide for a pair of two 32px x 32px images if they belong to the same symbol (binary classification).
• hasy_tools.py: Various functions / command line tools
• symbols.csv: All classes
• README.txt: This file

How to evaluate

Classification Task

Use the pre-defined 10 folds for 10-fold cross-validation. Report the average accuracy as well as the minumum and maximum accuracy.

Verification Task

Use the train.csv for training. Use test-v1.csv, test-v2.csv, test-v3.csv` for evaluation. Report TP, TN, FP, FN and accuracy for each of the three test groups.

hasy_tools

hasy_tools.py can be used in two ways: (1) as a shell script (2) as a Python module.

If you want to get more information about the shell script options, execute

python hasy_tools.py

If you want to use hasy_tools.py as a Python module, see

python -c "import hasy_tools;help(hasy_tools)"

Changelog

• 24.01.2017, HASYv2: Points were not rendered in HASYv1; improved hasy_tools https://doi.org/10.5281/zenodo.259444
• 18.01.2017, HASYv1: Initial upload https://doi.org/10.5281/zenodo.250239