OMR Project Team 4 We have used SVM in the classifier with linear kernel as it's fast and very accurate in our case. 1. How to train the classifier? 1. You have to create a folder of the dataset containing folders for each symbol as each folder name is the label of the symbol. - You can find our naming convention here . 2. Each image should be binarized and inverted (symbols = white, background = black). 3. Then run features.py file as follow: python features.py [Dataset path] 2. The Dataset that we have used: - We have generated and collected our own dataset. - Our data set is a collection of printed and handwritten music notes. - You can find it here . 3. How much time does it take to train The classifier? - For a dataset with size about 48K images (41 MB), It takes about 5-6 minutes. 4. The Hardware that we used for training: - CPU: core i7-8750H - RAM: 16 GB