GSoC 2018: Machine Learning Dataset for OMR - Week 10

Hey!
These couple of weeks are going to be a notch up in performance as many things are supposed to be taken into account. I have been testing the implementation for a couple of weeks now and getting more and more updates in the implementation as I proceed forward. I have done further testing, bringing us to the last 472 scores, completing our entire set of 988 scores. There are two issues which are needed to be resolved and some more shape additions to our Omr, Audiveris. Coming to this week's analysis,

Below is the segmented status of the project:

Current status of the project
We are done with:
1. Porting the OMR work from imeta to master.
2. Grace Notes Implementation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/27
3. Bracket Implementation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/26
4. Tuplet Implementation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/22
5. Time Signature Upper and Lower Halves annotation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/28
6. Rest Dot Implementation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/23
7. Simple Image URL for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/30
8. Staccato Dot for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/25
9. SMuFL symbols identifier for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/29
10. Repeat dot implementation for OMR tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/24
11. Crash error rectification while XML generation. - An issue which was faced while testing it on different kind of scores.
12. Testing of scores on Musescore so that they generate XML. The application has been tested on a dataset of 988 scores and it works perfectly.
13. Tuplet Implementation made better.
14. Grace Note Implementation corrected. It now has the nested approach as discussed in the issue: https://github.com/Audiveris/omr-dataset-tools/issues/27. Some samples can be seen in the comments.
Clef Implementation made better. No Sym issue corrected. Made changes for using SMuFL names in the code.
Ported all these changes to nasehim7/imeta, which is rebased with the nasehim7/2.3 which has the latest changes from MuseScore/2.3, at this moment.
https://github.com/nasehim7/MuseScore/compare/2.3...nasehim7:imeta
15. Image Format changed to support grayscale image tackling the issue: https://github.com/Audiveris/omr-dataset-tools/issues/31. Testing and resolving issues that I came across. Giving more structure to the code I wrote before. Some changes to my previous commits and adding those to imeta.
16. Initialized segmented testing of our test data set in chunks of 150 to 200 depending on the complexity of the scores. First, 165 scores are done.
17. Done testing of 350 more scores and found an issue. Worked on it. Found some missing shapes.

Added: Done with testing the remaining 472 scores. Some issues encountered and refined many of our implementation for better(mostly our nasehim7/imeta). Some shape additions again.

Key accomplishments this week
Nothing major encountered apart from two issues on which I am working. For the rest, things are working fine. Some shape additions I have noted down. Posting them in the OMR issue tracker. Will be discussing them with lasconic and Herve. I have updated my comment on the issue tracker annotating most of the symbols with their relevant links for ease.

Key tasks that stalled
None

Tasks in the upcoming week:
Working on resolving the issues as well as discussing more, the current status of the project with lasconic and Herve plus taking their reviews. Checking more into the codebase and refining the code.

We are converging towards the end of GSoC 2018 but a lot of work is needed on this project. This project is not just bound to GSoC but has a very broader time span. I will be working post-GSoC so that we can go further on this project and make it better for everyone. Hope to keep contributing and refining our work.

Wish everyone the best,
Animesh
Github: https://github.com/nasehim7