GSoC 2018 - Machine Learning Dataset for OMR - Week 14

Hey! :D
This is my last week report under GSoC 2018. We have implemented all the important symbols annotation that OMR needed. Presented Herve with some missing symbols during the testing, on the issue tracker. The application works fine with all the OMR changes on master but we are still into resolving the issues with 2.3.2. I'm in touch for further queries, implementation refinement and issue tackling that will come our way. Final 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.
18. 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.
19. Resolved previous week issues.
20. Tested the entire once again to check and jot down issues. Refining. I have noted all of them and now I will be working on them. Made the imeta compatible with 2.3.2 branch as discussed.
21. Improvements in the code. Debugged few issues.
22. imeta work successfully ported and requested additions done as discussed during the start. Patch ready for master.

GSoC 2018 was amazing and I feel glad that finally, I made it to the end. Thanks to the members for letting me be a part. MuseScore is a great place to hone your skills as well as with open source contributions, you get to learn a lot about how to shape an idea into something real. It feels great that I am a part of a great project. Hope to contribute more. :D

Best,
Animesh
Github: https://github.com/nasehim7