Comments (6)
Hi Alex!
Has been a great surprise to find your message.
CoffeMIDI has been the first job I did while studying data science
The original version, not implemented in web, has the option of loading a MIDI to be compared with the complete dataset. It would be nice to implement it in a future version.
Also, You are right about the LAKH dataset
I have taken hundreds of MIDI files from different places, only filtering for similarity I found a good number of duplicates and I have filtered them and finally I am left with 90k. I think that with it I could also solve the lack of a really descriptive name. Can you tell me more about the dataset and your experience with it ?
I also have seen a little of your work and I found very interesting. For sure it would be good to collaborate. Tell me more about what you have in mind.
Greetings
Patricio
from coffemidi.
Hey Patricio,
You are very welcome :) You did a good job with Coffe MIDI :)
Yes, LAKH dataset is very nice. It has all annotations and everything. It is also de-duped and contains most pub MIDIs. Its about 170k MIDIs.
I already built a very simple and efficient classifier based on LAKH. Check it out:
https://github.com/asigalov61/tegridy-tools/blob/main/tegridy-tools/notebooks/Instant_Classy_MIDI_Classifier.ipynb
It uses a simple match by MIDI notation (start-time, duration, channel, pitch, velocity). This way it is possible to achieve 70% accuracy with minimum compute costs for such a large dataset. Its not as advanced as your matching system, but it is very fast and simple.
RE: Collabing: I mostly wanted to see if I can help you with Coffe MIDI? I can't do web stuff, but I can do Python stuff. And I can also help with hosting I think. I was thinking Pythonanywhere would be a good hosting place for a project like that.
Let me know.
Alex
from coffemidi.
I'm checking Instant_Classy_MIDI_Classifier, thanks !
have you already seen the website?
it is quite simple, visually precarious, but you can see the model API working.
Check finding different gender results.
I am open to returns and points for improvement.
Because of how I have modularized the work, implementing a new dataset does not cause me a lot of work, only processing time. we can exchange our contacts in order to talk it better. I am also open to thinking about new projects.
from coffemidi.
Yes, I really liked the website and the interface :) Very nice :)
I would only suggest adding a custom MIDI option (IMHO it's very important for a system like that). And also I would clean up the names/descriptions of the files because some of them have paths in them and also extensions. In my classifier, I only leave the base file name of the MIDI. This way, it is clear what song it is.
Yes, I know that processing can be difficult, especially on a large dataset. I can help with that if you want.
And sure, if you have anything else in mind, let me know. I am primarily interested in Music AI/Algorithmic Music, so anything related would be great. :)
My email is [email protected] if you want to contact me directly.
Alex.
from coffemidi.
I think your AI knowledge and talent deserve at least one gmail hahah
great! I'm going to write you there
from coffemidi.
from coffemidi.
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