Bottle VS spleeter

Bottle.py: uber-fast and simple python web microframework, about 3x faster, saner, and more memory-efficient than Flask in my experience: https://github.com/bottlepy/bottle

Fossil: distributed version control and much more in a single executable, from the creators of SQLite: https://fossil-scm.org/

Here's a web framework in a single file: bottle.py

I don't do much development for microcontrollers or limited resource environments, but it's nice to have a low boilerplate tool for throwing together quick web apps. I've used Bottle for that in the past. It looks like this might have more of an API focus, rather than templates or static pages? Very cool, will check it out.

There was a time, I want to start a new project and have to choose what technologies to use for the frontend and backend parts as well. Research gets me to Aqueduct and Shelf, both of them weren't looking actively developing and supported and that leads me to the idea to make my own small micro-framework like Echo for Golang or Bottle for Python. And it was easy to decide: I've had time and motivation :)

It was developed by Marcel Hellkamp and Bottle was initially released on July 1 2009 it is cross-platform and open-source. its Github repository is https://github.com/bottlepy/bottle. It is integrated with Python, Vue JS, and Jinja.

This post inspired me to check on Bottle, and it can't say the same: https://github.com/bottlepy/bottle

why not https://github.com/bottlepy/bottle the first python micro framework less than 5k of lines,

Another option you might want to look in to is small web server stuff. I do a lot of prototyping of REST services using Bottle (http://bottlepy.org/). It's so easy to get going and works really well. Plus my code is so decoupled that if I promote to a heavier-weight server I don't really have to worry much about it.

Raymond Hettinger recommended bottle in one of his talks for exactly this reason, https://github.com/bottlepy/bottle

I tried to use it but I had some issues as others in the thread.

I have tried many sources and method over the years and settled on spleeter [0]. Works well even for 10+ minute songs, varying styles from flamenco to heavy metal.

[0] https://github.com/deezer/spleeter

Chopped from their website Simple Stems is a quick and easy way to decompose any audio into it’s constituent parts. The plugin uses the well established Spleeter algorithm by Deezer to deconstruct songs into 2, 4 or 5 stems. The results are stunning, though more complicated mixes and live recordings are not always perfectly decomposed.

I was going to post basic pitch from Spotify but it looks like billconan beat me to it. That said I can give you a bit more advice. The Spotify basic pitch model isn't too good at multi-track input. It's capable of it, but you may actually get better results if you separate out the tracks first and then run them individually through the basic pitch model.

In order to do this you can use a source/stem separation model like spleeter (https://github.com/deezer/spleeter) and then run the basic pitch model (or any other midi transcription model). There's other you can try which may yield better results, for example: (https://github.com/Music-and-Culture-Technology-Lab/omnizart)

Either way the key words you want to be looking for are "midi transcription" and "stem separation", should help you find more models to try for both steps. Good luck! :)

I'm chasing my white whale, which is to create a real-time version of the audio stem separation tool 'Spleeter' that I've been using for a few years now to remove instruments like drums/bass guitar from existing music so that I can play along at home.

I use Spleeter.

Some of you have probably heard of spleeter, a machine learning program developed by Deezer that isolates instruments. It was pretty good, but it had some obvious weaknesses. But what if I told you that there's something even better? Ultimate Vocal Remover is so good I audibly said "holy sh*t" when I listened to what it produced. It recently released a full-band model (UVR-MDX-NET Inst HQ 1), unlike spleeter which has an 11kHz cutoff.

I'm actually planning on using something like spleeter to create drumless tracks from youtube videos on a website where people can share the pre-synced music sheets and audio.

2) It's possible to separate vocals (and other stems) using software like Demucs, LALAL.AI, etc... While it isn't a perfect solution, the technology for this is getting better and better. I originally used Spleeter but now exclusively use Demucs (v4) since the results are highly impressive. If you're not comfortable setting up a python environment, there are some websites like AudioStrip that allow you to try it online with limitations.