Once upon a machine learning noise removal app
Trials, errors, dead ends and strokes of genius of two Python tinkerers writing a ML-powered noise removal app from scratch
Stemanz (right) and houseofbards (left) before starting the project. Let’s see how aged we get at the end.
It all began when I downloaded the demo version of an app that promised AI-powered noise reduction in pictures. Sure, it worked well (from acceptably well to astonishingly well depending on individual cases). Sure, it cost a lot. Thus, I was left with two options: just shelling out the cash (quickest option), or getting my hands dirty into making it myself – from scratch (most hellish option).
I chose the most obvious one.
As a rule of thumb, it's better not to suffer alone. Thus, unfortunately for him, I dragged houseofbards into this.
These blog posts will tell the tale of two self-taught Python tinkerers trying to write a working app, from the ground up, that leverages machine learning to remove noise from images. We have no idea whatsoever of what we’re doing, and we’re gonna fill all holes by best practicing:
- stealing code (I’m told it’s OK as long as you give credit to the poor souls who made the effort in the first place)
- implementing ideas without understanding them (matrix multiplication, tensor algebra, cost and loss functions, autoencoders, GANs and friends – you know they’re there, and it’s all you need. Stir the cauldron until it works.)
- approximating (this is when you know when good enough is good enough)
Join us, it’ll be fun!