There will be several methods shown for each step.įor the sake of transparency blog post is monetised with the Topaz labs affiliate link.

This blog is a work in progress so keep coming back to see updated examples and methods. Youtube videos will show the process before and after. In this post, I’ll be taking a video from YouTube, extracting all the frames, feeding them into a ML upscaler, then stitching them back together. Someone somewhere has fed a video processing model into a Machine Learning algorithm, and then the algorithm repeats, to increase the resolution of an image. I think that is about as succinct as I can make it.

These models are then used on other images, applying the same computational paths to correct missing colour or detecting edges of colour. These neural networks are being “trained”, they are given millions of images and manipulated to weigh particular processing paths as “correct”, or “Learned”. With the advent of GPU leveraging for neural network type computation, the floodgates are creaking open on new and exciting methods of processing video and still images.Ī lot of modern methods are based on a neural network, which is a software program that compares data in virtual representations of a neuron.

Topaz upscale ai