Viewing profile — ruarai

This is called 'overshoot'. See here for a good explanation https://twitter.com/CT_Bergstrom/status/1252077930286444545

Working on genomics stuff right now and gene ontology (GO) is ubiquitous. My primary complaint with GO is that it doesn't map to any statistical analyses very well

This article read a little annoying. I don't know why this PhD holder failed to find the actual paper describing the algorithm: https://www.cv-foundation.org/openaccess/content_cvp…

This is an area that needs work, but basically there's the table of 'edge intensity' that gets multiplied by a constant baseChance variable for every pixel. baseChance = 8 * sample…

This doesn't seem to have any benefit unfortunately. It seems like the current approach already produces the before-after edge effect.

Wow, that works pretty well. I was mistaken in thinking that either the Dictionary class or the process of sampling would sort them. Mind if I merge that? Or you could submit a pul…

Here's Lenna reconstructed after 30,000 samples. http://i.imgur.com/hlPonsO.png The compressed data comes out to 303KB, which isn't that great. It's a pretty noisy image.

Not sure if that applies for my purposes, since I'm not actually using linear interpolation barycentric coordinates (I don't think that's possible). The barycentric coordinates sup…

I tried your struct-of-array idea, and that's produced an okay improvement ~1%. Sorting them seems tough as the index of each value must match for each channel, so any sorting woul…

It's not very comparable to PNG, since they're designed for different types of imagery. I know currently Trigrad cannot handle text at all. In regards to your other comment, it's c…

Currently compressing the example image (the one of the flowers) with 100,000 samples takes 1.5 seconds + 1.5 seconds for AForge's edge detection. I'm sure this could be increased …