3 Matching Annotations
  1. Aug 2023
    1. After running the tests, I ended up with six profiles (three cached, three uncached). I’ve made those public, and you can find links to them below. First up, here’s a TL;DR of the key findings:Across all tests, loading the WebP page had the lowest energy consumption.Across all tests, loading the AVIF page had the highest energy consumption.JPEG was close to WebP in most tests.The uncached tests are fairly consistent. Testing when images are cached, however, has some wild variability. More testing is probably needed there.

      Fershad Irani looked at power consumption of images in websites. WebP came out on top (to his surprise) and JPG close. By the looks of it this is power consumption on the browser side. I suppose on the server side, power correlates with file size. The files used has JPG at 3.5 times WebP and 6 times Avif. Is webp / avif optimised for file compression (faster transmission) and less for rendering time? Does that explain the diff between Avif and Webp? All in all no biggie to stick with jpg it seems, except for choosing lowest suitable filesizes (percentwise webp would then achieve less optimisation on the transmission side)

      via Heinz .h feed.

  2. Nov 2021
    1. We can also see that converting the original non-dithered image to WebP gets a much smaller file size, and the original aesthetic of the image is preserved.

      Favor converting images to WebP over ditchering them

  3. Apr 2016
    1. While there are assets that have not been assigned to a cluster If only one asset remaining then Add a new cluster Only member is the remaining asset Else Find the asset with the Highest Average Correlation (HC) to all assets not yet been assigned to a Cluster Find the asset with the Lowest Average Correlation (LC) to all assets not yet assigned to a Cluster If Correlation between HC and LC > Threshold Add a new Cluster made of HC and LC Add to Cluster all other assets that have yet been assigned to a Cluster and have an Average Correlation to HC and LC > Threshold Else Add a Cluster made of HC Add to Cluster all other assets that have yet been assigned to a Cluster and have a Correlation to HC > Threshold Add a Cluster made of LC Add to Cluster all other assets that have yet been assigned to a Cluster and have Correlation to LC > Threshold End if End if End While

      Fast Threshold Clustering Algorithm

      Looking for equivalent source code to apply in smart content delivery and wireless network optimisation such as Ant Mesh via @KirkDBorne's status https://twitter.com/KirkDBorne/status/479216775410626560 http://cssanalytics.wordpress.com/2013/11/26/fast-threshold-clustering-algorithm-ftca/