# I am the Watcher. I am your guide through this vast new twtiverse.
# 
# Usage:
#     https://watcher.sour.is/api/plain/users              View list of users and latest twt date.
#     https://watcher.sour.is/api/plain/twt                View all twts.
#     https://watcher.sour.is/api/plain/mentions?uri=:uri  View all mentions for uri.
#     https://watcher.sour.is/api/plain/conv/:hash         View all twts for a conversation subject.
# 
# Options:
#     uri     Filter to show a specific users twts.
#     offset  Start index for quey.
#     limit   Count of items to return (going back in time).
# 
# twt range = 1 14
# self = https://watcher.sour.is/conv/7vczdla
@fastidious On the loss of quality on image processing / resizing... I _think_ it might have something to do with the resampling that occurs during the resize operation. On the backend yarnd we use the gift library for most processing (_mostly just Resize() and ResizetoFit()_). PNG itself is a lossless image format with selectable compression levels depending on output size and decode speed, so I _think_ the culprit is the resampling...
@fastidious On the loss of quality on image processing / resizing... I _think_ it might have something to do with the resampling that occurs during the resize operation. On the backend yarnd we use the gift library for most processing (_mostly just Resize() and ResizetoFit()_). PNG itself is a lossless image format with selectable compression levels depending on output size and decode speed, so I _think_ the culprit is the resampling...
I'm not an expert though in resampling algorithms when it comes to resizing images. So I'm not really sure whether the Resampling we use gift.LanczosResampling is the best choice here 🤔
I'm not an expert though in resampling algorithms when it comes to resizing images. So I'm not really sure whether the Resampling we use gift.LanczosResampling is the best choice here 🤔
@prologic I will run a small research to see what's would the best resampling be. I will be looking something of a compromise, whilst trying to achieve better quality.
@fastidious Sounda good 👌
@fastidious Sounda good 👌
@prologic so I checked. It seems we are already using the best resampling method. So... hmm, yeah. Other than resizing the images less---say, instead of 850px, resize to 1000px, if bigger than 1000px---I don't see any other way to get better results.
@fastidious To be honest I'm not sure how even using an "original size" image and doing CSS size to fit or even on any app really doesn't also suffer from loss of quality due to resampling.
@fastidious To be honest I'm not sure how even using an "original size" image and doing CSS size to fit or even on any app really doesn't also suffer from loss of quality due to resampling. Resampling is a pretty common algorithm to apply to any image resizing I thought? 🤔
@fastidious To be honest I'm not sure how even using an "original size" image and doing CSS size to fit or even on any app really doesn't also suffer from loss of quality due to resampling. Resampling is a pretty common algorithm to apply to any image resizing I thought? 🤔
@prologic this is easy to test. I will pull one original, host it, and link it on a twt. Then we will compare it to the uploaded version. Granted, it will be a visual comparison only.
@fastidious Ok 👌
@fastidious Ok 👌