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Congrats on what you’ve made! What sort of noise are you running in to? (Curious) In an old project we actually did something a bit more based on visual chang

Congrats on what you’ve made! What sort of noise are you running in to? (Curious) In an old project we actually did something a bit more based on visual changes. Basically detected visual diffs and got coordinates of offsets to the change. We then found the smallest html container that encompassed the diff and highlighted it. Using visual diff you can fuzz things a bit to handle artifact and small movements. A good lib we have some miles on https://github.com/mapbox/pixelmatch https://github.com/mapbox/pixelmatch And this write up on niffy is pretty good https://segment.com/blog/perceptual-diffing-with-niffy/ https://segment.com/blog/perceptual-diffing-with-niffy/

bluepeter 7y ago
In terms of overall noise, we're running into a lot. (This is what led us to ML as a way to hopefully reduce it.) Comparing the pure DOM reveals almost constant change due to various inserted Javascript from Google/Facebook/etc modifying the DOM. Looking at text/images also result in a fair amount of expected noise, but it's mostly in the form of interstitial marketing banners, fundraising targets, etc. We already have various options to "filter" out certain DOM areas. (As an example, remove all footers, headers, or any other CSS selector.) These work really well... but they require a fair bit of setup. Thanks for the pixelmatch GH repo link... I have it starred so must have taken a look in the past. We need to evolve our image diff, so we may end up using this!