You could jump to the results section if going through the walls of code is not your cup of tea.īefore diving into the implementation we picked different types of PNGs that we want to classify. TLDR: The code works and is currently deployed in production. The next two sections are all about technical implementation. We decided to go with option number 2 and fallback to the first if performance will become a problem. Analysing images are memory and CPU intensive and could be a showstopper in the case of Image CDN where images should be processed in a reasonable time on the first request.Write a boring algorithm (we are a profitable startup after all) that would use image statistics.What if it will break free and will take over our servers/planet?!!!.ML model + training and using it in the application. We don’t have an ML expert on the Team.We have a good dataset, so we could train a model and use it. Use machine learning (we are a startup after all).We would like to distinguish between photos and illustration/logos then use lossy compression for the first and lossless for the latterĪfter the brainstorming session, we tabled two conceptually different approaches: The difference in the size is huge, and the verdict is lossy compression would be much preferable in this case.Īfter running the experiments above on the bunch of PNGs, the requirement distilled itself: There is a visible glitch in the plant’s pot texture, but most likely it will be lost to a human eye due to the number of details and colours. The difference here is 127Kb which is 46% of the original image. Let’s look at the other example where PNG used for transparency: Original PNG - 276Kb The conclusion for us here was - 8Kb doesn’t worth quality loss, and we would prefer lossless compression over lossy in this case. The lossless version is the same as the original, and we could see that the lossy image became smoother and also have some artifacts around the red notebook and shadow from the sweater. Now, let’s zoom in a bit and see what happened to quality: The difference is 8 Kb which is 3% of the original image. We use ImageMagick with WebP format here because it’s supported by all browsers: magick image.png -define webp:lossless= image.webp. Lossy compressed images are smaller compared to lossless, but they also might have visual artifacts and glitches. When is it better to use lossy or lossless compression when converting PNG to the next generation format? Though, when we use modern formats to deliver the image, they support both lossy and lossless encoding, and we can pick which one to use. Keeping the above in mind it shouldn’t be a problem to choose the format for the source image. The popular use case is product images on online shops. If you’d like to show a background of the page on some parts of the image then you make those parts transparent. We’ll look at some examples in the next section The examples could be logos, banners, illustrations. Generally, it makes sense to use lossless compressions for sharp images with few colours. JPEG could introduce visual artefacts to the image, and usually, the images with fewer details and colours are affected the most. However, it’s rarely a requirement for the Web, rather we want our images to look good. So, if it is important to display exactly the same image then PNG will be our choice. On the contrary, the resulting image is not the same when using JPEG. This is like a ZIP archive that doesn’t change the source data after you extracted it. Let’s see what the main difference between JPEG and PNG are and when we use each.įirstly, PNG is a lossless format, meaning when you compress/uncompress the image it doesn’t change. Our opensource Image CDN “transformimgs” that is available on Github is using the approach from this blog, and it works quite well in production. ![]() You can get the latest version of the library using ImageMagick docker image that I maintain. We use Go and MagickWand library in the code snippets. □ "The element refers to an image or icon via a hyperlink (see 7.3, "Simultaneous Presentation of Image Resources")."Ī few links to keep you busy today: □ ⬇️- Henri Helvetica □□ □□□ □ November 1, 2021 That means we can celebrate RFC 1866, or when the tag was introduced to the HTML spec. It’s also the 1st of November, and very appropriate to talk about images! In this article, I’ll explain why converting PNG to the next-gen format is not as straightforward and how we went about it. But JPEG and PNG are still the source of truth most of the time. Web standards came a long way, and often we use next-generation formats, such as WebP/AVIF/JpegXL, to deliver an image to the end-user. PNG and JPEG are the two oldest image formats that web developers use Choosing between lossy and lossless conversion for PNG
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