High Compression Rate
pngquant can significantly reduce the file size of PNG images while maintaining a high visual quality, often achieving compression rates of 60-70%.
Lossy and Lossless Options
It offers both lossy and lossless compression options, providing flexibility based on the user's needs for quality and file size.
Cross-Platform Support
pngquant is available for multiple platforms, including Windows, macOS, and Linux, making it accessible to a wide range of users.
Open Source
Being open-source software, pngquant allows users to inspect, modify, and enhance the code, ensuring transparency and community-driven improvements.
Easy to Integrate
The command-line interface allows for easy integration into various workflows, such as automated image processing pipelines and web development projects.
Preserves Transparency
It maintains full alpha channel support, preserving the transparency of images which is crucial for web graphic design.
pngquant is a highly recommended tool for anyone looking to optimize PNG images. Its ability to balance file size reduction with image quality makes it an excellent choice for those needing efficient and reliable image compression.
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Check the traffic stats of pngquant on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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Check the "Domain Authority" of pngquant on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about pngquant on Reddit. This can help you find out how popualr the product is and what people think about it.
Optimize images at every step: Compress with mozjpeg/ pngquant, resize to actual display dimensions, serve progressive JPEGs, and use CDNs with on-the-fly optimization (Cloudinary, imgix). - Source: dev.to / 3 months ago
No I meant lossy. This is the library I use; https://pngquant.org/. - Source: Hacker News / 6 months ago
Fair point, though not entirely true: you can run an image through lossy compression and store the result in a PNG, using tools like pngquant [1]. Likely not as efficient for many kinds of images, but totally doable. [1] https://pngquant.org/. - Source: Hacker News / 8 months ago
The cornerstone of our enhancement is libimagequant-wasm, a WebAssembly port of the industry-standard pngquant library. This library uses a sophisticated color quantization algorithm that produces visually superior results compared to simple palette reduction. - Source: dev.to / 9 months ago
Nice. I have a command similar to the one listed "removeexif" called prep_for_web which takes any image file (PNG, BMP, JPG, WebP), scrubs EXIF data, checks for transparency and then compresses it to either JPG using MozJPEG or to PNG using PNGQuant. [1] https://github.com/mozilla/mozjpeg [2] https://pngquant.org. - Source: Hacker News / 9 months ago
Image-shrinker is a simple, easy to use open source tool for shrinking images. Under the hood it uses pngquant, mozjpg, SVGO, and gifsicle. You can also install these tools individually if you need to compress some images. I often use pngquantafter exporting PNGs for web projects from Figma or similar tools. I literally run it like this:. - Source: dev.to / almost 3 years ago
Searching more I found https://pngquant.org/ which I could add to my bulk workflow to make most png's approach the jpeg size. Source: about 3 years ago
But this did prompt me to do some searching, and I see https://pngquant.org/ which seems to achieve jpeg like size reduction while maintaining the file as a png. One difference they note is that this method will typically preserve sharp edges better than jpeg (which is probably a strong plus for my type of use case). Source: about 3 years ago
Pngquant is also great for shaving filesizes down, but unlike oxipng, it's explicitly lossy. It'll reduce colors and even dither, but it will try to keep an image visually similar. Https://pngquant.org/. Source: over 3 years ago
Oxipng, pngquant and svgcleaner โ optimizing images. Source: over 3 years ago
-https://pngquant.org/ compress png without losing transparency. Source: over 3 years ago
In most cases we're trying to use svg. In case of png's, to compress it we use this tool https://pngquant.org/. Source: over 3 years ago
Gif's uses a limited palette of 256 colors. How do you make that palette. There are many options just here. A user defined palette, a palette based on the average use of colors (perceptually based on the human eye or just based on raw image data), create it using the pngquant library or maybe some machine learning voodoo? And these are just the one I could think of right now:) Following that, should you be able... Source: over 3 years ago
While you are correct, in real world tools like https://pngquant.org/ blur the line. Source: over 3 years ago
I'd like to give a shoutout to pngquant. https://pngquant.org/. Source: almost 4 years ago
AVIF is the example. It supports palette-based blocks in addition to classic DCT with sophisticated deringing. There's also https://pngquant.org and https://github.com/richgel999/rdopng. - Source: Hacker News / almost 4 years ago
Any LiveArea assets HAVE to be 8-bit indexed AND have to be the sizes listed. Otherwise VPK installation will fail I like to use pngquant. Source: about 4 years ago
If your dataset allows it, I would look at pngquant for "lossy" compression of PNG images by means of color quantization: https://pngquant.org/ This works absolute wonders if you are talking about images with a limited amount of colors and without many gradients. I use it to compress screenshots of websites, which, if you think about it, are mostly large blobs of uniform colors with hard edges. I also use it every... - Source: Hacker News / about 4 years ago
Except that you don't know that with PNG either, other than for images you've transcoded yourself. Plenty of PNG optimization programs use lossy methods (AFAIK mostly color quantization, see pngquant), and you can't know if an image you got off the internet has been run through such a processor. And besides, you never know what's been done to the image prior to it being converted to PNG, making it non-lossless. Source: about 4 years ago
Generally speaking, absolutely. In this case, no. These were core contributors to AV1, JPG XL, and so on. For example, one of them was Kornelski, the guy who wrote https://gif.ski/ and https://pngquant.org/. They know more about this shit than you and me, and between also explained to me how bad a choice APNG was. Source: over 4 years ago
While full PNG is lossless, you can still do lossy 8-bit PNG with pngquant, using a custom palette - and it is an excellent way to optimize a PNG for size while minimizing quality loss. It is not going to win you any awards for medical photography, but if you are producing graphics for the web, pngquant is awesome. It is kinda-like mozjpeg for PNGs. Source: over 4 years ago
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