There are a few options, and which one you use depends a lot of your use case and the available documentation. The next step I took was to look into existing libraries on NPM and Github. At this point, my goal became to write my own library for GIF encoding. My article GifIt goes into more detail on that subject, and the Source Code is available if you want to check out how I went about recording the desktop. Having these sequential images is essential to this approach to GIF encoding. Electron's desktopCapturer API makes capturing the user's screen a frame at a time and then saving those images to disk possible. The Electron environment combines the features of the browser, the the features of Node, and Electron's own APIs. I have been playing around with Electron a lot lately and I decided to attempt a desktop application that could record the user's screen and then turn the captured images into a GIF. For more general information, Wikipedia is a great source, and for an in-depth breakdown of the entire specification, check out What's In a GIF. GIF images are compressed using the LZW algorithm, which provides lossless data compression. This limitation is why GIF is more suited to illustrations than photography, even though it is used for both. In GIFs as we know them today, each image is allowed a maximum palette size of 256 colors. While the PNG format has pretty much replaced GIF for single images, GIF's ability to animate a series of images keeps the format relevant and supported today. It turns out the Graphics Interchange Format was originally created by CompuServe back in the 1980s and was one of the first image formats used on the web. A good starting point is to research the history of the GIF format. url ) // It works with the `preset` query parameter const myImage4 = new URL ( "image.png?as=webp&w=150&h=120", import. url ) // You can omit one of the parameters to auto-scale const myImage3 = new URL ( "image.png?w=150", import. url ) const myImage2 = new URL ( "image.png?w=150&h=120", import.
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