If you need to resize an image on the backend, APIs also work, or there are many image processing libraries available for various languages. If you need to resize an image for upload, using a library like react-image-file-resizer, or an API like AbstractAPI’s Image Processing API are excellent solutions. If you are simply resizing a loaded image for display, setting the height and width attributes via CSS or HTML may be enough. There are many ways to resize images in code, and the method you choose will depend on the language you are using, and what the resulting image will be used for. Keep in mind that the API only provides the option for lossy image compression, so when compressing any image in this way, there will be some small decrease in the image quality. Let’s now take a look at simple lossy image compression using the AbstractAPI endpoint. When false, the image filesize will still be reduced a small amount (about 10-20%) but there will be no affect on the image quality. If the option is omitted, it defaults to false. AbstractAPI provides a lossy option to specify whether you would like the API to use lossy compression to compress the file size. The image quality will not be affected by this process. Other options include the ability to resize the image to the exact height and width given, without maintaining the aspect ratio, or to crop the image to fit into a given width and height (through the exact, and fit strategies.) In this case, because we set the resize options to resize just the width and use the auto strategy, the image will be resized to the specified width and the aspect ratio will be maintained. "url": "url of the image hosted by Abstract API for you to download. "final_width": "final width in pixels of the image", "final_height": "final height in pixels of the image", "bytes_saved": "the number of bytes saved by compressing and resizing the image", "final_size": "the size of the new image, in bytes", "original_width": "original width in pixels of the image", "original_height": "original height in pixels of the image", "original_size": "the size of the original input image, in bytes", AWS Lambda functions can be built to handle image compression, and a plethora of APIs exist specifically to handle image manipulation, resizing needs, and transform images in a multitude of other ways. In today’s world, though, serverless architecture is becoming more and more prevalent, and developers are turning to APIs to handle many of the backend tasks that they used to code themselves. PIL is a popular Python image manipulation library, and jimp and sharp are two great options for working with images in Node. Libraries like react-image-file-resizer are popular options for those working with React on the frontend. There are many ways to transform images within code to get a high-quality resized image. Image compression and resizing allow a site to serve responsive images and resized images fast, and enable faster image uploads. Not only that, the prevalence of images in websites and applications is more ubiquitous than ever. The upshot of this is that as image quality has increased, file size has also increased.
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