Knowledge is power. And if you allow your users to upload images, you also probably want to better understand what their images contain. Whether a photo is of a building, people, animals, celebrities, or a product, image processing and analysis can assist in further comprehension. The benefits of this knowledge can go beyond "merely" categorizing your content and making your image library searchable: drawing insights from user generated content can be very useful! What better way to learn more about your users than to analyze the images they upload and find out what they care about and then have the ability to display relevant content to them according to their interests or even match them with other users that share similar interests.
Allowing your users to upload their own images to your website can increase user engagement, retention and monetization. However, allowing your users to upload any image they want to, may lead to some of your users uploading inappropriate images to your application. These images may offend other users or even cause your site to violate standards or regulations.
One of the main optimization challenges for website and mobile developers is how to display sufficiently high quality images to their visitors while minimizing the image file size. A smaller image file size can lead to faster load times, reduced bandwidth costs and an improved user experience. The problem is that reducing the file size too much may lead to a lower image quality and could harm visitor satisfaction. Delivering an optimized image with just the right balance between size and quality can be quite tricky.
One of the most important things to know about compressing image files is that a smaller file size comes at the cost of a lower image quality. How much lower, and whether low enough to make a difference visually, depends on the image. Compression can be very effective at reducing the size of the image, and besides lowering the costs of storage space and bandwidth, a reduced image size goes a long way to retaining your users’ attention with faster, smaller downloads.
The Rolling Stones claim, “You can’t always get what you want”.
And when your application needs to crop hundreds or thousands of images to specific sizes within a strictly defined UI design, that frustrating Rolling Stones phrase may be ringing in your ears.
But maybe it doesn’t have to.
Every image is unique and every one of your website visitors is different. In a perfect world, we'd like to adapt each image individually to be "just right" for every user. With "just right" being perfectly cropped, using responsive dimensions, correct encoding settings and optimal quality with the best image format.
As a developer, you want to allow your users to download multiple files in a single click. An easy way to download multiple files and share them is to generate a ZIP file. When images are involved, you may also want to normalize the original images before including them in the ZIP file, by scaling them down to the same maximum resolution or converting them to the same format.
It's great to have the capability to manipulate images on the fly by using dynamic URLs to customize the images to fit the graphic design of your site or mobile application. However, what if you want to manipulate an image depending on a specific image characteristic (like its width or aspect ratio) or its contents (does it contain a face?). What you need is a way to apply a transformation to an image only if a specific condition is met. Take for example a situation where you have allocated space on your page for a user uploaded image with a width and height of 200 pixels. Furthermore, if the image contains a face you would like to zoom in and focus on the face itself, otherwise you would like to fit the entire image into the available space:
Many of the photos displayed on the internet these days are of people. If your website or mobile application displays photos that include people, you will want to make sure that their faces are included in the delivered images when cropping and manipulating them to fit your graphic design and responsive layout. You may even want to further manipulate an image according to the faces present, for example, adding a harlequin mask overlay on all of their eyes, where each mask is adjusted to the correct size and orientation (although not a typical use case, it's a cool example of using advanced facial attribute detection):