On June 13-14, O'Reilly held its annual Fluent + Velocity conference in San Jose and it was great! Cloudinary set up a pretty incredible booth and brought in a professional photographer to take headshots of the attendees who stopped by. Once a photo was snapped, the raw camera file was immediately uploaded to our media library and transformed into something that can be posted right away on LinkedIn.
Developers are always looking for new and creative ways to deliver content that resonates with the way users feel. Often using the latest technical innovations the market has to offer such as Artificial Intelligence (AI) and Machine Learning (ML). What better way to demonstrate innovative uses of these technology in a consumer market than capturing expressions from your users and then serving content based on that expression!
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):