Cloudinary Blog

Adding code to display an image in your application is one of the most common tasks for almost every application developer. However, when it comes to Android applications, there is no inbuilt support for any image related tasks, which could be a potential pain when Android developers need to handle loading (and reloading) images into the view, handling the caching and memory issues, and supporting simple UI functionality.

The Portable Document Format (PDF) is a popular format developed by Adobe for delivering formatted text and images. A PDF file includes a complete description of all layout elements, including text, fonts, images and layers, ensuring that the file will look identical when opened on any device. The PDF format also has the big advantage of compressing high-quality files to a relatively small file size.

Delivering video files to users can be a much more complex undertaking than many people stop to consider. There are a large variety of video formats and codecs to choose between, and various optimization parameters for encoding the videos. Parameters such as bitrate, key-frame-interval, and frame-rate will have an effect on the visual quality and bandwidth requirements when delivering the video file. To make matters worse, there are so many potential viewing devices out there (desktops, laptops, tablets, mobiles, wearables, etc). Each of these devices have different browsers or apps, and they all support different formats and codecs!

With Cloudinary's transformation options, you as web or mobile developers can manipulate images in real time through dynamic URLs, from optimization and responsive delivery to other tasks, complete with cool effects. For example, a robust transformation applies another image to displace your base image with a mapping algorithm that evaluates the base image's pixels, displacing them according to the intensity of the corresponding image's map pixels.

Cloudinary offers a wide array of image manipulations and effects to apply to images as part of our image-processing pipeline, helping to ensure that your images fit the graphic design of your website or mobile application. Cloudinary is an open platform, and you can use our APIs, Widgets and UI to build the media management flow that matches your needs.

Recently we added the Cloudinary Demo - eCommerce App to the Google Play Store. This app demonstrates the best practices for optimal delivery of images on a storefront, including category pages, product pages, and a shopping cart. At the time, we published Introducing the Cloudinary Demo Android App, Part 1, which provided an under-the-hood tour of how the eCommerce Android App was designed and how Cloudinary was integrated throughout.

At Cloudinary, we manage the entire pipeline of media assets for thousands of customers of varying sizes from numerous verticals. Cloudinary is an end-to-end solution for all your image and video needs, including upload, storage, administration, manipulation, optimization and dynamic delivery.

Cloudinary has recently added the Cloudinary Demo - eCommerce App to the Google Play Store. The App demonstrates the best practices for optimal delivery of images on a storefront, including category pages, product pages, and a shopping cart.

As you may have heard, Cloudinary, the end-to-end media management solution, now has a certified cartridge with Salesforce Commerce Cloud (formerly Demandware), one of the industry's most agile and scalable eCommerce platforms. The Cloudinary cartridge enables you to simplify and automate the process of manipulating, optimizing, and delivering images and videos throughout your entire Commerce Cloud store, including product images and videos, category assets, and site catalogs.

The value of categorizing all the images in your library cannot be underestimated. Besides the obvious advantage of making your image library searchable and displaying relevant content to your users based on their interests, you can also learn more about your users according to the content they upload, and find out what people care about and look for. However, when dealing with a large volume of images, manually categorizing the images would take up too much time and resources.