Globally, approximately two billion people now own smartphones, which also feature cameras capable of capturing photos and videos of a tonal richness and quality unimaginable even five years ago. Until recently, those cameras behaved mostly as optical sensors, catching light that determines the resulting image's pixels. The next generation of cameras, however, can blend hardware and computer-vision algorithms that apply to an image's semantic content, spawning creative mobile photo and video apps.
In this part, I'll show you how to implement our new responsive images solution, which enables you to optimize the image you deliver based on the requesting device's resolution and the available dimensions. This new feature can help you to simplify the many complexities of creating multiple variants of every media assets, with on-the-fly manipulation and fast delivery through the CDN.
In the previous post, we showed how to upload images to a Cloudinary server. In this part, we will play with some of the features we see on the WhatsApp technology. After you or your users have uploaded image assets to Cloudinary, you can deliver them via dynamic URLs. You can include instructions in your dynamic URLs that tell Cloudinary to manipulate your assets using a set of transformation parameters. All image manipulations and image optimizations are performed automatically in the cloud and your transformed assets are automatically optimized before they are routed through a fast CDN to the end user for an optimal user experience. For example, you can resize and crop, add overlays, blur or pixelate faces, apply a variety of special effects and filters, and apply settings to optimize your images and to deliver them responsively.
With more than one billion people using WhatsApp, the platform is becoming a go-to for reliable and secure instant messaging. Having so many users means that data transfer processes must be optimized and scalable across all platforms. WhatsApp is touted for its ability to achieve significant media quality preservation when traversing the network from sender to receiver, and this is no easy feat to achieve.
In this talk, the audience learns everything they will ever need to know about playback controls, offline media, image & video optimization and transformation, pre-loading, deep learning with Images, audio & improving web performance by using the right tools while dealing with media assets in their react apps.
In Android, working with images (bitmaps) is really difficult because the application runs out of memory (OOM) very frequently. OOM is the biggest nightmare for Android developers.
There are some well known open source libraries that can help us deal with such problems like Picasa, Glide, and Fresco.
Developing applications for mobile consumption requires facing, and overcoming, some difficult challenges. Apps need to limit their RAM, CPU and battery usage while still performing the required tasks in a reasonable time frame. If too many background tasks are running, the mobile device can become sluggish, with the battery running out very quickly. Coordination with other apps is crucial to keep the device responsive and make the battery last longer.
Managing media files (processing, storage and manipulation) is one of the biggest challenges we encounter as practical developers. These challenges include:
A great service called Cloudinary can help us overcome many of these challenges. Together with Cloudinary, let's work on solutions to these challenges and hopefully have a simpler mental model towards media management.
Embedding and managing images and other media content in a mobile application is always challenging. The processes of downloading a media file from the web, storing it on the device, and then displaying it to the user are surprisingly and often frustratingly complex from a coding perspective. In addition, you probably want to add code that enables reusing images rather than downloading it every time, but you have to be smart about it to avoid clogging the precious storage space on your customer's device. Furthermore, your design probably requires that images be displayed in different sizes and DPRs in different devices, but creating and maintaining multiple versions of every image manually is virtually impossible.