In Flutter’s early days in 2019, I developed a live object detection system for a major German company, despite the platform’s constraints. With release of Flutter 3.7 and advancements of TensorFlow have catalyzed the need to refine or overhaul this approach. This article discusses the newest techniques in live-stream object detection as showcased in the flutter-tflite GitHub repository.
What device should be used to run the tests? What operating system version, manufacturer and model to use? How to get these devices? These are some of the questions we ask ourselves when planning a mobile application testing strategy. If we consider automating these tests, other questions will surely come to mind.
Mobile developers using Javascript-based mobile application development platforms such as Cordova, Ionic and React Native have enjoyed the benefit of being able to push app updates over-the-air without resubmitting their apps to the App Store or Google Play for quite some time. As long as the updates are not compiled code, and don’t change the primary purpose of the application then both Apple and Google allow this.
Bitrise has introduced a new feature that allows you to connect to your code repositories using a private link, simplifying the way you build apps. With this update, you have more control and security, and the process is quicker and less complicated, making managing workflows easier.
Mobile devices permeate almost every facet of our lives. With the number of mobile users currently at 5.1 billion and growing, mobile commerce growth will not stop anytime soon. To capitalize on this market, it’s critical to deIiver a high-quality user experience through robust mobile testing. Unfortunately, most companies have been slow to adopt mobile testing. Part of the complexity lies in setting up and configuring various iOS and Android devices.
