In this chapter, we built a Pictorial Translator application to translate texts appearing in pictures. We leveraged Amazon Rekognition to first detect lines of text in pictures and then leveraged Amazon Translate to translate the detected texts. This is our first intelligence-enabled solution that solves a real-world problem. Building these solutions through hands-on projects helps to build your intuition for solving problems with AI capabilities. Along the way, we also discussed solution design decisions and trade-offs that must be validated against the real-world usages of our application. From an architectural perspective, not only did we build a working application, we architected it in a way that allows for reusable components that we can leverage in future hands-on projects.
In the next chapter, we will build more intelligence-enabled applications using additional...
