Our Experience With Rekognition
Recently, a client asked us to explore the development of a facial recognition engine on a very short timeline. Rekognition seemed like a good fit: it promised scalability, functionality, and speed — which meant we could save countless data science and software engineering hours.
As we began investigating, we found that off-the-shelf Rekognition had some limitations. But using simple statistics, we were able to manipulate the platform and improve the performance. In only three days, we delivered a highly effective solution for the client.
Rekognition isn’t the only image analysis API around. Google, Microsoft, IBM — to name a few — also have developed platforms with similar or overlapping features. Of course, each API has its own strengths (and weaknesses, too). Each can be used to fast-track machine learning, or at least get it off the ground, so we think they’re valuable tools — especially in cases where time and resources are limited.