How To Maximize Accuracy Using An API For Face Analysis


If you want to know how to maximize accuracy using an API for face analysis, you are in the right place. Keep reading!
Face recognition is a topic of interest in many fields, including security, entertainment, and biometrics. It is a form of artificial intelligence (AI) that identifies and verifies a face using maths and algorithms. Face recognition is a subset of facial analysis, which also includes identification, verification, and analysis.
In other words, the algorithm examines the pixels of an image and compares them to those in its database to find a match. The algorithm then returns a match score that indicates the probability that the two faces belong to the same person. Thus, it unlocks a device, grants access or gives admission to the individual.

Broadly speaking, facial recognition technology is today 99 percent accurate thanks to the constant evolution of digital tools, AI and Deep Learning. Developers are constantly at work. But our industry as a whole has more work to do to secure that extra percentage point. That’s because there are a few demographic blindspots.

Nevertheless, according to data from the most recent evaluation, each of the top 150 algorithms are over 99% accurate across Black male, white male, Black female and white female demographics. For the top 20 algorithms, accuracy of the highest performing demographic versus the lowest varies only between 99.7% and 99.8%. This is an achievement to celebrate, but not yet a goal. Development of APIs is dynamic and it`s always evolving.

Face Recognition Applications

To augment accuracy using an API for face analysis, we suggest using Face Analyzer API. This tool works with artificial intelligence and it’s very accurate. Moreover, it’s very simple to use. It´s integrated with other APIs by the same vendor: Face Analysis API, Age Detection API, Gender Detection API, Facial Expression API, Face Identity API, and others. This suite of tools optimize efficiency.

To use this API, follow these steps: first access You can get an API key by entering your name, email address and a desired password. Upload the two images you want to compare (jpeg files), and the result will show on the screen at once. And that`s all there is to it! 

Additionally, this API provides a complete report on all the similarities it found out between the two faces: angle distance, eye distance, facial features alignment, and more, in a pixel-by-pixel comparison. 


Scientists have shown that focusing on someone’s ears and facial marks improves accuracy by 6 percent. This is a significant increase because even experienced face identification staff can get as many as one in two wrong when it comes to comparing photos with unfamiliar faces. Precision in analysis has further evolved in times of COVID-19 pandemic, when face analysis tools were optimized to analyze faces with masks on.

To make use of it, you must:

  1. Go to Face Analysis API and simply click on the button “Subscribe” to start using the API.
  2. After signing up in Zyla API Hub, you’ll be given your personal API key. Using this one-of-a-kind combination of numbers and letters, you’ll be able to use, connect, and manage APIs!
  3. Use the different API endpoints depending on what you are looking for.
  4. Once you find your needed endpoint, make the API call by pressing the button “run” and see the results on your screen.




Alejandro Brega

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