In April 2018, facial recognition technology was used in part of a landmark arrest of a new father. This case raised a number of ethical concerns over facial recognition and due process. It also signaled the beginning of a new age of face recognition technology — and all the implications that come with it.

Facial recognition is no longer within the purview of dystopian sci-fi satire. But facial recognition isn’t just for solving crimes. It’s becoming a common security measure, for example. It’s even being used to reward recycling by certain vending machines in China.

If you’re looking to implement facial recognition into your apps or development projects, facial recognition APIs make that process exponentially easier. We’ve compiled a list of seven helpful face recognition APIs so you can test out facial recognition within your projects.

1. Inferdo API

Given how prevalent image recognition and computer vision has become, it’s no surprise that there are a lot of facial recognition APIs out there. We’ve decided to start our list of facial recognition APIs with the products with the highest accuracy rate. Inferdo API leads the charge with the highest purported accuracy rate on the market.

Inferdo is used to analyze photos to determine the name, age, and even gender of its subjects. This should already give you ideas of more advanced, creative ways to implement facial recognition into your workflow. You might use Inferdo to create a demographic breakdown of a public event, for example, which you might use in your future marketing materials.

Inferdo is also built for easy use and integration. It also has a generous free tier, letting you analyze up to 5,000 photographs a month at no charge.

2. Lambda Labs API

Lambda Labs’ face recognition API has all the face recognition abilities you could hope for, as well as some bells and whistles to help it stand out from the pack. For starters, it lets you reposition eyes, nose, and mouth for greater clarity. It also enables you to create photo albums and libraries, which new photos can be compared against, making it even more useful. Lambda Labs’ face recognition API also boasts a 99% accuracy rate and has a 1,000-image-per-month free tier.

3. EyeRecognize API

EyeRecognize API also offers basic face recognition functionality with enough advanced features to make it striking. It attributes coordinates for facial features like eyes, nose, and mouth. It can also analyze photos for face-to-image ratio as well as eye and hair color. It can even determine age, race, and gender.

EyeRecognize API talks up its usefulness for content moderation, like analyzing social media content for NSFW. It’s also easy to imagine countless scientific applications for this computer vision API, with its object detection and text analysis abilities.

4. Face++

Face++ does face recognition and then some. This face recognition API also offers body recognition, specifically. Face comparison is another useful feature that makes Face++ notable and worth checking out.

Face++ is built around a machine learning training model with millions of images, making it one of the most accurate face recognition APIs with a 99% accuracy rate. It’s also available as an SDK, in case you’re implementing face recognition for an offline app.

5. Microsoft Computer Vision API

Of course, one of the world’s leading tech companies is going to pull out all the stops for their face recognition solution. The Microsoft Computer Vision API is a facial recognition API and more.

The Microsoft Computer Vision API offers everything from object and brand detection to color schemes and image types. OCR recognition even lets you determine what region an image comes from based on character recognition and text, word, and language analysis. Considering its 96% accuracy rate, there are many reasons to check out the Microsoft Computer Vision API if you’re looking for computer vision.

Consider the Microsoft Computer Vision API if you’re looking for one face recognition API that can do it all. It can supercharge your marketing efforts by making your content more discoverable. It can give you additional insights and benefits from your visual content with spatial analysis to provide further context.

6. Betaface

The Betaface API offers a face recognition service that provides various functionalities related to facial analysis and identification. Betaface identifies and locates faces within images, compares and matches faces against a database to identify or verify individuals and extracts facial attributes such as age, gender, and emotional state. It can also perform search for similar faces within a database and can be integrated into both web and mobile applications to provide advanced facial recognition capabilities.

7. Kairos API

Sometimes you need facial recognition for something other than static images. Kairos is well-known and widely used for its ability to implement face recognition in video and even real-time streaming.

Kairos has a few features to recommend it as a face recognition API for photos, too, though. Multi-face detection for crowd settings is one feature that differentiates it from the other face recognition APIs. The ability to detect potential fraud and counterfeits using anti-spoof detection is another, which allows Kairos to discern the liveness of a face in an image. Finally, Kairos handles diversity better than most other face recognition APIs on the market, which often struggle with accuracy when detecting darker skin. This alone makes Kairos worth checking out to ensure your visual media is being used to its fullest potential.

Final Thoughts on Face Recognition APIs

Facial recognition technology is inevitable. If there’s one thing that’s certain in the worlds of business and technology, it’s that business owners and shareholders will find a way to extract the most value from their assets with as little investment of time and money as possible. Considering the prevalence of micro-tasks like Amazon MTurk, it’s inevitable that business owners will cut out the intermediary and let APIs do the work.

As we have seen, there are also plenty of potential applications for face recognition and computer vision in the social sciences and the humanities. Moving forward, face recognition APIs will be used for much more than simply solving crimes.