What is the best way to build an image recognition app?

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Let’s see how to develop a face recognition application in the best possible way and what instruments have to be applied for such purposes. Actually, there’s a wide selection of the tools, but I’d like to mention the follow key approaches.

# Native APIs

That would be one of the most popular and the simplest solutions. Applying Native APIs from both - Google & Apple - will make the development process rather smooth.

Moneywise, the option is great as well. It’s relatively cheap, and you won’t have much hassle to get it installed. Moreover, you don’t have to worry about additional costs or further efforts.

However, don’t expect it to have too many functionalities. Though, it might be pretty enough for you to get what you want.

# 3rd party services

Here’s another option I’d recommend you to consider. You might even be surprised with all the solutions they’ll provide you with to attain the desired. There exist multiple businesses offering the APIs for those who’d like to make a face detection mobile application.

Here are only few bright representatives:

• Visual Recognition API is provided by Amazon. The company makes their numerous clients happy with various development solutions, say, shopping services, cloud options, etc. Mentioned API is presented with two packages - a free and paid one.
• Luxand.cloud API is what you need when planning to create a service to define emotional conditions, age, gender of a person and the like. You would have three options to select from: a basic package, a pro option and an ultra package.
• FaceMark represents a handy and convenient API. The option offers multiple solutions for full face recreation. Its owners claim the API is simple to be applied. Few price packages are available.

Here - when applying 3rd party solutions - is rather difficult to clearly define specific costs you’ll bear while developing a face recognition service, since everything shall depend on the solution you’ll decide to go for.

# Open Source Computer Vision Library

One more tool I’d like to mention is OpenCV.

It’s a library having over 2.500 thoroughly adjusted and optimized algorithms. There are various options to choose from, providing both traditional and modern algorithms. Those algorithms are mainly aimed at computer visions, as well as machine learning, which could be applied for image identification, and, of course, for human face identification.

In addition, the library can help tracking moving objects, extracting 3D models of various items, and the rest.

Working on the code is truly simple and convenient, and it was provided thanks to the fact that this library represents a licensed BSD product.