What Face Recognition Software in Pakistan Should You Use in 2021?

Paypeople #1 Face recognition software in Pakistan I’ve tried my hardest to compile a complete list of all current facial recognition technologies available. Surprisingly, the active development of half of the prospective free solutions only began in 2020! I found it difficult to thoroughly research paid solutions for businesses because they don’t provide much information for ordinary people, thus I expect this post to be most useful for small businesses. 

Paypeople #1 Face recognition software in Pakistan
What Face Recognition Software in Pakistan Should You Use in 2021?
What Face Recognition Software in Pakistan Should You Use in 2021?


Types of Facial Recognition Solutions Available on the Market

The first thing you should know is that facial recognition software comes in a wide range of options. Some of them are ready to use without the need for machine learning knowledge, while others will take a lot more time and effort.

I would classify facial recognition services into three categories, each with its own set of benefits and drawbacks. Take a look at the following:

Facial recognition engines based on Software as a Service (SaaS)

 In this example, face recognition software in Pakistan providers are responsible for everything from machine learning to administering and servicing high-load servers. All you have to do is use an API to connect the software to your IT systems. Although there are numerous benefits, these solutions also have a number of drawbacks. To begin with, this is the most expensive option because the provider handles everything. You’ll also need a reliable Internet connection because you’ll be sending large photographs to a server on the Internet. There may also be security concerns because you must transfer your images to a third-party company over which you have no control.

REST API solutions that are self-hosted

Such solutions can be used on-premises as well as in the cloud. They are not plagued by the same issues as SaaS products. You can regulate where your data flows by storing it on your own servers (or in your private cloud), and you can even construct a system that functions offline. You will, however, be responsible for managing the servers on your own.

Servers, on the other hand, are typically deployed as Docker containers, making orchestration a breeze. While not as expensive as SaaS alternatives, self-hosted solutions are nonetheless quite costly. Fortunately, self-hosted REST API alternatives that are free and open-source are starting to appear. They are not as well-developed as other options, but they show great promise.

Frameworks and libraries that are free to use

Many researchers are ready to share the code from their cutting-edge approaches, therefore these are usually free. To utilize this software, you will, of course, require at least some machine learning knowledge. If you wish to combine these solutions with your bespoke apps, you’ll also need to spend some time RESTifying them.

Best Free Facial Recognition Software Solutions to Use in 2021

With 37.6k ratings on GitHub, this is perhaps the most popular free face attendance in Pakistan. You can use it in one of two ways: using its Python API or through their binary command line program. Installation instructions are provided for all major platforms, as well as a Docker image for quick setup. While there are valid reasons for its appeal, there are some severe drawbacks to be aware of.

For instance, the most recent release was in 2018 (three years in the AI business is a long time), and while there are currently commits in the repository, it appears that no significant improvements have been made. Second, it employs an out-of-date facial recognition algorithm that is only 99.38% accurate on LFW (we can do better in 2021). Lastly, because this solution lacks a REST API, it is more essential to combine.


This framework was released on GitHub in February 2020 and has already received over 1,100 stars, owing to its similarity to Facebook’s Deep Face face recognition approach. Face Net and Insight Face are two facial recognition algorithms supported by this library

It also has a REST API, however it just allows verification methods, so you can’t create face collections and search through them for your face. Even if it’s simple to get started if you’re a Python coder, it’s a bit more difficult for everyone else. The most recent version is 0.0.49, which was released in January of 2021.

Face  Net:

Face Net is a Google-developed face recognition software in Pakistan and the open-source Python library that implements it. The repository has 11,000 stars, and it is used as a base library in many “how to” articles. Despite the fact that this method is relatively old, it is still used by some fresh researchers (most recently for face recognition in masks).

This approach has a high level of accuracy (99.65% on the LFW dataset, which isn’t terrible, but not exceptional). The lack of a REST API and the fact that the repository is no longer supported are also downsides of this approach

Insight Face:

With 8,000 ratings, Insight Face is another open-source Python module. It employs Retina Face, one of the most modern and precise technologies for face detection and recognition. This source is quite active as of the starting of 2021. On the LFW dataset, this solution is also extremely accurate at 99.86 percent. The main drawback is that it is difficult to use.

Last Thoughts

As we approach 2021, the facial recognition market is continually evolving. Face recognition algorithms are improving all the time, thus it’s pointless to use services that are no longer supported. Because of new open-source options, using facial recognition software is becoming more economical. There are numerous applications for this powerful platform, including although comparing them can be difficult, there’s sure to be an option that works right for you.

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