Do you want to get human emotions in images in Python? If the answer is yes, you are in luck! Just use one of these APIs!
Nowadays, the field of artificial intelligence (AI) has advanced to such an extent; that it is now possible to recognize human emotions at the click of a button. This capability is of great help in improving our interpersonal relationships in our work environment; and even in our daily lives.
Therefore, computer programs that recognize human emotions are more in demand by different industries; and developers can take advantage of this opportunity to produce their own emotion detection APIs in any programming language they want, like Python.
Why Should You Use A Human Emotion Detection API That Works With Python?
You may have heard about Python. This programming language is frequently used by enterprises to develop software that can be hosted on their own servers. Developers are increasingly using this high-level programming language since it is easier to learn, quicker to produce, and easier to maintain code than other languages like C++.
So, in terms of an emotion detection API; this tool enables your software to instantly identify any visible human emotions in an image by just loading the image’s URL. Moreover, as it typically comes in portable JSON format, which can be easily parsed into Python for ease of use; it can also be simply integrated into any website or application.
Additionally, because it makes use of artificial intelligence, it has perfect accuracy and can quickly retrieve emotion data! All you need to use this kind of technology is: a computer, an internet connection, and a reliable API provider. So, to help you with the last one, we have gathered information on the best APIs in Python available today! Take a look:
Emotion Detection API
Emotion Detection API is a high-quality API available at Zyla API Hub. It uses artificial intelligence and advanced technologies to swiftly and accurately identify emotions in an image. Since it comes from a reliable API provider, it guarantees quality, safety, and quick results!
This program analyzes an image to immediately recognize faces, detects micro-expressions, and classifies them into seven basic emotions thanks to a big database of emotions and precise information. The findings are then returned in JSON format within seconds, making it simple to parse them into Python.
Face Reader API By Noldus
Noldus Face Reader API is based on artificial learning and employs a database of data made up of 10.000 photos of facial expressions. It is primarily utilized in the academic community. Using 500 essential facial points, the API examines six basic expressions, neutral expressions, and depressed expressions.
In order to accurately identify emotions, Noldus Face Reader API also identifies the direction of the eyes and the angle of the head. This API’s response is delivered in portable JSON format and can also be easily parsed in Python.
EmoVu API By Eyeris
This API swiftly ascertains a person’s emotional state from an image using autonomous learning and identification of microexpressions. EmoVu API makes it possible for any company to accurately predict the emotional impact and depth of its content or product on its target market.
EmoVu’s broad platform compatibility offers a variety of tracking features as well, including head position, inclination, eye tracking, open/closed eyes, and more; which is ideal for any developer looking to enhance their own apps. Additionally, EmoVu provides a sample no-cost at all, in addition to many paid plans for business use!
Related post: 3 Emotion Analysis APIs For The Automotive Industry
Also published on Medium.