How Hot and Cool are You?

Artificial Intelligence will decide how hot and cool you are
on a scale of 1 to 10.


She’s Very Hot, lets see how hot you are! Mobile App - Artificial Intelligence - Mobile App to ​automatically rates ​all of your ​current selfies on a scale of 1-10. If you aren't satisfied with the shots in your camera roll,​ then use the camera button in the app to create your masterpiece photo.

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About Technology

Face Recognition API & Technology uses the Face Recognition API developed by , which relies on facial recognition algorithms and deep learning to calculate a person's facial attractiveness score between 1 and 10.

How does this Facial Attractiveness Test Work?

We trained Machine Learning algorithm, to detect the attractiveness of each user. The algorithm was trained by thousand of users using our App, which you can download from the Play Store .

Shold I take results seriously?

While these scores are determined by advanced algorithms that include identifying and comparing a person's facial features against a database of other people's facial features and real people's view of how attractive a person is, it is important for a person to take the Facial Attractiveness Test in a fun and lighthearted manner. These results are meant to be used only for entertainment purposes only.


The Idea under Attractiveness AI

Often people wonder, " how attractive am I ?" or “ am I hot ?”
We have all asked ourselves these questions, however until, a person had limited options in determining how attractive they were. Typically, the only options available were simple facial attractiveness tests that used either no facial recognition software or appeared to respond with random scores. While these facial attractiveness tests were largely for entertainment purposes, the overall experience left people wanting something more accurate. offers anybody the ability to have their photo scanned by facial recognition software and compared against a database of other photos.You just have to choose the photo of yourself that you wish to upload to the Facial Attractiveness Test, which will then scan the photo to determine the person’s facial features based on a number of different facial points. A facial attractiveness score between 1 and 10 is then displayed under the person’s photo.

Facial Features Recognition

The facial recognition api developed by determines the person's facial features by mapping their face. The shape and size of the eyes, nose, cheekbones, mouth and jaw are some of the important features used in determining a person's unique facial structure. The facial recognition software also determines a person's age based on a variety of features.

There are important factors in regards to facial attractiveness that determine how a facial attractiveness score is calculated once a person’s facial points have been determined. For a person’s eyes, the distance between the eyes and the depth of the eye sockets are important factors. Important factors for a person’s nose, the width of the nose and the length of the nose. Other important factors include the size of a person’s lips, the length, and width of their chin and jaw and the position of their cheeks.

Deep Learning

Deep learning offers a variety of benefits to artificial intelligence algorithms. Essentially, it is the process of continually feeding new information into an artificial intelligence system and increasing the amount of information in the databases used for many purposes, including mapping the history of and guiding the predictions of an artificial intelligence system. For facial recognition systems, this new information is used to evolve the artificial intelligence algorithms that help determine accurate facial points. In the case of the Facial Attractiveness Test, this new information also helps determine a more accurate facial attractiveness score.

New data is constantly fed into deep learning, which uses existing and new data to identify facial features better and more accurately determine a facial attractiveness score, is an important part in the development of better accuracy and scoring.

Deep learning is used to continually increase the accuracy of the facial recognition process by comparing new photos of a person’s face with a continually growing database of photos previously evaluated for facial attractiveness. Deep learning also is used to improve the Facial Attractiveness Test scores by comparing previous facial features and their facial attractiveness scores with new photos to form a scoring curve of more and more accurate facial attractiveness scores.

Mobile App

The mobile app offers a person the ability to upload their photos from their mobile phones and tablets to have their facial attractiveness calculated and scored. The mobile app also provides users the ability to anonymously rate other users' facial attractiveness, using the same scoring system of 1 to 10. These user scores are then fed into deep learning to help the facial recognition api determine the attractiveness curve based on current trends in the way real people view the facial attractiveness of others.

These facial features and facial attractiveness scores are calculated together and compared against a database of other facial features and facial attractiveness scores to determine a current facial attractiveness score. The result is a more accurate facial attractiveness score between 1 and 10, with 1 being low facial attractiveness and 10 being high facial attractiveness, based on the previous and current facial features and facial attractiveness scores.