Realtime and offline Face Recognition app using Google ML Kit, FaceNet | ML Android app

Face recognition is a powerful tool that uses biometric data to identify or verify a person's identity. It works by analyzing unique facial features such as the distance between the eyes, nose, and mouth.

Here, we implement face recognition using Google MLKit and TensorFlow Lite model of FaceNet.

There are two main types of face recognition: 1:1 and 1:N. 1:1 face recognition compares a single face to a single stored reference, often used for unlocking devices or secure access. 1:N face recognition compares a single face to a database of many faces, used for identity verification and tagging people in photos.

The technology behind face recognition has come a long way in recent years and is now more accurate and reliable than ever before. It can be used in a variety of settings, such as security systems, mobile apps, and social media platforms.

Face detection and face recognition are both related to processing and analyzing faces in images or videos, but they are different in their purpose and functionality.

Face detection is the process of identifying and locating faces in an image or video. It is used to detect whether or not there is a face present in a given image and, if so, where it is located. It typically returns bounding boxes around any detected faces.

Face recognition, on the other hand, is the process of identifying a specific person based on their facial features. It compares a given face to a database of known faces and returns a match, along with a confidence score indicating how likely it is that the match is correct. It is used for identifying a person or verifying a person's identity.

In summary, face detection finds faces in an image, while face recognition identifies who those faces belong to.

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[mbvhd]

Thank you for this video. it works great, but in some phones, visitor analysis will not detect faces and will not show any result.

[aristoncatipay]

Awesome Project Sir! I am also developing a mobile application that will need this type of functionality. However, I am using Flutter. Can I replicate this functionality using flutter?

[dakshjain]

Sir, very good tutorial. I have a dought, if i restart the app after training the model it will not detect my face. Can you give me the steps to fix it

(Edit): just added not after it will

[katsprolabsug]

i imported the project into android studio and the app was generated successfully, I tested all features but find all features are working except face recognition, what could be the problem

[mariannicolae]

I have a question based on the facial recognition project, the recognition for me is not done in real time, but at a certain time, for example now it recognizes, then after about 2 seconds, then after about 5, etc.. How to solve it so that it recognizes in real time and immediately detect faces

[durgamurugan]

hello sir, great video using the code i able to do face register & recognition, instead of the registered face here im getting the face images frm db through api which is done in webapp[face registration], while using those images the recognition is not correct, so tell me can we able to predict the face only register here, not from others, if we can, what steps i need to do after got the face image list, plz help me out sir, thank u!

[RichardMedia]

How can I save permanently the captured images and use it face recognition? not in temporary even I close the apps it is no need to registered the face again?

[kavinraj]

hi how can i link it to firebase and retrieve the facial values from there for recogntion

[nisarhussainlaghari]

Does it work offfline in android? As if employee pictures are saved once then?
I want to take attendance of my 30 employee in a working room and store their today attendance to firebase realtime database.

[rahil]

It is using back camera, what if I want to use front camera.

[jepoy]

will this work if i run this on physical device

[amivadera]

How to reuse this code with flutter?? please help me