Face Regconition

This is the project face recognition using MTCNN to handle scan function, ultralight to detect face and ArcFace to recognition.

Supported by the F-Code club.

Introduction

In this face recognition problem, I use a Learning Similarity method so that I don't have to retrain the model when add a new face.

How to setup!

$ git clone https://github.com/ttthanhf/face-recognition.git

$ pip3 install -r requirements.txt"

• Download weights : Click here to download weights (Put arcface_h5 folder and ultralight_onnx folder in weights folder)
  
  
  

To start server:

$ py main.py server start

(It will start localhost with port 5000)

If your computer has 16gb ram or more you can use docker to run this model !

API

using json in body web request.

• api_v1 : using upload image.
• api_v2 : using path of image in local. (Body: Json: {path: "your url", name: "your name"})
• api_v3 : using url of image. (Body: Json: {url: "your url", name: "your name"})

---

• / (method: POST) : recognition face

Input: (look)

=> Output { status , 
            name , 
            execute_time 
          }

• /create (method: POST) : insert new image

=> Output { status , 
            execute_time
          }

• /add (method: POST) : add more image

=> Output { status , 
            execute_time 
          }

• /delete (method POST) : delete data user

Input: json ({name: "your name"})

> => Output { status , 
              execute_time 
            }

• /scan (method: GET) : generate data face

> => Output { add , 
              exist , 
              total , 
              execute_time 
            }

• /list (method: GET) : show all user

> => Output { 
               *json list* 
            }

• /rename (method POST) : rename user in database

Input: Json ({oldname: "your oldname", newname: "your newname"})

> => Output { status , 
              execute_time 
            }

Example

To easily interact with users as well as being able to add one project to another, I use RESTful API to interact with Model.

I use POSTMAN for this example with api_v3

POSTMAN

Step 1: create a new face to start recognition. Here I use the image of Harry Potter character.

(link: https://gocsaoviet.com/wp-content/uploads/2021/06/photo-1-1622984031118226200693.jpg)

url: http://localhost:5000/api_v3/create (method POST)

Step 2 : Use "scan" to generate the face data into database.

url: http://localhost:5000/api_v3/scan (method GET)

Step 3 : Result.

(link: https://vtv1.mediacdn.vn/thumb_w/650/2019/9/3/17988102-7420621-the8bookpotterseriesandotherrelatedstoriesaudiorecordi-a-61567460030727-15674958768921527956477.jpg)

*Example in folder webapp (it using fetch or axios)

Note

! You need to scan face before create new face !

! => To avoid unexpected errors, use the python version 3.7.9 <= !

Ff you are in python 3.7.9 and still not working, delete that python version and reinstall it. Python 3.7.9

Reference :

• https://github.com/ipazc/mtcnn
• https://github.com/serengil/deepface
• https://github.com/deepinsight/insightface
• https://github.com/davidsandberg/facenet/
• https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB
• https://viblo.asia/p/paper-explained-some-face-recognition-approaches-facenet-arcface-cosface-Do754zgLZM6

Contact

if you have any problem, you can contact to me ! :)

License

This project is licensed under the MIT License - see MIT LICENSE for more details.