Face Recognition with FaceNet (InceptionResnetV1) in Pytorch

Introduction

This is a mini-project of implementing Face Recognition using FaceNet in Pytorch on my internship at Widya Robotics

Tutorial

Clone the project

git clone https://github.com/zogojogo/face-recognition-wii.git

Go to the project directory

cd face-recognition-wii

Download Dependencies

pip install -r requirements.txt

Download the Face Recognition model in this link and then put on the ./models/ folder

https://github.com/timesler/facenet-pytorch/releases/download/v2.2.9/20180402-114759-vggface2.pt

Start API service

app.py --path <enrollment_path>

I made this program customizable so you can put your own enrollment path with face images inside to perform face recognition. The structure of the path is should be like this.

├── id1
│   ├── 1.jpg
│   ├── 2.jpg
│   └── ...
├── id2
│   ├── 1.jpg
│   ├── 2.jpg
│   └── ...
├── id3
│   ├── 1.jpg
│   ├── 2.jpg
│   └── ...
└── ...
    ├── 1.jpg
    ├── 2.jpg
    └── ...

API Reference

Service: http://your-ip-address:8080

POST image

  POST /predict_identification

Content-Type: multipart/form-data

Name	Type	Description
image	file	Required. image/jpeg or image/png MIME Type

  POST /predict_verification

Content-Type: multipart/form-data

Name	Type	Description
image	file	Required. image/jpeg or image/png MIME Type
image_2	file	Required. image/jpeg or image/png MIME Type

Result Example (Identification)

Input:

Output:

{
  "filename": "0001_0.jpg",
  "contentype": "image/jpeg",
  "predicted id": "25",
  "confidence": "0.8785694285637182",
  "inference time": "0.05906987190246582"
}

---

Result Example (Verification)

Input:

Output:

{
  "prediction": "Same Person!",
  "confidence": "0.8526605431392245",
  "inference time": "0.06154894828796387"
}