Face Recognition

One shot learning using FaceNet and MTCNN.

Quick start

Step 1: Clone repository or download zip

!git clone https://github.com/SarahHannes/face-recognition.git

Step 2: Add training images to `/database` folder

Step 3: Create a new environment using `requirements.txt` or `face_recog38.yml`

Step 4: Activate the created environment on anaconda prompt

conda activate <environment name>

Step 5: Change directory to cloned folder on anaconda prompt

cd <path to cloned folder>

Step 6: Predict! 😌

To view arguments:
python main.py --help
To set path for training folder (required):
python main.py --database <path to folder containing training images>
To perform face verification through webcam:
python main.py --database <path to folder containing training images> --webcam
To perform face verification on media inputs (.JPG, .MP4):
python main.py --database <path to folder containing training images> --media <path to folder containing media inputs>
To specify threshold:
python main.py --database <path to folder containing training images> -t <value>

References & credits

Thank you!
[1] GitHub repo by foo290
[2] GitHub repo by R4j4n
[3] Shared google drive containing FaceNet weights by Hiroki Taniai
[4] Tutorial on face recognition
[5] Tutorial on argparse