One shot learning using FaceNet and MTCNN.
Step 1: Clone repository or download zip
!git clone https://github.com/SarahHannes/face-recognition.git
Step 3: Create a new environment using requirements.txt
or face_recog38.yml
conda activate <environment name>
cd <path to cloned folder>
- 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>
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