Classroom visual sign in program
Project description
Face In
Sign in system with face recognition Based on code from https://github.com/serengil/deepface
Urs Utzinger, 2022
Requisits
pip3 install deepface
pip3 install camera-util
Create folder database and place images of known faces into them. Supports .jpg files.
Supports multiple images for same person, in database/First_Last/First_Last001.jpg
Configuration
detector_backend = "retinaface" # opencv*, ssd, mtcnn, dlib, retinaface
freeze_time = 5 # how will the results be displayed
frame_threshold = 5 # how many frames required to focus on a face, 5*
minimum_face_width = 180 # filter out small faces, depends on camera
model_name = "ArcFace" # VGG-Face*, Facenet, OpenFace, DeepFace, DeepID, Dlib, ArcFace or Ensemble
distance_metric = "cosine" # cosine*, euclidean, euclidean_l2
datafile = "./database/bme210_2022Spring.dat"
db_path = "./database" # Folder for .jpg files of known faces
Performance
| Detector | Example exection time in ms | Works w glasses | Works w obstruction | Works w facemask |
|---|---|---|---|---|
| Retinaface | 172-233 | yes | yes | yes |
| OpenCV | 40-56 | no | no | no |
| SSD | 19-30 | yes | yes | no |
| MTCNN | 873-1029 | yes | yes | no |
| DLIB | 346-352 | yes | no | no |
| Model | Example exection time in ms | Works w glasses | Works w obstruction | Works w facemask |
|---|---|---|---|---|
| ArcFace | ||||
| VGG-Face | ||||
| FaceNet | ||||
| OpenFace | ||||
| DeepID |
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