Entrance Monitor
Monitors labolatory entrance & notifies it.
Environment
- Python 3
- dlib
- face_recognition
- Cloud Firestore
- DialogFlow
Usage
$ docker-compose up -d
To check log
$ docker-compose logs
or
$ docker-compose logs | tail
or
$ docker-compose logs -f
Files
.
├── README.md
├── build_base_image # to build face_recognition image with cuda driver
│ └── Dockerfile
├── data_store.py # stores detected info to Cloud Firestore
├── docker-compose.yml # service info
├── faces
│ ├── personA # contains person image as .jpg .png
│ ├── personB
│ ├── ...
│ └── personN
├── face_recognizer_knn.py # face recognizer
├── facerec_from_video.py # recognize face with video
├── for_streaming # streaming recognized webcam
│ ├── face_recognizer.py
│ ├── ip_camera.py
│ ├── streaming.py
│ └── templates
│ └── index.html
├── knn_train.py # trains knn model with faces folder
├── line_notifier.py # line notifier
├── monitoring.py # main
├── people.py # out of git, cilab people info
├── secret.env # out of git, camera url & firestore , slack, line token
└── slack_notifier.py # slack notofier
How to add person
- Writes person name in people.py.
- Adds user to Cloud Firestore.
- train knn model
$ docker-compose restart
env file
secret.env
- LINE_ACCESS_TOKEN
- LINE_USER_ID
- SLACK_WEBHOOK_URL
- CAM_URL
- FIRESTORE_PROJECT_ID
- FIRESTORE_KEY_ID
- FIRESTORE_KEY
- FIRESTORE_CLIENT_EMAIL
- FIRESTORE_CLIENT_ID
- FIRESTORE_CERT_URL
proxy.env
http_proxy https_proxy