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https://github.com/fvlima/raspycammonitor
A simple and experimental python script to run on raspberry, that uses picamera and opencv-python to detect human presence by face recognition, taking a photo and sending it through email
https://github.com/fvlima/raspycammonitor
Last synced: 3 months ago
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A simple and experimental python script to run on raspberry, that uses picamera and opencv-python to detect human presence by face recognition, taking a photo and sending it through email
- Host: GitHub
- URL: https://github.com/fvlima/raspycammonitor
- Owner: fvlima
- License: gpl-3.0
- Created: 2018-03-08T00:57:27.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-01-24T02:02:30.000Z (9 months ago)
- Last Synced: 2024-04-04T04:32:21.906Z (7 months ago)
- Language: Python
- Homepage:
- Size: 39.1 KB
- Stars: 6
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- starred-awesome - raspycammonitor - A simple and experimental python script to run on raspberry, that uses picamera and opencv-python to detect human presence by face recognition, taking a photo and sending it through email (Python)
README
# raspycammonitor
A simple and experimental python script to run on raspberry, that uses picamera and opencv-python to detect human presence by face recognition, taking a photo and sending it through email.
It uses the haar-cascade [1] classifier for face detection and some configurations to improve the classifier type and detection scale can be made by envvars configured in .env file.
1 - http://bit.ly/2FjyYB5
## Installation and usage
This project requires `pipenv`.
1. Clone the project `git clone https://github.com/fvlima/raspycammonitor.git`
2. `pipenv install` (if any error occurs, try `pipenv install --skip-lock`)
3. `cp default.env .env`
4. Edit the `.env` file with your email credentials and other configuration if necessary
5. Run `python monitor.py`
## Using as a background service
It's possible to configure it as a service, to run in background and automatic launch on system boot, example:
Create the service file
```
vim /lib/systemd/system/raspycammonitor.service
```
Edit this file like the lines bellow (change the venv and project location)
```
[Unit]
Description=Raspberry Py Camera Monitor
After=multi-user.target
[Service]
Type=simple
ExecStart=/your/venv/path/bin/python /your/local/path/raspycammonitor/monitor.py
Restart=on-failure
[Install]
WantedBy=multi-user.target
```
And run the follow comands in terminal (change the project location)
```
sudo chmod 644 /lib/systemd/system/raspycammonitor.service
chmod +x /your/local/path/monitor.py
sudo systemctl daemon-reload
sudo systemctl enable raspycammonitor.service
sudo systemctl start raspycammonitor.service
```
After it, the project is already ready to run. It's possible to see the service status with the follow command
```
sudo systemctl status raspycammonitor.service
```
More information about systemd can be found here https://wiki.debian.org/systemd
## Configuration file
Here the envvars configuration options are described
```
SMTP_SERVER=smtp.some-domain.com # the smtp server
SMTP_PORT=587 # the smtp port
[email protected] # the user for smtp login
SMTP_PASS='password' # the user smtp password between single quotes
SMT_USE_TLS=True # if the smpt uses TLS or not
[email protected] # the email that will send the captured image
[email protected] # the email that will receive the captured image
EMAIL_SUBJECT=Face detection # the email subject
CV2_CLASSIFIER=/usr/share/opencv/haarcascades/haarcascade_frontalface_alt.xml # the classifier location
CV2_SCALE_FACTOR=1.1 # cv2 scale factor image detection
CV2_MIN_NEIGHBORS=5 # cv2 min neighbors image detection
CAMERA_RESOLUTION=1024,768 # the picamera resolution
CAMERA_CAPTURE_INTERVAL=2 # the interval in seconds between image capture
```
## Notes
- This project was tested with python 2.7+ and 3.5+
- Maybe you need to install libopencv-dev