This is a project of the face recognizer with Movidius on RaspberryPi 3B+ platform. The project also uses Django and Django REST framework which providing the web platform. The project would like to build a safety and intelligent face recognition system in AI era.
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GitHub: https://github.com/nature1995/Face_Recognition_System
Compatibility
The code is tested using Tensorflow r1.7 and Movidius NCSDK2 under Debin 2018-06-27(Kernel version:4.14) with django 2.1.1 and Python 3.5.
Real Product Images
Requirements
- Logitech HD Webcam C270
- Micro SD Card 32G
- Raspberry Pi 3 B+
- Intel Movidius Neural Compute Stick
The code requires Python 3.5, Tensorflow 1.7, as well as the following python libraries:
- Pillow
- django
- django-allauth 0.37.1
- django-widget-tweaks 1.4.3
- pip 18.0
- qrcode 6.0
- setuptools 40.4.3
Those modules can be installed using: pip3 install xxx
.
Neural Compute Application Zoo
This repository is a place for any interested developers to share their projects (code and Neural Network content) that make use of the Intel® Movidius™ Neural Compute Stick (Intel® Movidius™ NCS) and associated Intel® Movidius™ Neural Compute Software Development Kit.
You can use the following url(NC App Zoo) or git command to use the ncsdk2 branch of the NC App Zoo repo:
1 | git clone -b ncsdk2 https://github.com/movidius/ncappzoo.git |
Install Django and Django REST framework
1 |
|
Install Adafruit_Python_DHT library
1 |
|
Install Adafruit_Python_BMP library
1 | git clone https://github.com/adafruit/Adafruit_Python_BMP.git |
Install psutil (process and system utilities)
1 | sudo pip3 install psutil |
rpi-mjpg-streamer
Instructions and helper scripts for running mjpg-streamer on Raspberry Pi.
A. Setup mjpg-streamer
Enable Raspberry Pi Camera module from raspi-config
1 | $ sudo raspi-config |
Install necessary packages for mjpg-streamer
1 | $ sudo apt-get update |
Build mjpg-streamer
1 | $ sudo ln -s /usr/include/linux/videodev2.h /usr/include/linux/videodev.h |
Setup video4linux for Raspberry Pi Camera module
1 | $ sudo modprobe bcm2835-v4l2 |
Add yourself to the video group
1 | $ sudo usermod -a -G video $USER |
B. Run mjpg-streamer
1. Clone this repository
1 | $ git clone https://github.com/meinside/rpi-mjpg-streamer.git |
2-a. Run mjpg-streamer from the shell directly
1 | # copy & edit run-mjpg-streamer.sh to your environment or needs |
2-b. Or run mjpg-streamer as a service
systemd
1 | # copy & edit systemd/mjpg-streamer.service file, |
C. Connect
Connect through the web browser:
Most modern browsers(including mobile browsers like Safari and Chrome) will show the live stream immediately.
Notice
Virtualenv
pip3 install virtualenv
Run Virtualenv
source venv/bin/activate
sqlite3 数据库文件db.sqlite3 权限 666
chmod 666 db.sqlite3
django 所在文件夹 权限 775
chmod 777 xxx
Citation
Just can be used for non-business projects.