Raspberry Pi


Pi Zero Face Recognition

posted Apr 25, 2019, 3:58 PM by Chris G   [ updated Apr 25, 2019, 3:58 PM ]


Face Recognition Raspberry Pi Zero Party Greeter


Building a face recognition system to recognize the faces of my friends and welcome them to a party.

There are a few ways of building a system like this. Possibly the simplest approach is using this library – https://github.com/ageitgey/face_recognition that is built on Built using dlib's state-of-the-art face recognition built with deep learning.. I’m using a Raspberry Pi Zero W with the Pi Zero Camera for the face recognition and a cheap Bluetooth module and speaker to announce friends with a greeting when a face is recognized. If the face is known to the system than the person's name is included in the greeting.

Read the full article at:

How To Disable The Red LED On The Pi Camera Module

posted Dec 17, 2018, 8:35 AM by Chris G   [ updated Dec 17, 2018, 8:36 AM ]

The Pi camera module includes a red LED in one corner of the PCB. This lights up when the camera is active. It’s really useful in giving a visual indication that the camera is doing something and most of the time you will be glad it is there.

However there are a number of reasons you might wish it wasn’t.


To disable the red LED you simply need to add the following line to your config.txt file :

disable_camera_led=1

To edit the config.txt file you can use Nano :

sudo nano /boot/config.txt


python picamera motion detection

posted Dec 5, 2018, 6:38 PM by Chris G   [ updated Dec 5, 2018, 6:38 PM ]

A simple example of using the Raspberry Pi Camera Module and python picamera for motion detection without any additional dependencies.


FutureSharks/raspberrypi-picamera-motion-detection.py

Kerberos.io - a low-budget video surveillance solution for the Raspberry Pi

posted Dec 5, 2018, 6:34 PM by Chris G   [ updated Dec 5, 2018, 6:35 PM ]

What's Kerberos.io?

Video surveillance made easy

Kerberos.io is a free, open-source video surveillance solution, which works with any camera and on every Linux based machine. You can deploy a fully configured video surveillance system within a few minutes on the environment you prefer: Raspberry Pi, Orange Pi, Docker, etc.


Kerberos.io is a low-budget video surveillance solution, that uses computer vision algorithms to detect changes, and that can trigger other devices. Kerberos.io is open source so everyone can customize the source code to its needs and share it with the community under the CC-NC-ND license model. When deployed on the Raspberry Pi or any other board, it has a green footprint and it's easy to install; you only need to transfer the Kerberos.io OS (KIOS) to your SD card and that's it.



Pi Eyes

posted Dec 30, 2017, 6:50 AM by Chris G   [ updated Dec 30, 2017, 6:51 AM ]

Pi_Eyes

The Python code in this repository allows users to display 3D renditions of eyes on any Raspberry Pi display:



You can also view the full project and hardware requirements on the adafruit website:

How to setup tmpfs as ramdisk to protect SD card

posted Dec 28, 2017, 7:26 PM by Chris G   [ updated Dec 28, 2017, 7:28 PM ]

How to setup tmpfs as ramdisk to protect SD card


https://www.raspberrypi.org/forums/viewtopic.php?t=107265

Add the following to /etc/fstab:-
sudo nano /etc/fstab


tmpfs /tmp  tmpfs defaults,noatime 0 0
tmpfs /var/log  tmpfs defaults,noatime,size=16m 0 0

Raspberry Pi controlling GPIO in Python

posted Sep 3, 2016, 2:52 AM by Chris G   [ updated Sep 3, 2016, 2:53 AM ]


A simple interface to everyday GPIO components used with Raspberry Pi.

Component interfaces are provided to allow a frictionless way to get started with physical computing


This is by far the easiest way to control your Pi's GPIO devices using Python. LED, push-buttons, motion sensors, etc.

Install OpenCV 3.30 for Python 3.6 on MacOS

posted Sep 2, 2016, 4:27 AM by Chris G   [ updated Dec 30, 2017, 7:09 AM ]

How to Install OpenCV 3.30 MacOS High Sierra:


  The best way is simply to use homebrew: 
  

ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
brew update
#brew install git cmake
brew install pkg-config jpeg libpng libtiff openexr eigen tbb
brew install opencv3 --with-contrib --with-python3  

Homebrew will unfortunately not install the package in the proper location, so we need to rename the package and link it to the proper place for Python to find it. Adjust accordingly for your OS and Python version. 


mv /usr/local/opt/opencv/lib/python3.6/site-packages/cv2.cpython-36m-darwin.so /usr/local/opt/opencv/lib/python3.6/site-packages/cv2.so
#echo /usr/local/opt/opencv/lib/python3.6/site-packages/ >> /usr/local/lib/python3.6/site-packages/opencv3.pth
echo /usr/local/opt/opencv/lib/python3.6/site-packages/ >> /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/opencv3.pth
#python3 -c "import sys; print(next(p for p in sys.path if 'site-packages' in p))"

Finally...verify the installation:

python

Type "help", "copyright", "credits" or "license" for more inform
>>> cv2.__version__


Installing OpenCV 3.1 on Raspbian Jessie

posted Aug 25, 2016, 3:59 AM by Chris G   [ updated Aug 25, 2016, 4:00 AM ]

While it is relatively easy to install OpenCV 2 on the Raspberry Pi (apt-get), getting the enhancements available in version 3.1 requires a bit more work.

Fortunately, there is a very nice script that will do most of the work for you, and it is available at:



Simply download the latest version of the script, make it executable, and run it! It will take quite some time to build though, but it will take care of all the dependencies.

However, using OpenCV on a Raspberry Pi with only 512MB or RAM offers some very limited options...but with 1GB or RAM the performance is not too bad.

Enjoy!

Add Facial Recognition to your Raspberry Pi

posted Aug 9, 2016, 5:34 PM by Chris G   [ updated Aug 9, 2016, 5:36 PM ]

The Microsoft Cognitive Services Faces API allows you to not only recognize faces in photos, but also to identify specific people based on a trained model.

For more information, and the API definition, see the following links:

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