Raspberry Pi | 4 min | 452
coralcoral usb acceleratordockeredge-tpumachine learningraspberry piteachable machinetensorflow lite
Last week, the Coral team released updates to the Coral platform to "address customer feedback and make it easier to use the products and tool-chain". The Python API has now the ability to run multiple models in parallel, using multiple Edge TPUs.
Thus, due to the multiple changes, I updated the Docker image
lemariva/raspbian-edgetpuwhich includes the Edge-TPU libraries for Raspberry Pi 3 B+, Jupyter Notebooks and some other interesting libraries (check the Dockerfile).
Fig 1: Coral USB Accelerator, Jupyter and some training objects
The base Docker image remained
Raspberry Pi | 4 min | 142
dockerembeddedhass.iohome assistantraspberry pisensorsxiaomizigbee
Last week, I published an article about using Xiaomi sensors without a Xiaomi Gateway. The gateway/hub can be replaced with a Raspberry Pi and a USB-ZigBee dongle. You find the instructions here: #ZigBee: Xiaomi Sensors using Raspberry Pi (without Gateway!).
As you can read in that article, two repositories are available to connect and process the data from the Xiaomi sensors. Additionally, Zigbee2mqtt can be connected to Hass.io. Well, I didn't want to use HassOS (the OS on which hass.io runs), but I wanted to use Hass.io running on Raspbian, otherwise with Home Assistant running as an appli...
Raspberry Pi | 5 min | 7805
aqaradoor sensorhome assistanthome automationmqttpirraspberry pixiaomi gatewayxiaomi sensorszigbee
This is what I will try to accomplish in this tutorial:
- Flash the USB-Zigbee Dongle with the correct FW
- Install a broker to connect to the sensors
- Configure the sensors using the broker
Xiaomi sensors use Zigbee for the connection which means we need some extra components to connect to them. This is the list of needed hardware:
Wireless Zigbee CC2531 x1 SmartRF04EB x1 Debugger Cable x1
Raspberry Pi | 4 min | 1151
analyticscoraldockeredge-tpumachine learningobject detection
In summer 2018, Google announced two Edge TPU devices for machine learning. These are now available under the Coral brand. Two weeks ago, I bought the Coral USB Accelerator. It is a portable USB accessory that brings machine learning inferencing to existing systems and it is compatible with Raspberry Pi and other Linux systems.
Fig. 1: Coral USB Accelerator, Raspberry Pi Camera and a RasPad
I wanted to test the performance of the Edge-TPU on my Raspberry Pi3, and as I have every application running on Docker on my Raspberry Pi, I've created a Docker image with everything inside t...
Raspberry Pi | 5 min | 384
cup serverdockerdockerizedprint serverprinterraspberry pitutorial
A good friend of mine has an old printer and he was always thinking of buying some adapter to make it Wi-Fi compatible. He actually bought one, but it was not compatible! I told him to buy a Raspberry Pi W Zero and build a CUPS Print Server, but he did not have time to do that, so I planned as XMas gift! I hope he is not going to read this before he gets his present. :) - If you received this as a gift, your instructions are here.
A big challenge was to make it plug & play. I did not want to have his Wi-Fi credentials, and he should not use a terminal over SSH to configure it. I looked for som...
batteryraspadraspberry pitable for raspberry pitouch screen
This is my first review on a product that I bought. I hope you enjoy it! Advices and tips are welcome. Please leave me them in the comment section.
Update: I changed the title of the article from "#Reviews: RasPad - an open source tablet for Raspberry Pi" to "#Reviews: RasPad - a tablet for open-source platforms like Raspberry Pi". The table is a close-source solution for open-source platforms like Raspberry Pi, Beaglebone, etc. (thanks Zykino for your advice!)
At the beginning of March I supported the Kickstarter campaign called RasPad. I pledged for the
Super Early Bird - RasPad...