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The Coral USB Accelerator is a USB device that provides an Edge TPU as a coprocessor for yourcomputer. It accelerates inferencing for your machine learning models when attached to eithera Linux, Mac, or Windows host computer. This page is your guide to get started.
All you need to do is download the Edge TPU runtime and the TensorFlow Lite library on thecomputer where you'll connect the USB Accelerator. Then we'll show you how to perform imageclassification with an example app.
If you want to learn more about the hardware, see theUSB Accelerator datasheet.
Requirements
Raspberry Pi Desktop is the PC and Mac version of the Raspbian desktop, as used on the Raspberry Pi. Using the disc that comes with issue 60, you can install. Many of the Raspberry Pi users would like to run Desktop on the Raspberry Pi. This article provides you with the steps to use your PC or Mac to run the Raspberry Pi Foundation’s desktop operating system, Debian with the Raspberry Pi Desktop. This OS is very much similar to the Raspbian and both of. Homebridge adds HomeKit support to your non-HomeKit smart home devices. The raspberry pi desktop for pc and mac based on debian. Android on the other hand has more compatibility with third party apps and services especially streaming ones. Running Mac Os 9 On Raspberry Pi install ios on raspberry pi is important information accompanied by photo and HD pictures sourced from all websites in the world.
The Raspberry Pi 3 Model B+ comes with Wi-Fi and Bluetooth already installed, so besides the initial setup, you don’t need to install additional drivers or Linux dependencies.
- A computer with one of the following operating systems:
- Linux Debian 10, or a derivative thereof (such as Ubuntu 18.04), and a system architecture of either x86-64, Armv7 (32-bit), or Armv8 (64-bit) (Raspberry Pi is supported, but we have only tested Raspberry Pi 3 Model B+ and Raspberry Pi 4)
- macOS 10.15, with either MacPorts or Homebrew installed
- Windows 10
- One available USB port (for the best performance, use a USB 3.0 port)
- Python 3.5, 3.6, or 3.7
1: Install the Edge TPU runtime
The Edge TPU runtime provides the core programming interface for the Edge TPU. You can install it onyour host computer as follows, on Linux, on Mac, oron Windows.
1a: On Linux
- Add our Debian package repository to your system:
- Install the Edge TPU runtime:
- Now connect the USB Accelerator to your computer using the provided USB 3.0 cable. If you alreadyplugged it in, remove it and replug it so the newly-installed
udev
rule can take effect.
Then continue to install the TensorFlow Lite library.
Install with maximum operating frequency (optional)
The above command installs the standard Edge TPU runtime for Linux, which operates the device at areduced clock frequency. You can instead install a runtime version that operates at the maximumclock frequency. This increases the inferencing speed but also increases powerconsumption and causes the USB Accelerator to become very hot.
If you're not certain your application requires increased performance, you should use the reducedoperating frequency. Otherwise, you can install the maximum frequency runtime as follows:
You cannot have both versions of the runtime installed at the same time, but you can switch bysimply installing the alternate runtime as shown above.
Caution: When operating the device using the maximum clock frequency, the metal on the USB Accelerator can become very hot to the touch. This might cause burn injuries. To avoid injury, either keep the device out of reach when operating it at maximum frequency, or use the reduced clock frequency.
1b: On Mac
- Download and unpack the Edge TPU runtime:
- Install the Edge TPU runtime:The installation script will ask whether you want to enable the maximum operating frequency.Running at the maximum operating frequency increases the inferencing speed but also increasespower consumption and causes the USB Accelerator to become very hot. If you're not certain yourapplication requires increased performance, you should type 'N' to use the reduced operatingfrequency.You can read more about the performance setting in the USBAccelerator datasheet.
- Now connect the USB Accelerator to your computer using the provided USB 3.0 cable.
Then continue to install the TensorFlow Lite library.
1c: On Windows
- First, make sure you have the latest version of the Microsoft Visual C++ 2019 redistributable.
- Then download edgetpu_runtime_20200728.zip.
- Extract the ZIP files and double-click the
install.bat
file inside.A console opens to run the install script and it asks whether you want to enablethe maximum operating frequency. Running at the maximum operating frequency increases theinferencing speed but also increases power consumption and causes the USB Accelerator to becomevery hot. If you're not certain your application requires increased performance, you should type'N' to use the reduced operating frequency.You can read more about the performance setting in the USBAccelerator datasheet. - Now connect the USB Accelerator to your computer using the provided USB 3.0 cable.
2: Install the TensorFlow Lite library
There are several ways you can install TensorFlow Lite APIs, but to get started with Python,the easiest option is to install the
tflite_runtime
library. This library provides the bareminimum code required to run an inference with Python (primarily, the Interpreter
API), thus saving you a lot ofdisk space.To install it, follow the TensorFlow Lite Python quickstart, and then return to this page after you run the
pip3 install
command.3: Run a model using the TensorFlow Lite API
Now you're ready to run an inference on the Edge TPU.
Windows users: The following code relies on a Bash script to install dependencies. If you're new to using Bash on Windows, we suggest you try either Windows Subsystem for Linux or Git Bash from Git for Windows.
Follow these steps to perform image classification with our example code and model:
- Download the example code from GitHub:
- Download the bird classifier model, labels file, and a bird photo:
- Run the image classifier with the bird photo (shown in figure 1):
You should see results like this:
Congrats! You just performed an inference on the Edge TPU using TensorFlow Lite.
To demonstrate varying inference speeds, the example repeats the same inference five times. Itprints the time to perform each inference and then the top classification result (the label ID/nameand the confidence score, from 0 to 1.0). Your inference speeds might differ based on your hostsystem and whether you're using a USB 3.0 connection.
To learn more about how the code works, take a look at the
classify_image.py
source codeand read about how to run inference with TensorFlow Lite.Note:The example above uses the TensorFlow Lite Python API, but you can also run aninference using the Edge TPU Python API or the TensorFlow Lite C++ API. For information abouteach option, read the Edge TPU inferencing overview.
Next steps
To run some other types of neural networks, check out our example projects,including examples that perform real-time object detection, pose estimation, keyphrasedetection, on-device transfer learning, and more.
If you want to create your own model, try these tutorials:
- Retrain an image classification model using post-training quantization (runs in Google Colab)
- Retrain an image classification model using quantization-aware training (runs in Docker)
- Retrain an object detection model using quantization-aware training (runs in Docker)
Or to create your own model that's compatible with the Edge TPU, readTensorFlow Models on the Edge TPU.
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Regular readers will know that we first gave away a copy of The Raspberry Pi Desktop operating system with issue 53 of The MagPi. Well, we’re back with an update. The latest version of The Raspberry Pi Desktop x86 is included with the print edition of this month’s magazine.
You can still run the Raspberry Pi Desktop on a PC or Mac computer, but now you can also install the Raspberry Pi Desktop on your hard drive, replacing the previous operating system.
This DVD is an ideal tool for adapting an old computer into a useful coding and hacking machine. The Raspberry Pi Desktop x86 runs on most computers with an Intel x86 architecture. We’ve run it successfully on many old PC and Mac devices.
United app for mac. The full article can be found in The MagPi 60 and was written by Lucy Hattersley.
Let’s look at how to go about doing a basic installation of The Raspberry Pi Desktop x86 on an old PC or Mac computer.
Warning! This tutorial erases the operating system running on your computer.
Raspberry Pi Install Package
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You'll need
- Mac or PC with optical drive
- The Raspberry Pi Desktop x86 DVD
- The Raspberry Pi Desktop x86 ISO image file
- USB thumb drive
How to: Use The Raspberry Pi Desktop x86
STEP-01 Boot from DVD on a PC
The free DVD bundled with the print edition of The MagPi #60 can be used to start up a PC or Mac computer with an optical DVD drive. Turn off your computer and insert the DVD. Most PC computers are set up to boot from the optical drive before the hard drive, and you should see the Debian GNU/Linux installer boot menu. If it does not boot from the DVD, you need to change the Boot Priority Order in your BIOS settings. On most PCs, you press F1 during boot to do this.
Apple Mac computers are designed to boot from the hard drive first, and not from an inserted DVD. Insert the DVD into your Mac and shut it down. Now power it up and hold down the C key. The menu should boot from the DVD. If this doesn’t work, hold down the Option key (marked ‘alt’) and choose the EFI Boot icon.
STEP-02 Boot menu
![Raspberry pi install mariadb Raspberry pi install mariadb](https://cdn-learn.adafruit.com/assets/assets/000/005/899/original/raspberry_pi_installing_raspbmc_mac.png?1396829352)
The new version of The Raspberry Pi Desktop features a boot menu. Here you’ll see seven options: Run with persistence, Run and reset persistence, Run without persistence, Install, Graphical install, and Advanced options.
STEP-03 Run Raspbian
Choose ‘Run without persistence’ to quickly boot into the Raspberry Pi Desktop x86 operating system. Here you can experiment and play around. Be warned that it won’t save any files. For this, you need to choose ‘Run with persistence’, and attach a USB pen drive to your computer. The persistence drive saves any files you create while using Raspbian (see The MagPi #53 for an in-depth explanation of persistence).
Mac On Raspberry Pi
STEP-04 Install
Two options are available: Install and Graphical install. Both offer a similar experience. You’ll find additional settings under Advanced options. Select Install. Run through the Configuration options using the arrow keys and Enter. You’ll now see ‘Loading additional components’.
STEP-05 Partition disks
You have several options for partitioning disks. We’re going with ‘Guided – use entire disk’. Note that this wipes the original operating system! Choose the correct disk from the Partition Disks list and ‘All files in one partition’. Finally, select Finish partitioning, write changes to disk, and Yes.
STEP-06 Installing the system
Wait for the system to be installed on your hard drive. Choose Yes to Install the GRUB boot loader on a hard disk, and pick your device from the list (typically it will be /dev/sda on a single disk machine). When you see ‘Installation is complete’, click Continue. Your computer will reboot and start up in the Raspberry Pi Desktop.
Mac Classic Raspberry Pi
Install Raspberry Pi Desktop on a Mac without a DVD drive using a thumb drive
We had some trouble installing the Raspberry Pi Desktop on an old Macbook. We think it might be because the Macbook drive was very old.
A few people asked us for help on this one. So, we also produced this bonus video which shows you how to take the Raspberry Pi Desktop file and turn it into a Mac thumb drive installer. This enables you to bypass the CD/DVD drive on a Mac and install straight from a USB thumb drive.
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Raspberry Pi Install Camera Module
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