Installation
- Linux, MacOS, and Raspberry Pi OS
- Windows Subsystem for Linux (WSL)
-
Install Node.js v16.x+ or above on your host computer.
Alternatively, run the following commands:
The last command should return the node version, v16 or above. Let’s verify the node installation directory:
curl -sL https://deb.nodesource.com/setup_22.x | sudo -E bash - sudo apt install -y gcc g++ make build-essential nodejs sox gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-base gstreamer1.0-plugins-base-apps node -vIf it returns /usr/local/, run the following commands to change npm’s default directory:npm config get prefixOn MacOS you might be using zsh as default, so you will want to update the correct profilemkdir ~/.npm-global npm config set prefix '~/.npm-global' echo 'export PATH=~/.npm-global/bin:$PATH' >> ~/.profilemkdir ~/.npm-global npm config set prefix '~/.npm-global' echo 'export PATH=~/.npm-global/bin:$PATH' >> ~/.zprofile -
Install the CLI tools via:
npm install -g edge-impulse-linux
Windows Subsystem for Linux (WSL) allows you to run a Linux environment directly on Windows. This is particularly useful for developers who want to use Linux-based tools and workflows on a Windows machine.To install the Edge Impulse CLI using WSL, follow these steps:You can find full instructions on how to install WSL here.Once complete you can then enable WSL by running the following command in PowerShell as an Administrator:If you are using WSL, you will need to install the following npm packages, and may need to install audio / video dependencies for your machine:e.g. audio dependencies for Ubuntu:npm route for WSL use administrator user permissions:Then proceed with installing the Linux CLI:
- Create an Edge Impulse account.
- Install WSL on your Windows machine.
wsl --install
wsl
sudo apt-get install libportaudio2 libportaudiocpp0 portaudio19-dev
sudo apt install -y gcc g++ make build-essential nodejs sox gstreamer1.0-tools gstreamer1.0-plugins-good gstreamer1.0-plugins-base gstreamer1.0-plugins-base-apps
sudo npm install -g edge-impulse-linux --unsafe-perm
sudo npm install -g edge-impulse-linux --unsafe-perm
Edge Impulse Linux
edge-impulse-linux --help
Usage: edge-impulse-linux [options]
Edge Impulse Linux client 1.18.1
Options:
-V, --version output the version number
--api-key <key> API key to authenticate with Edge Impulse (overrides
current credentials)
--hmac-key <key> HMAC key to sign new data with (overrides current
credentials)
--disable-camera Don't prompt for camera
--disable-microphone Don't prompt for microphone
--width <px> Desired width of the camera stream
--height <px> Desired height of the camera stream
--gst-launch-args <args> Override the arguments to gst-launch-1.0. This should
be a stream that returns JPEG images, e.g.: "v4l2src
device=/dev/video0 ! video/x-raw,width=640,height=480
! videoconvert ! jpegenc"
--clean Clear credentials
--silent Run in silent mode, don't prompt for credentials
--dev List development servers, alternatively you can use
the EI_HOST environmental variable to specify the Edge
Impulse instance.
--camera <camera> Which camera to use (either the name, or the device
address - e.g. /dev/video0). If this argument is
omitted, and multiple cameras are found, a CLI
selector is shown.
--microphone <microphone> Which microphone to use (either the name, or the
device address). If this argument is omitted, and
multiple microphones are found, a CLI selector is
shown.
--verbose Enable debug logs
--greengrass Enable AWS IoT greengrass integration mode
-h, --help output usage information
Edge Impulse Linux Runner
edge-impulse-linux-runner --help
Usage: edge-impulse-linux-runner [options]
Edge Impulse Linux runner 1.18.1
Options:
-V, --version output the version number
--model-file <file> Specify model file (either path to .eim, or
the socket on which the model is running), if
not provided the model will be fetched from
Edge Impulse
--api-key <key> API key to authenticate with Edge Impulse
(overrides current credentials)
--download <file> Just download the model and store it on the
file system
--list-targets List all supported targets and inference
engines
--force-target <target> Do not autodetect the target system, but set
it by hand (e.g. "runner-linux-aarch64")
--force-engine <engine> Do not autodetect the inference engine, but
set it by hand (e.g. "tflite")
--force-variant <variant> Do not autodetect the model variant, but set
it by hand (e.g. "int8")
--force-resize-mode <mode> Do not use the resize method from the
impulse, but set it by hand (valid: "squash",
"fit-shortest" or "fit-longest")
--impulse-id <impulseId> Select the impulse ID (if you have multiple
impulses)
--run-http-server <port> Do not run using a sensor, but instead expose
an API server at the specified port
--preview-port <port> Port to use to render the preview HTTP
interface (default: 4912) (ignored when
running with --run-http-server).
Alternatively you can use the PORT
environmental variable. If both are set then
`--preview-port` takes precedence.
--preview-host <host> Host to listen on for the preview HTTP
interface (default: 0.0.0.0) (ignored when
running with --run-http-server).
Alternatively you can use the HOST
environmental variable. If both are set then
`--preview-host` takes precedence.
--preview-original-resolution If set, does not resize the preview image to
the impulse resolution
--monitor Enable model monitoring (default: false)
--monitor-max-storage-size <size> The maximum storage size to be used for model
monitoring, in MB. Defaults to 250.
--monitor-summary-interval-ms <ms> The time interval (in milliseconds) for model
monitoring summaries. Defaults to 60000.
--clean Clear credentials
--silent Run in silent mode, don't prompt for
credentials
--quantized Download int8 quantized neural networks,
rather than the float32 neural networks.
These might run faster on some architectures,
but have reduced accuracy.
--enable-camera Always enable the camera. This flag needs to
be used to get data from the microphone on
some USB webcams.
--gst-launch-args <args> Override the arguments to gst-launch-1.0.
This should be a stream that returns JPEG
images, e.g.: "v4l2src device=/dev/video0 !
video/x-raw,width=640,height=480 !
videoconvert ! jpegenc"
--dev List development servers, alternatively you
can use the EI_HOST environmental variable to
specify the Edge Impulse instance.
--greengrass Enable AWS IoT greengrass integration mode
--dont-print-predictions If set, suppresses the printing of
predictions
--thresholds <values> Override model thresholds. E.g. --thresholds
4.min_anomaly_score=35 overrides the min.
anomaly score for block ID 4 to 35.The
current thresholds are printed on startup.
--mode <mode> Either: "streaming" (runs on a camera/audio
stream and outputs a live inference server)
or "http-server" (opens an HTTP server for
inference on-demand). When passing
--run-http-server XXX in, the mode will
always default to "http-server", in all other
cases the mode defaults to "streaming".
--camera <camera> Which camera to use (either the name, or the
device address - e.g. /dev/video0). If this
argument is omitted, and multiple cameras are
found, a CLI selector is shown.
--microphone <microphone> Which microphone to use (either the name, or
the device address). If this argument is
omitted, and multiple microphones are found,
a CLI selector is shown.
--shm-behavior <mode> Whether to use shared memory to communicate
between .eim file and Linux runner
(experimental feature), valid: "auto",
"always", "never". If not set, defaults to
'auto' - which will use shm if available, and
fall back to JSON over TCP otherwise. If set
to 'always' will only use shm to communicate
(errors out if not available), if set to
'never' will always use JSON over TCP socket.
--profiling If set, prints profiling info
--verbose Enable debug logs
-h, --help output usage information
Edge Impulse Linux Runner Inter-process Communication Debugging
If you are getting errors with the runner you can get additional debug data. With your EIM model downloaded use two terminals with the following commands to print additional debug data. Terminal 1:$ ./<path-to-model.eim> /tmp/ei.socket
$ edge-impulse-linux-runner --model-file /tmp/ei.socket