Deploy to any Linux-based development board
Edge Impulse for Linux lets you run your models on any Linux-based development board,
with SDKs for Node.js, Python, Go and C++ to integrate your models quickly into
your application.
- Install the Edge Impulse Linux CLI
- Run
edge-impulse-linux-runner
(run with --clean
to switch projects)
Run your model as a Docker container
To run your model as a container with an HTTP interface, use:
Container:
public.ecr.aws/g7a8t7v6/inference-container:7994c0f6e72f7223ce694daa669fbd94daae6c5a
Arguments:
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:7994c0f6e72f7223ce694daa669fbd94daae6c5a \
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson's GPUs (JetPack 4.6.x), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson:60eba474f34bbfb0859180f2a339ddff66acb6c1
Arguments:
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson:60eba474f34bbfb0859180f2a339ddff66acb6c1 \
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson Orin's GPUs (JetPack 5.1.x), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin:ccdc07d5acc92616ab72f5c1113d2b6462fa9d01
Arguments:
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin:ccdc07d5acc92616ab72f5c1113d2b6462fa9d01 \
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.
Run your model as a Docker container
To run your model as a container with an HTTP interface on NVIDIA Jetson Orin's GPUs (JetPack 6.0), use:
Container:
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin-6-0:193b04d465abf1bc8d3031c98f5e977b5b206988
Arguments:
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it --runtime=nvidia --gpus all \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container-jetson-orin-6-0:193b04d465abf1bc8d3031c98f5e977b5b206988 \
--api-key ei_fb43dc2aed7bc751f12b4b84ec708a277ddb337c09332a24c544198bc44be701 \
--run-http-server 1337
This automatically builds and downloads the latest model (incl. hardware optimizations), and runs an HTTP endpoint at
http://localhost:1337 with instructions.
Read the docs for information,
like bundling in your model inside the container and selecting extra hardware optimizations.