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:1dbc421cf3fff5c2a02f229c2cd05cb0377b1ace
Arguments:
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:1dbc421cf3fff5c2a02f229c2cd05cb0377b1ace \
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b \
--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:cf9cf00e05a46d552b9383f2b3b41b663a20ef94
Arguments:
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b --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:cf9cf00e05a46d552b9383f2b3b41b663a20ef94 \
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b \
--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:8f5af924efc4b944b531aa4dc632b4a3d10c6a6f
Arguments:
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b --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:8f5af924efc4b944b531aa4dc632b4a3d10c6a6f \
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b \
--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:e348bd92b724494c3c496f4860c3002d76ef52dc
Arguments:
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b --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:e348bd92b724494c3c496f4860c3002d76ef52dc \
--api-key ei_c33da741dc38a16e7046ce8c021a8d19ebd69f65801d5e2e143e70395677138b \
--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.
