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:f4270a3f7c464e66c2879b885d6bbb40c7fc3e5f
Arguments:
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:f4270a3f7c464e66c2879b885d6bbb40c7fc3e5f \
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 \
--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:4930b05e500ae30cba1cd4a8b30848ec8d5fdb1c
Arguments:
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 --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:4930b05e500ae30cba1cd4a8b30848ec8d5fdb1c \
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 \
--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:0987afc99483178f9ef75a30f037bef11d85f4c7
Arguments:
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 --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:0987afc99483178f9ef75a30f037bef11d85f4c7 \
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 \
--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-6-0:8b79ee1cd3f5134db1ec14ed6b5560f56d92476e
Arguments:
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 --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-6-0:8b79ee1cd3f5134db1ec14ed6b5560f56d92476e \
--api-key ei_635da8632248a085e3a99a1296a3db361d4cbeeaa517bb35fa6336edc3d69830 \
--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.