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:02f6d0cd1b6cb5d3089ee7a8d22b382bdeae4954
Arguments:
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:02f6d0cd1b6cb5d3089ee7a8d22b382bdeae4954 \
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 \
--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:9c09a8ad25845357da7e6bbb22086898f7782d71
Arguments:
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 --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:9c09a8ad25845357da7e6bbb22086898f7782d71 \
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 \
--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:a2a77ce86b87bd43f2ca792ba9f9ddff20464236
Arguments:
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 --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:a2a77ce86b87bd43f2ca792ba9f9ddff20464236 \
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 \
--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-6-0:03d0782ba5b8454177e0f14f2a5eff9766681e4d
Arguments:
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 --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-6-0:03d0782ba5b8454177e0f14f2a5eff9766681e4d \
--api-key ei_c61a99ac10fbdb558d9150f12049543d6856e934b4c4c6b4225f6f1d88e968c3 \
--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.
