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:b059854aa82274b16d242ced0892ef9fea15b4df
Arguments:
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:b059854aa82274b16d242ced0892ef9fea15b4df \
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 \
--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:804e5e422ad8845fc73d9e9cdbe8bef22d60b7a0
Arguments:
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 --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:804e5e422ad8845fc73d9e9cdbe8bef22d60b7a0 \
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 \
--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:30f06d0124ac283c0ba22b89ef8d7f8426ab6bc6
Arguments:
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 --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:30f06d0124ac283c0ba22b89ef8d7f8426ab6bc6 \
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 \
--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-6-0:99c973efcfd0b186dc38782d76e862540296b2ea
Arguments:
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 --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-6-0:99c973efcfd0b186dc38782d76e862540296b2ea \
--api-key ei_4e9592296e47dd2c82f7328bf5f3fa8731f553a5bd1c1f730155113ca5dc3d26 \
--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.
