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:1848ae7fabfb4987cec7376488c277e9d52e7535
Arguments:
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:1848ae7fabfb4987cec7376488c277e9d52e7535 \
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 \
--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:6568bfe7f107e0bbbe21f045521a70b08b33265a
Arguments:
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 --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:6568bfe7f107e0bbbe21f045521a70b08b33265a \
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 \
--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:c2f74e741d438f5788263b4193f370c49695c648
Arguments:
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 --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:c2f74e741d438f5788263b4193f370c49695c648 \
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 \
--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-6-0:63792a8e520c0de76b1e0e0a61a401fc5edc5fb7
Arguments:
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 --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-6-0:63792a8e520c0de76b1e0e0a61a401fc5edc5fb7 \
--api-key ei_849771ca2dbd8dfe0040dfe9a07cb4c0d0776366cbac35909fe875be3c79acf6 \
--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.
