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:8ac461741cb28a58c905c2edbad1cbe33af1a486
Arguments:
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:8ac461741cb28a58c905c2edbad1cbe33af1a486 \
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 \
--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:be640638c099b35a5db9924d3d67558acd84183d
Arguments:
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 --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:be640638c099b35a5db9924d3d67558acd84183d \
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 \
--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:add8d056efc339e061f7aa6265827f6777421a5c
Arguments:
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 --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:add8d056efc339e061f7aa6265827f6777421a5c \
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 \
--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:dd9a0121b426fa4d800b8d82cc6d4b803bf62c02
Arguments:
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 --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:dd9a0121b426fa4d800b8d82cc6d4b803bf62c02 \
--api-key ei_f520b64008880793132fef4d8bfc62bdfd7b168c35e9ab47570f3b4fcf4de888 \
--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.