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:88fdcc9ced8d8feb149a37e809cb835e49d4baf7
Arguments:
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:88fdcc9ced8d8feb149a37e809cb835e49d4baf7 \
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d \
--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:479ee38c84553250970af5d2226442df1c56aa83
Arguments:
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d --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:479ee38c84553250970af5d2226442df1c56aa83 \
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d \
--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:d810b687a4952ec9c3f4e21c2728ae84ff3d8c99
Arguments:
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d --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:d810b687a4952ec9c3f4e21c2728ae84ff3d8c99 \
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d \
--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-6-0:23ed6195d87f28b457407aad7892332532836aa6
Arguments:
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d --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-6-0:23ed6195d87f28b457407aad7892332532836aa6 \
--api-key ei_b8b44e3867c08470b5243fd841ba0fcf41d621787c279f7148c05673b26f0e0d \
--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.
