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:a15189e5e7d52ff3d2fccb35a583a0e927424918
Arguments:
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:a15189e5e7d52ff3d2fccb35a583a0e927424918 \
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d \
--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:a1803726d5167036d6e8a5d0c079f37e6b0bffec
Arguments:
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d --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:a1803726d5167036d6e8a5d0c079f37e6b0bffec \
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d \
--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:1e5db20c1391b93019e75e4d5202cee841e59e5c
Arguments:
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d --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:1e5db20c1391b93019e75e4d5202cee841e59e5c \
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d \
--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-6-0:5408ace140917a027d5997fea464bb510b7ccedf
Arguments:
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d --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-6-0:5408ace140917a027d5997fea464bb510b7ccedf \
--api-key ei_84aa1a9aa052951da6ec94f40f86922250f51d8039aa19545ca8a54c5eda7c6d \
--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.
