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:8a314a54172e0a7644a5eb177351afbf67314d90
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:8a314a54172e0a7644a5eb177351afbf67314d90 \
--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:303d113a42c38bbbac3af4b69194e5b1e88198ba
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:303d113a42c38bbbac3af4b69194e5b1e88198ba \
--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:df6a98c1a46b3bb13bfbfddadda3259e05627528
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:df6a98c1a46b3bb13bfbfddadda3259e05627528 \
--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-6-0:2e763ba656e1791d52a9b3cff6f30d9844c90c0f
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-6-0:2e763ba656e1791d52a9b3cff6f30d9844c90c0f \
--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.
