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:35668a240a066b55c76328d1babd0da83787e0e9
Arguments:
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:35668a240a066b55c76328d1babd0da83787e0e9 \
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 \
--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:50816643426355c8ea8ce5b86ef4d9ad68328754
Arguments:
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 --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:50816643426355c8ea8ce5b86ef4d9ad68328754 \
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 \
--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:39a800b7e6aa8edb0db5b4b24314abec0c34831c
Arguments:
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 --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:39a800b7e6aa8edb0db5b4b24314abec0c34831c \
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 \
--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-6-0:32d73964641aa09767ac4eeb3626c2bceaf60feb
Arguments:
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 --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-6-0:32d73964641aa09767ac4eeb3626c2bceaf60feb \
--api-key ei_745c10f7e7e4e2dad47d76a1bb230163a2e3cb878dcb30338ecb489f35b1ef49 \
--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.
