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:4154ca1e32bd624ffabece9f281494041acc2ffa
Arguments:
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:4154ca1e32bd624ffabece9f281494041acc2ffa \
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 \
--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:6c6c56120323653b7d5195373cc543ae2e18e861
Arguments:
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 --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:6c6c56120323653b7d5195373cc543ae2e18e861 \
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 \
--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:033e52714eebce3c1c35200cd05890a3b6d36b5c
Arguments:
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 --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:033e52714eebce3c1c35200cd05890a3b6d36b5c \
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 \
--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-6-0:313f50b3512595611ef5b8be0a804b41b7b6f916
Arguments:
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 --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-6-0:313f50b3512595611ef5b8be0a804b41b7b6f916 \
--api-key ei_3bce2a45340bac2c22982f536ea1a25a382ca7d35245fc7e2dc91ea822612395 \
--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.
