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:7a21fe51fb82a2a89c24e4e58b497998afe4b5ec
Arguments:
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b --run-http-server 1337
For example, in a one-liner locally:
docker run --rm -it \
-p 1337:1337 \
public.ecr.aws/g7a8t7v6/inference-container:7a21fe51fb82a2a89c24e4e58b497998afe4b5ec \
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b \
--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:424702687c249c952ea9c4fd9338400ae7749cbf
Arguments:
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b --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:424702687c249c952ea9c4fd9338400ae7749cbf \
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b \
--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:68a4d5a75852d8476db2704da99b73de9cdb9832
Arguments:
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b --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:68a4d5a75852d8476db2704da99b73de9cdb9832 \
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b \
--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-6-0:15b52abc5b6cf074d41598b9b952ae3e8d70bed4
Arguments:
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b --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-6-0:15b52abc5b6cf074d41598b9b952ae3e8d70bed4 \
--api-key ei_dee47db1d779e60ef8ce2efcfedd73e7fd85a1b7c507344370401fd23950370b \
--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.
